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The Computer Science Department has a rich history of published research relating to a variety of computer science interests. Many of the publications below were completed by or with assistance from graduate students. Experience with published research is an important part of graduate school and we encourage our students to take part in or lead research with the intention of being published.  

Publications

• 2022-23
  • T. W. Hartman, E. Radichev, Hafiz M. Ali, et al., “BASIN: A semi-automatic workflow, with machine learning segmentation, for objective statistical analysis of biomedical and biofilm image datasets.” Journal of Molecular Biology (2022): 167895, December 2022.
  • Hafiz M. Ali, Bomgni, A.B., Bukhari, S.A.C. et al. “Power-Aware Fog Supported IoT Network for Healthcare Infrastructure Using Swarm Intelligence-Based Algorithms”. Mobile Netw Appl, January 2023.
  • A.B. Bomgni, Hafiz M. Ali, et al., “Multi-hop uplink communication approach based on layer clustering in LoRa networks for emerging IoT Applications.” Mobile Information Systems. May 2023.
  • T. Chase, Ali J. Ben Ali, S. Y. Ko and K. Dantu. "PRE-SLAM: Persistence Reasoning in Edge-assisted Visual SLAM," 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS), Denver, CO, USA, December 2022, pp. 458-466.
  • Ali J. Ben Ali, Marziye Kouroshli, Sofiya Semenova, Zakieh Sadat Hashemifar, Steven Y. Ko, and Karthik Dantu. “Edge-SLAM: Edge-Assisted Visual Simultaneous Localization and Mapping”. ACM Trans. Embed. Comput. Syst. 22, 1, Article 18, January 2023.
  • Si, W. M., Backes, M., Blackburn, J., De Cristofaro, E., Stringhini, G., Zannettou, S., & Zhang, Y. (2022, November). Why So Toxic? Measuring and Triggering Toxic Behavior in Open-Domain Chatbots. In Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security (pp. 2659-2673).
  • Paudel, P., Blackburn, J., De Cristofaro, E., Zannettou, S., & Stringhini, G. (2022, December). LAMBRETTA: Learning to Rank for Twitter Soft Moderation. In 2023 IEEE Symposium on Security and Privacy (SP) (pp. 1542-1557).
  • Balci, U., Ling, C., De Cristofaro, E., Squire, M., Stringhini, G., & Blackburn, J. (2023, April). Beyond Fish and Bicycles: Exploring the Varieties of Online Women’s Ideological Spaces. In Proceedings of the 15th ACM Web Science Conference 2023 (pp. 43-54).
  • Yudhoatmojo, S., De Cristofaro, E., & Blackburn, J. (2023, April). Understanding the Use of e-Prints on Reddit and 4chan’s Politically Incorrect Board. In Proceedings of the 15th ACM Web Science Conference 2023 (pp. 117-127).
  • Kevyn Irizary, Zichen Zhang, Christopher Stewart, Jayson Boubin. “Scalable distributed microservices for autonomous UAV swarms.” ACM/IFIP Middleware, November 2022.
  • Jayson Boubin, Codi Burley, Peida Han, Bowen Li, Barry Porter, Christopher Stewart. “MARbLE: Multi-Agent Reinforcement Learning at the Edge for Digital Agriculture.” IEEE/ACM Symposium on Edge Computing (SEC), December 2022.
  • Chengyi Qu, Jayson Boubin, Durbek Gafurov, Jianfeng Zhou, Noel Aloysius, Henry Nguyen, Prasad Calyam. “UAV Swarms in Smart Agriculture: Experience and Opportunities.” IEEE International Conference on eScience, October 2022.
  • Jayson Boubin, Zichen Zhang, John Chumley, Christopher Stewart. “Adaptive Deployment for Autonomous Agricultural UAV Swarms.” ACM Agsys, November 2022 (SenSys workshop).
  • Anituddha Rakshit, Jayson Boubin. “Poster Abstract: Automatic Deployment Right-Sizing Through Hyperparameter Optimization.” ACM/IEEE International Conference on Internet of Things Design and Implementation (IoTDI), May 2023.
  • Wenna Duan, Parshant Sehrawat, Tony D Zhou, James T Becker, Oscar L Lopez, H Michael Gach, Weiying Dai. “Pattern of Altered Magnetization Transfer Rate in Alzheimer’s Disease.” J Alzheimers Dis. August 2022; 88(2): 693–705.
  • Vera Novak, Christos S Mantzoros, Peter Novak, Regina McGlinchey, Weiying Dai, Vasileios Lioutas, Stephanie Buss, Catherine B Fortier, Faizan Khan, Laura Aponte Becerra, Long H Ngo. “MemAID: Memory advancement with intranasal insulin vs. placebo in type 2 diabetes and control participants: a randomized clinical trial”. Journal of Neurology, September 2022; 269, 4817–4835.
  • Luis Hernandez‐Garcia, Verónica Aramendía‐Vidaurreta, Divya S Bolar, Weiying Dai, Maria A Fernández‐Seara, Jia Guo, Ananth J Madhuranthakam, Henk Mutsaerts, Jan Petr, Qin, Jonas Schollenberger, Yuriko Suzuki, Manuel Taso, David L Thomas, Matthias JP Van Osch, Joseph Woods, Moss Y Zhao, Lirong Yan, Ze Wang, Li Zhao, Thomas W Okell. “Recent technical developments in ASL: a review of the state of the art.” Magnetic Resonance in Medicine, November 2022; 88(5), 2021–2042.
  • Shichun Chen, Yakun Zhang, Zongpai Zhang, Tony D Zhou, Wenna Duan, George Weinschenk, Wen-Ming Luh, Adam K Anderson, Weiying Dai. “Global Functional Connectivity at Rest Is Associated with Attention: An Arterial Spin Labeling Study.” Brain Sciences, January 2023; 13(2): 228.
  • Anshul Gandhi, Kanad Ghose, Kartik Gopalan, Syed Rafiul Hussain, Dongyoon Lee, Yu David Liu, Zhenhua Liu, Patrick McDaniel, Shuai Mu, Erez Zadok. “Metrics for Sustainability in Data Centers”. Proceedings of the 1st Workshop on Sustainable Computer Systems Design and Implementation (HotCarbon'22), La Jolla, California, July 2022.
  • Kolesar, John C., Ruzica Piskac, and William T. Hallahan. “Checking equivalence in a non-strict language.” Proceedings of the ACM on Programming Languages 6.OOPSLA2, October 2022: 1469-1496.
  • Y. Liu, K. D. Kang, M. J. Doe. “HADD: High-Accuracy Detection of Depressed Mood,” MDPI Technologies, 10(6), 123, October 2022.
  • Y. Liu, K. D. Kang. “Preprocessing via Deep Learning for Enhancing Real-Time Performance of Object Detection.” IEEE 97th Vehicular Technology Conference, Florence, Italy, June 2023.
  • Daniel Townley, Kerem Arikan, Yu David Liu, Dmitry Ponomarev, Oguz Ergin. “Composable Cachelets: Protecting Enclaves from Cache Side-Channel Attacks,” USENIX Security, August 2022.
  • Philip Dexter, Yu David Liu, Kenneth Chiu. “The Essence of Online Data Processing,” OOPSLA, December 2022.
  • Manish Munikar, Jiaxin Lei, Hui Lu and Jia Rao. “PRISM: Streamlined Packet Processing for Containers with Flow Prioritization.” In Proc. of 42nd IEEE International Conference on Distributed Computing Systems (ICDCS' 22), Bologna, Italy, July 2022.
  • Jiaxin Lei, Manish Munikar, Hui Lu and Jia Rao. “mFlow: Accelerating Packet Processing in Container Overlay Networks via Packet-level Parallelism.” In Proc. of 37th IEEE International Parallel & Distributed Processing Symposium (IPDPS' 23), St. Petersburg, Florida, May 2023.
  • Zhijia Chen, Weiyi Meng, and Eduard Dragut. “Web Record Extraction with Invariants.” Proc. of the VLDB Endowment (VLDB), 16(4):959-972, December 2022.
  • Satadisha Saha Bhowmick, Eduard Dragut, and Weiyi Meng. “Globally Aware Contextual Embeddings for Named Entity Recognition in Social Media Streams.” Proc. of the 39th IEEE International Conference on Data Engineering (ICDE), April 2023.
  • Ulugbek Ergashev, Eduard Dragut, and Weiyi Meng. Learning to Rank Resources with GNN. Proc. of 2023 ACM Web Conference (WWW), pp.3247-3256, April 2023.
  • Jingyao Zhang, Hoda Naghibijouybari, and Elaheh Sadredini. “Sealer: In-SRAM AES for High-Performance and Low-Overhead Memory Encryption.” In Proceedings of the ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED '22). New York, NY, USA, Article 14, 1–6, August 2022.
  • Sankha Baran Dutta, Hoda Naghibijouybari, Arjun Gupta, Nael Abu-Ghazaleh, Andres Marquez, and Kevin Barker. “Spy in the GPU-box: Covert and Side Channel Attacks on Multi-GPU Systems.” In Proceedings of the 50th Annual International Symposium on Computer Architecture (ISCA '23). New York, NY, USA, Article 45, 1–13, June 2023.
  • Matthew Cole and Aravind Prakash. “SIMPLEX: Repurposing Intel Memory Protection Extensions for Secure Storage.” In the proceedings of the 27th Nordic Conference on Secure IT Systems (NORDSEC'22), Reykjavik, Iceland, December 2022.
  • David Demicco, Matthew Cole, Shengdun Wang and Aravind Prakash. “A Security Analysis of Labeling-Based Control-Flow Integrity Schemes.” In the proceedings of the Workshop on Data Fabric for Hybrid Clouds, collocated with IEEE HiPC (WDFHC'22), Bengaluru, India, December 2022.
  • Ravi Theja Gollapudi, Gokturk Yuksek, David B Demicco, Matthew Cole, Gaurav N Kothari, Rohit H Kulkarni, Xin Zhang, Kanad Ghose, Aravind Prakash and Zerksis Umrigar. “Control Flow and Pointer Integrity Enforcement in a Secure Tagged Architecture.” In the proceedings of the 44th IEEE Symposium on Security and Privacy (S&P'23), San Francisco, USA, May 2023.
  • Taehun Kim, Hyeongjin Park, Seokmin Lee, Seunghee Shin, Junbeom Hur, Youngjoo Shin. “DEVIOUS: Device-Driven Side-Channel Attacks on the IOMMU.” May 2023.
  • Guo, X., Sikdar, S., Xia, L., Cao, Y., & Wang, H. Favoring Eagerness for Remaining Items: Designing Efficient, Fair, and Strategyproof Mechanisms. Journal of Artificial Intelligence Research, 76, 287-339, January 2023.
  • Wang, H., Sikdar, S., Guo, X., Xia, L., Cao, Y., & Wang, H. “Multi resource allocation with partial preferences”. Artificial Intelligence, 314, 103824, January 2023.
  • Hadi Hosseini, Sujoy Sikdar, Rohit Vaish, and Lirong Xia. “Fairly Dividing Mixtures of Goods and Chores under Lexicographic Preferences”. In Proceedings of the 22nd International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS-23), May 2023.
  • Wen, Z., Pacherkar, H. S., & Yan, G. “VET5G: A Virtual End-to-End Testbed for 5G Network Security Experimentation.” In Proceedings of the 15th Workshop on Cyber Security Experimentation and Test, pp.19-29, August 2022.
  • Zhihua Li, Alexander Nagrebetsky, Syvia Ranjeva, Nan Bi, Dianbo Liu, Marcos F. Vidal Melo, Lijun Yin, and Hao Deng. “A Transformer-based Deep Learning Algorithm to Auto-record Undocumented Clinical One-lung Ventilation Events.” AAAI 7th International Workshop on Health Intelligence (W3PHIAI-23) in conjunction with the 37th AAAI Conference on Artificial Intelligence (AAAI’23), February 2023.
  • Zhihua Li and Lijun Yin. “Multimodal Facial Action Unit Detection with Physiological Signal,” IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), June 2023.
  • Kishan Chandan, Jack Albertson, and Shiqi Zhang. “Learning Visualization Policies of Augmented Reality for Human-Robot Collaboration.” The Conference on Robot Learning (CoRL), December 2022.
  • Yan Cao, Keting Lu, David DeFazio, and Shiqi Zhang. “Goal-oriented Vision-and-Dialog Navigation through Reinforcement Learning.” The Conference on Empirical Methods in Natural Language Processing (EMNLP Findings), Short Paper, December 2022.
  • Xiaohan Zhang, Saeid Amiri, Jivko Sinapov, Jesse Thomason, Peter Stone, and Shiqi Zhang. “Multimodal Embodied Attribute Learning by Robots for Object-Centric Action Policies.” Autonomous Robots Journal (AURO), March 2023.
  • Mohammad Shokrolah Shirazi, Brendan Tran Morris, and Shiqi Zhang. “Intersection Analysis Using Computer Vision Techniques with SUMO.” Intelligent Transportation Infrastructure (ITI), May 2023.
  • Keting Lu, Yan Cao, Xiaoping Chen, and Shiqi Zhang. “Efficient Dialog Policy Learning with Hindsight, User Modeling, and Adaptation.” IEEE Transactions on Cognitive and Developmental Systems (TCDS), June 2023.
  • Yingxue Zhang, Yanhua Li, Xun Zhou, Xiangnan Kong, and Jun Luo. “STrans-GAN: Spatially-Transferable Generative Adversarial Networks for Urban Traffic Estimation.” IEEE International Conference on Data Mining, Orlando, FL, November 2022.
  • Yingxue Zhang, Yanhua Li, Xun Zhou, Ziming Zhang, and Jun Luo. “STM-GAIL: Spatial-Temporal Meta-GAIL for Learning Diverse Human Driving Strategies.” SIAM International Conference on Data Mining (SDM23), Minneapolis, April 2023.
  • Zhong Ji, Xuejie Yu, Yanwei Pang, and Zhongfei Zhang. “Semantic-Guided Class-Imbalance Learning Model for Zero-Shot Image Classification.” IEEE Transactions on Cybernetics, Volume 52, Issue 7, Pages 6543-6554, IEEE Press, July 2022.
  • Xiang Deng and Zhongfei Zhang. “Deep Causal Metric Learning.” Proc. the 39th International Conference on Machine Learning, (ICML 2022), Baltimore, MD, USA, July 2022.
  • Yunlong Yu, Dingyi Zhang, Yingming Li, and Zhongfei Zhang. “Multi-Proxy Learning from an Entropy Optimization Perspective.” Proc. International Joint Conference on Artificial Intelligence, (IJCAI 2022), Vienna, Austria, July 2022.
  • Yunlong Yu, Dingyi Zhang, Sidi Wang, Zhong Ji, and Zhongfei Zhang. “Local Spatial Alignment network for Few-Shot Learning.” Neurocomputing, Issue 497, Pages 182-190, Elsevier, August 2022.
  • Qiang Wang, Jiayi Liu, Zhong Ji, Yanwei Pang, and Zhongfei Zhang. “Hierarchical Correlations Replay for Continual Learning.” Knowledge-Based Systems, Issue 250, Elsevier, August 2022.
  • Zhong Ji, Ping An, Xiyao Liu, Yanwei Pang, Ling Shao, and Zhongfei Zhang. “Task-Oriented High-Order Context Graph Networks for Few-Shot Human-Object Interaction Recognition.” IEEE Transactions on Systems, Man, and Cybernetics, Volume 52, Issue 9, Pages 5443 - 5455, IEEE Press, September 2022.
  • Hangyu Zhang, Yingming Li, and Zhongfei Zhang. “Video-Grounded Dialogues with Joint Video and Image Training.” Proc. the 29th International Conference on Image Processing, (ICIP 2022), Bordeaux, France, October 2022.
  • Xiang Deng, Jean Zheng, and Zhongfei Zhang. “Personalized Education: Blind Knowledge Distillation.” Proc. the European Conference on Computer Vision, (ECCV 2022), Tel Aviv, Israel, October 2022.
  • Yaodong Wang, Zhong Ji, Kevin Chen, Yanwei Pang, and Zhongfei Zhang. “COREN: Multi-Modal Co-Occurrence Transformer Reasoning Network for Image-Text Retrieval.” Neural Processing Letters, Springer, December 2022.
  • Zhankun Xiong, Shichao Liu, Feng Huang, Ziyan Wang, Xuan Liu, Zhongfei Zhang, and Wen Zhang. “Multi-relational Contrastive Learning Graph Neural Network for Drug-drug Interaction Event Prediction.” Proc. the 37th AAAI Conference on Artificial Intelligence, (AAAI 2023), Washington DC, USA, February 2023.
  • Jurgen Dix and Zhongfei Zhang. “AI's 10 to Watch 2022.” IEEE Intelligent Systems, Volume 38, Number 2, Pages 5-16, IEEE Computer Society Press, March/April 2023.
  • Shichao Liu, Yang Zhang, Yuxin Cui, Yang Qiu, Yifan Deng, Zhongfei Zhang, and Wen Zhang. “Enhancing Drug-Drug Interaction Prediction Using Deep Attention Neural Networks.” IEEE/ACM Transactions on Computational Biology and Bioinformatics, Volume 20, Number 2, Pages 976-985, March/April 2023.
  • Zhong Ji, Jin Li, Qiang Wang, and Zhongfei Zhang. “Complementary Calibration: Boosting General Continual Learning With Collaborative Distillation and Self-Supervision.” IEEE Transactions on Image Processing, Volume 32, Pages 657-667, IEEE Press, May 2023.
• 2021-22
  • Saeed, Mohammad Hammas, Shiza Ali, Jeremy Blackburn, Emiliano De Cristofaro, Savvas Zannettou, and Gianluca Stringhini. "TROLLMAGNIFIER: Detecting state-sponsored troll accounts on reddit." 43rd IEEE Symposium on Security and Privacy (Oakland '22), May 2022.
  • Horta Ribeiro, Manoel, Shagun Jhaver, Savvas Zannettou, Jeremy Blackburn, Gianluca Stringhini, Emiliano De Cristofaro, and Robert West. "Do platform migrations compromise content moderation? evidence from r/the_donald and r/incels." Proceedings of the ACM on Human-Computer Interaction 5, no. CSCW2 (2021): 1-24, October 2021.
  • Doerfler, Periwinkle, Andrea Forte, Emiliano De Cristofaro, Gianluca Stringhini, Jeremy Blackburn, and Damon McCoy. ""I'm a Professor, which isn't usually a dangerous job": Internet-facilitated Harassment and Its Impact on Researchers." Proceedings of the ACM on Human-Computer Interaction 5, no. CSCW2 (2021): 1-32, October 2021.
  • Papadamou, Kostantinos, Savvas Zannettou, Jeremy Blackburn, Emiliano De Cristofaro, Gianluca Stringhini, and Michael Sirivianos. ""How over is it?" Understanding the Incel Community on YouTube." Proceedings of the ACM on Human-Computer Interaction 5, no. CSCW2 (2021): 1-25, October 2021.
  • Ling, Chen, Ihab AbuHilal, Jeremy Blackburn, Emiliano De Cristofaro, Savvas Zannettou, and Gianluca Stringhini. "Dissecting the meme magic: Understanding indicators of virality in image memes." Proceedings of the ACM on Human-Computer Interaction 5, no. CSCW1 (2021): 1-24, October 2021.
  • Wang, Yuping, Savvas Zannettou, Jeremy Blackburn, Barry Bradlyn, Emiliano De Cristofaro, and Gianluca Stringhini. "A multi-platform analysis of political news discussion and sharing on web communities." In 2021 IEEE International Conference on Big Data (Big Data), pp. 1481-1492, December 2021.
  • Shehtab Zaman, Maurcio Araya, Denis Akhiyarov, Kenneth Chiu. “MoleculeFlow: A Deep Generative Workflow for 3D Molecular Generation”. ELLIS Machine Learning for Molecule Discovery Workshop, December 2021.
  • K. D. Kang, “A Review of Efficient Real-Time Decision Making in the Internet of Things”, MDPI Technologies, 10(1):12, January 2022.
  • Steinberg, G., Baur, J., Nikulin, A., Chiu, K., & de Smet, T. S. “How to Implement Drones and Machine Learning to Reduce Time, Costs, and Dangers Associated with Landmine Detection”, Journal of Conventional Weapons Destruction, September 2021, 25(1), Article 29.
  • Shehtab Zaman, Tim Moon, Tom Benson, Sam Adé Jacobs, Kenneth Chiu, Brian Van Essen. “Parallelizing Graph Neural Networks via Matrix Compaction for Edge-Conditioned Networks”. CCGRID 2022: 386-395, May 2022.
  • Huanyi Qin, Zongpai Zhang, Bo Yan, Madhusudhan Govindaraju, Kenneth Chiu. “QSketch: GPU-Aware Probabilistic Sketch Data Structures”. CCGRID 2022: 706-715, May 2022.
  • Nikolas Burzynski, Yuhao Yuan, Adiel Felsen, David Reitano, Zhibo Wang, Khalid A. Sethi, Fake Lu, Kenneth Chiu. “Deep Learning Techniques for Unmixing of Hyperspectral Stimulated Raman Scattering Images”. IEEE BigData 2021: 5862-5864 (Poster), December 2021.
  • Adiel Felsen, Yuhao Yuan, Nikolas Burzynski, David Reitano, Zhibo Wang, Khalid A. Sethi, Fake Lu, Kenneth Chiu. “Cell Nuclei and Lipid Droplets Quantification in Stimulated Raman Images”. IEEE BigData 2021: 5888-5890 (Poster), December 2021.
  • Ethan Ferguson, Shehtab Zaman, Mauricio Araya, Denis Akhiyarov Kenneth Chiu. “ParticleGrid: A Library for 3D Molecular Representation for Deep Learning”. APS March Meeting 2022, March 2022.
  • Ali Eker, David Timmerman, Barry Williams, Kenneth Chiu, Dmitry Ponomarev. “GVT-Guided Demand-Driven Scheduling in Parallel Discrete Event Simulation. ICPP 2021: 22:1-22:10, 2021.
  • W Dai, SA Wagh, S Chettiar, GD Zhou, R Roy, X Qiao, PS Visich, EP Hoffman. “Blunted circadian cortisol in children is associated with poor cardiovascular health and may reflect circadian misalignment”. Psychoneuroendocrinology 2021:129:105252, July 2021.
  • Z Zhang, W Luh, W Duan, TD Zhou, L Zhao, G Weinschenk, AK Anderson, W Dai. “The Longitudinal Effect of Meditation on Resting-State Functional Connectivity Using Dynamic Arterial Spin Labeling: A Feasibility Study”. Brain Sciences 2021:11(10):1263, September 2021.
  • Rickard Brannvall, Gokturk Yuksek and Kanad Ghose, "Data Center Load Balancing Under Homomorphic Encryption." in Proc. The 9th Swedish Workshop on Data Science, December, 2021.
  • Ghazal Mohsenian, Sadegh Khalili, Mohammad Tradat, Yaman Manaserh, Srikanth Rangarajan, Anuroop Desu, Dushyant Thakur, Kourosh Nemati, Kanad Ghose, Bahgat Sammakia, "A novel integrated fuzzy control system toward automated local airflow management in data centers."  Journal of Control Engineering Practice, Vol. 112, July 2021.
  • Anuroop Desu, Udaya Puvvadi, Tyler Stachecki, Sagar Vishwakarma, Sadegh Khalili, Kanad Ghose, Bahgat G. Sammakia, "Latency-Aware Dynamic Server and Cooling Capacity Provisioner for Data Centers." Proceedings ACM Symposium on Cloud Computing (SoCC 2021), November 2021, pages 335-349.
  • Sandeep S. Mittal, Jack Rothberg, Kanad Ghose, "Deep Learning for Morphological Arrhythmia Classification in Encoded ECG Signal." In Proc. 20-th IEEE International Conference on Machine Learning and Applications (ICMLA 2021), December 2021, Pages: 575-581.
  • K. D. Kang, “A Review of Efficient Real-Time Decision Making in the Internet of Things”, MDPI Technologies, 10(1):12, January 2022.
  • Adam Czerniejewski, John Henry Burns, Farshad Ghanei, Karthik Dantu, Yu David Liu, Lukasz Ziarek, "JCopter: Reliable UAV Software through Managed Languages," International Conference on Intelligent Robots and Systems (IROS), September 2021.
  • Sofiya Semenova, Steven Y. Ko, Yu David Liu, Lukas Ziarek, Karthik Dantu, “A Quantitative Analysis of System Bottlenecks in Visual SLAM”, HotMobile, March 2022.
  • Timur Babakol, Anthony Canino, Yu David Liu, “Eflect: Porting Energy-Aware Applications to Shared Environments”, International Conference on Software Engineering (ICSE), May 2022.
  • Kenan Liu, Khaled Mahmoud, Joonhwan Yoo, Yu David Liu, “Vincent: Green Hot Methods in the JVM”, European Conference on Object-Oriented Programming (ECOOP), May 2022.
  • Lin, Zhen, Kao-Feng Hsieh, Yu Sun, Seunghee Shin, and Hui Lu. "FlashCube: Fast Provisioning of Serverless Functions with Streamlined Container Runtimes." In Proceedings of the 11th Workshop on Programming Languages and Operating Systems, pp. 38-45, October 2021.
  • M. Khasawneh and P. H. Madden. “What's So Hard About (Mixed-Size) Placement?”, ISPD 2022, March 2022.
  • S. Ozdemir, M. Khasawneh, S. Rao, and P. H. Madden. “Kernel Mapping Techniques for Deep Learning Neural Network Accelerators”.  ISPD 2022, March 2022.
  • Satadisha Saha Bhowmick, Eduard Dragut, Weiyi Meng. “Boosting Entity Mention Detection for Targetted Twitter Streams with Global Contextual Embeddings”. Proceedings of IEEE International Conference on Data Engineering (ICDE), May 2022.
  • Satadisha Saha Bhowmick, Eduard Dragut, Weiyi Meng. “TwiCS: Twitter Stream Entity Mention Detection”. Proceedings of IEEE International Conference on Data Engineering (ICDE), poster paper, May 2022.
  • Liang Zhu, Xinfeng Li, Yonggang Wei, Qin Ma, Weiyi Meng. “Integrating Real-Time Entity Resolution with Top-N Join Query Processing”, 14th International Conference Knowledge Science, Engineering and Management (KSEM), Tokyo, Japan, August 2021,
  • Sarp Ozdemir, Rutvik Saptarshi, Aravind Prakash and Dmitry Ponomarev. “Track Conventions, Not Attack Signatures: Fortifying X86 ABI and System Call Interfaces to Mitigate Code Reuse Attacks.” In the International Symposium on Secure and Private Execution Environment Design, 2021 (SEED'21), September 2021.
  • David Demicco, Rukayat Erinfolami and Aravind Prakash. “Program Hardening via ABI Debiasing.” In the proceedings of the 37th Annual Computer Security Applications Conference (ACSAC'21), December 2021.
  • Swaroop Gowdra Shanthakumar, Anand Seetharam, Arti Ramesh, “Understanding the Societal Disruption due to COVID-19 via User Tweets”, IEEE SMARTCOMP, August 2021.
  • Q. Pei and S. Shin, "Improving the Heavy Re-encryption Overhead of Split Counter Mode Encryption for NVM," 2021 IEEE 39th International Conference on Computer Design (ICCD), October 2021, pp. 425-432.
  • Sikdar, S., Ruan, S., Han, Q., Pitimanaaree, P., Blackthorne, J., Yener, B., & Xia, L. “Anti-Malware Sandbox Games”. In Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, pp.1201-1209, May 2022.
  • Guo, X., Sikdar, S., Wang, H., Xia, L., Cao, Y., & Wang, H. “Designing Efficient and Fair Mechanisms for Multi-Type Resource Allocation”. In Proceedings of the 21st International Conference on Autonomous Agents and Multiagent Systems, pp.1938-1940, May 2022.
  • J. Dinal Herath, Priti Prabhakar Wakodikar, Ping Yang, and Guanhua Yan. “CFGExplainer: Explaining Graph Neural Network-Based Malware Classification from Control Flow Graphs”. Proceedings of the 52nd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN'22), Baltimore, Maryland, USA, June 2022.
  • Zhan Shu and Guanhua Yan. “IoTInfer: Automated Blackbox Fuzz Testing of IoT Network Protocols Guided by Finite State Machine Inference”. IEEE Internet of Things Journal (IOTJ'22). June 2022.
  • Zhihua Li, Xiang Deng, Xiaotian Li, and Lijun Yin. “Integrating semantic and temporal relationships in facial action units learning”, ACM Multimedia 2021 (long paper), October 2021.
  • Ambareesh Revanur, Zhihua Li, Umur A. Cifti, Lijun Yin, László A. Jeni. "The First Vision for Vitals (V4V) Challenge for Non-Contact Video-Based Physiological Estimation." In Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, October 2021.
  • Xiang Zhang and Lijun Yin, “Multi-Modal Learning for AU Detection Based on Multi-Head Fused Transformers”,16thIEEE International Conference on Automatic Face and Gesture Recognition (FG), December 2021.
  • Xiaotian Li, Zhihua Li, Huiyuan Yang, Geran Zhao, and Lijun Yin, “Your “Attention” Deserves Attention: A Self-Diversified Multi-Channel Attention for Facial Action Analysis”, 16thIEEE International Conference on Automatic Face and Gesture Recognition (FG), December 2021.
  • Yohei Hayamizu, Saeid Amiri, Kishan Chandan, Keiki Takadama, and Shiqi Zhang, “Guiding Robot Exploration in Reinforcement Learning via Automated Planning”, International Conference on Automated Planning and Scheduling (ICAPS), Guangzhou, China, August 2021
  • Kishan Chandan, Jack Albertson, and Shiqi Zhang, “Learning Visualization Policies of Augmented Reality for Human-Robot Collaboration”, International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2022 (Short Paper)
  • Xiaohan Zhang, Yifeng Zhu, Yan Ding, Yuke Zhu, Peter Stone, and Shiqi Zhang, “Visually Grounded Task and Motion Planning for Mobile Manipulation”, IEEE International Conference on Robotics and Automation (ICRA), Philadelphia, PA, May 2022
  • Saeid Amiri, Kishan Chandan, and Shiqi Zhang, “Reasoning with Scene Graphs for Robot Planning under Partial Observability”, IEEE International Conference on Robotics and Automation (ICRA), Published in IEEE Robotics and Automation Letters (RA-L), Philadelphia, PA, May 2022
  • Yan Ding, Xiaohan Zhang, Xingyue Zhan, and Shiqi Zhang, “Learning to Ground Objects for Robot Task and Motion Planning”, IEEE International Conference on Robotics and Automation (ICRA), Published in IEEE Robotics and Automation Letters (RA-L), Philadelphia, PA, May 2022
  • Haodi Zhang, Zhichao Zeng, Keting Lu, Kaishun Wu, and Shiqi Zhang, “Efficient Dialog Policy Learning by Reasoning with Contextual Knowledge”, the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI), Vancouver, BC, Canada, Feb 2022
  • Kishan Chandan, Jack Albertson, Xiaohan Zhang, Xiaoyang Zhang, Yao Liu, and Shiqi Zhang, “Learning to Guide Human Attention on Mobile Telepresence Robots with 360 Vision”. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Sept 2021
  • Hao Yang, Tavan Eftekhar, Chad Esselink, Yan Ding, and Shiqi Zhang, “Task and Situation Structures for Case-based Planning”. International Conference on Case-Based Reasoning (ICCBR), Salamanca, Spain, September 2021
  • Xiaohan Zhang, Jivko Sinapov, and Shiqi Zhang, “Planning Multimodal Exploratory Actions for Online Robot Attribute Learning”. The Robotics: Science and System Conference (RSS), July 2021.
  • Pengzhan Hao and Yifan Zhang. “EDDL: A Distributed Deep Learning System for Resource-limited Edge Computing Environment”. The Sixth ACM/IEEE Symposium on Edge Computing (SEC), December 2021.
  • Yunlong Yu, Dingyi Zhang, Sidi Wang, Zhong Ji, and Zhongfei Zhang. “Local Spatial Alignment network for Few-Shot Learning”, Neurocomputing, Issue 497, Pages 182-190, Elsevier, May 2022.
  • Yifan Deng, Yang Qiu, Xinran Xu, Shichao Liu, Zhongfei Zhang, Shanfeng Zhu, and Wen Zhang, “META-DDIE: Predicting Drug-Drug Interaction Events with Few-Shot Learning”, Briefings in Bioinformatics, Volume 23, Issue 1, January 2022.
  • Di Zhou, Weigang Chen, Chunsheng Guo, and Zhongfei Zhang, “Batch quadratic programming network with maximum entropy constraint for anomaly detection”, ITE Computer Vision, DOI: 10.1049/cvi2.12082, October 2021.
  • Yaqing Zhang, Xi Li, and Zhongfei Zhang, “Efficient Person Search via Expert-Guided Knowledge Distillation”, IEEE Transactions on Cybernetics, Volume 51, Number 10, Pages 5093-5104, Oct. 2021.
  • Zhong Ji, Jiayi Liu, Qiang Wang, and Zhongfei Zhang, “Coordinating Experience Replay: A Harmonious Experience Retention Approach for Continual Learning”, Knowledge-Based Systems, Volume 234, DOI: https://doi.org/10.1016/j.knosys.2021.107589, Elsevier, December 2021.
  • Xiang Deng and Zhongfei Zhang, “Graph-Free Knowledge Distillation for Graph Neural Networks”, Proc. 30th International Joint Conference on Artificial Intelligence (IJCAI 2021), July 2021.
  • Yunlong Yu, Bin Li, Zhong Ji, Jungong Han, and Zhongfei Zhang, “Knowledge Distillation Classifier Generation Network for Zero-Shot Learning”, IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2021.3112229, September 2021.
  • Baiyun Cui, Yingming Li, and Zhongfei Zhang, “Joint Structured Pruning and Dense Knowledge Distillation for Efficient Transformer Model Compression”, Neurocomputing, Volume 458, Pages 56-69, Oct. 2021.
  • Qiang Wang, Jiayi Liu, Zhong Ji, Yanwei Pang, and Zhongfei Zhang, “Hierarchical Correlations Replay for Continual Learning”, Knowledge-Based Systems, Issue 250, DOI: https://doi.org/10.1016/j.knosys.2022.109052, Elsevier, May 2022.
  • Xiang Deng and Zhongfei Zhang, “Sparsity-control ternary weight networks”, Neural Networks, Volume 145, Pages 221-232, January 2022.
  • Xiang Deng and Zhongfei Zhang, “Reducing Flipping Errors in Deep Neural Networks”, Proc. 36th AAAI Conference on Artificial Intelligence, (AAAI 2022), February 2022.
  • Xiang Deng and Zhongfei Zhang, “Comprehensive Knowledge Distillation with Causal Intervention”, Proc. 35th Conference on Neural Information Processing Systems, (NeurIPS 2021), December 2021.
• 2020-21
  • Erik Rye, Jeremy Blackburn, Robert Beverly. “Reading In-Between the Lines: An Analysis of Dissenter.” 20th ACM Internet Measurement Conference (IMC 2020), October 2020. 
  • Fatemeh Tahmasbi, Leonard Schild, Chen Ling, Jeremy Blackburn, Gianluca Stringhini, Yang Zhang, Savvas Zannettou, “Go eat a bat, Chang! An Early Look on the Emergence of Sinophobic Behavior on Web Communities in the Face of COVID-19.” 30th The Web Conference (WWW 2021), April 2021.
  • Antonis Papasavva, Jeremy Blackburn, Gianluca Stringhini, Savvas Zannettou, Emiliano De Cristofaro,“Is it a Qoincidence? An Exploratory Study of QAnon on Voat.” 30th The Web Conference (WWW 2021), April 2021.
  • Chen Ling, Utkucan Balcı, Jeremy Blackburn, Gianluca Stringhini. “A First Look at Zoombombing.” 42nd IEEE Symposium on Security and Privacy (S&P 2021), May 2021. 
  • Christopher Owen, Shehtab Zaman, Michael Lawler, Kenneth Chiu. "Graph Neural Network for Metal Organic Framework Potential Energy Approximation: Energy Landscape Database and Rigidity." Bulletin of the American Physical Society, March 2021.
  • Zaman, S., Owen, C., Chiu, K. and Lawler, M., “Graph Neural Network for Metal-Organic Framework Potential Energy Approximation”. Bulletin of the American Physical Society, March 2021. 
  • Phillips, K., Zaman, S., Chiu, K. and Lawler, M., “Towards Inverse Design of Metal-Organic Frameworks to Maximize Hydrogen Storage using Deep Learning”. Bulletin of the American Physical Society, 2021.
  • Barkovitch, J., Zhou, M., Zaman, S., Chiu, K., Lawler, M. and Wu, J., “Predicting geometric properties of metal-organic frameworks by fusing 3D and graph convolutional neural networks”. Bulletin of the American Physical Society, 2021.
  • Shehtab Zaman, Christopher Owen, Kenneth Chiu and Michael Lawler. Graph Neural Network for Metal Organic Framework Potential Energy Approximation”. Machine Learning for Molecules Workshop@NeurIPS, 2020.
  • L Zhou, Q Zhang, P Spincemaille, TD Nguyen, J Morgan, Weiying Dai, Y Li, A Gupta, MR Prince, Y Wang. “Quantitative transport mapping (QTM) of the kidney with an approximate microvascular network”. Magnetic resonance in medicine 2021: 85(4): 2247-2262, April 2021.
  • V Zeng, P Lizano, NR Bolo, O Lutz, R Brady Jr, EI Ivleva, Weiying Dai, B Clementz, C Tamminga, G Pearlson, M Keshavan. “Altered cerebral perfusion in bipolar disorder: A pCASL MRI study”. Bipolar Disorders. 2021:23(2):130-140, March 2021.
  • L Zhao, M Taso, Weiying Dai, DZ Press, DC Alsop. “Non-invasive measurement of choroid plexus apparent blood flow with arterial spin labeling”. Fluids and Barriers of the CNS. 2020:17(1): 1-11, December 2020. 
  • X Li, X Zhang, H Yang, W Duan, Weiying Dai, Lijun Yin. “An eeg-based multi-modal emotion database with both posed and authentic facial actions for emotion analysis”. 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020). 2020: 336-343, November 2020. 
  • Sandeep S Mittal, Madina Zabran, Kanad Ghose, James N Turner, “Low-Power Discreetly-Wearable Smart ECG Patch with On-Board Analytics,” in Proc. The 2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA), pp. 1-6, June 2020.
  • Pradyumna Kaushik, Srinidhi Raghavendra, Madhusudhan Govindaraju, Devesh Tiwari, “Exploring the Potential of using Power as a First Class Parameter for Resource Allocation in Apache Mesos Managed Clouds”, in the proceedings of the 13th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2020), December 7th - 10th, 2020. 
  •  Di Mu, Mo Sha, Kyoung-Don Kang, and Hyungdae Yi, “Radio Selection and Data Partitioning for Energy-Efficient Wireless Data Transfer in Real-Time IoT Applications,” Ad Hoc Networks, Special Issue on Algorithms, Systems and Applications for Distributed Sensing, vol. 107, pp. 1-11, October 2020.
  • F. Chai, K. D. Kang, “Adaptive Deep Learning for Soft Real-Time Image Classification”, MDPI Technologies, 9(1):20, February 2021.
    E. Marangoz, KD Kang, Seunghee Shin, “Designing GPU architecture for memory bandwidth reservation”, IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS),(poster), pp. 87-89, doi: 10.1109/ISPASS51385.2021.00024, March 2021.
  • Kishan Chandan, Xiaohan Zhang, Jack Albertson, Xiaoyang Zhang, Yao Liu, Shiqi Zhang, “Guided 360-Degree Visual Perception for Mobile Telepresence Robots”. The RSS-2020 Workshop on Closing the Academia to Real-World Gap in Service Robotics, July 2020.
  • Shuoqian Wang, Xiaoyang Zhang, Mengbai Xiao, Kenneth Chiu, Yao Liu, “SphericRTC: A System for Content-Adaptive Real-Time 360-Degree Video Communication”. Proceedings of the 28th ACM International Conference on Multimedia (ACM MM 2020) (Full Research Paper), Seattle, WA, USA, October, 2020.
  • Chao Zhou, Shuoqian Wang, Mengbai Xiao, Sheng Wei, Yao Liu, “AdaP-360: User-Adaptive Area-of-Focus Projections for Bandwidth-Efficient 360-Degree Video Streaming”. Proceedings of the 28th ACM International Conference on Multimedia (ACM MM 2020) (Full Research Paper), Seattle, WA, USA, October 12–16, 2020.
  • Chao Zhou, Shuoqian Wang, Mengbai Xiao, Sheng Wei, Yao Liu, “AdaP-360: User-Adaptive Area-of-Focus Projections for Bandwidth-Efficient 360-Degree Video Streaming”. Proceedings of the 28th ACM International Conference on Multimedia (ACM MM 2020) (Full Research Paper), Seattle, WA, USA, October 12–16, 2020.
  • Xiaoyang Zhang, Harshit Vadodaria, Na Li, Kyoung-Don Kang, Yao Liu, “A Smartphone Thermal Temperature Analysis for Virtual and Augmented Reality” Proceedings of the 3rd International Conference on Artificial Intelligence & Virtual Reality Utrecht, Netherlands, December 14-18, 2020.
  • Timur Babakol, Anthony Canino, Khaled Mahmoud, Rachit Saxena, Yu David Liu, “Calm Energy Accounting for Multithreaded Java Applications,” Proceedings of the ACM Conference on Foundations of Software Engineering (FSE 2020), November 2020.
  • Xiaozhou Liang, John Henry Burns, Joseph Sanchez, Karthik Dantu, Lukasz Ziarek, Yu David Liu, “Understanding Bounding Functions in Safety-Critical UAV Software,” Proceedings of the International Conference on Software Engineering (ICSE’21), May 2021.
  • John Henry Burns, Xiaozhou Liang, Yu David Liu, “Adaptive Variables for Declarative UAV Planning,” Proceedings of the International Workshop on Context-Oriented Programming (COP’20), July 2020.
  •  Jiaxin Lei*, Manish Munikar*, Kun Suo*, Hui Lu, Jia Rao (*equal contribution), “Parallelizing Packet Processing in Container Overlay Networks” In Proc. of 16th European Conference on Computer Systems (EuroSys’ 21), online, April 2021. (38/191 = 19.9%).
  • Haohang Xu, Jin Li, Hongkai Xiong, Hui Lu, “FedMax: Enabling a Highly-Efficient Federated Learning Framework”, In Proc. IEEE International Conference for Cloud Computing (Cloud’ 20), Beijing, China, October 2020. (53/256 = 20.7%).
  • Sarp Ozdemir, Jennifer Seibert, Mohammad Khasawneh, Patrick H. Madden, “A PostScript Toolkit for Electronic Design”, paper, presentation, October 2020.
  • Bustany, Ismail S. and Jung, Jinwook and Madden, Patrick H. and Viswanathan, Natarajan and Yang, Stephen, “Still Benchmarking After All These Years”, Association for Computing Machinery, March 2021.
  • Liang Wang, Rongrong Li, Weiyi Meng, and Zhiyong Peng. “Resolving Seemingly Conflicting Fact Statements Caused by Missing Terms”. Proc. of the 11th IEEE International Conference on Knowledge Graph (ICKG-2020), Nanjing, China, August 2020.
  • Abdullah Aljebreen, Eduard Dragut, and Weiyi Meng. “Segmentation of Tweets with URLs and its Applications to Sentiment Analysis”. Proc. of the 35th AAAI Conference on Artificial Intelligence (AAAI-21), February 2021. 
  • Hoda Naghibijouybari, A. Neupane, Z. Qian and N. Abu-Ghazaleh, “Beyond the CPU: Side–Channel Attacks on GPUs,” in IEEE Design & Test, vol. 38, no. 3, pp. 15-21, doi: 10.1109/MDAT.2021.3063359, June 2021.
  • Aisha Hasan, Ryan Riley, Dmitry Ponomarev. “Port or Shim: Stress-Testing Application Performance on Intel SGX”, IEEE International Symposium on Workload Characterization (IISWC), October 2020.
  • Ali Eker, Yehia Arafa, Abdel-Hameed Badawy, Nandakishore Santhi, Stephan Eidenbenz, Dmitry Ponomarev, “Load-Aware Dynamic Time Synchronization for Parallel Discrete Event Simulation”, ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS), May 2021.
  • Barry Williams, Ali Eker, Kenneth Chiu, Dmitry Ponomarev, “High-Performance PDES on Manycore Clusters”, ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS), June 2021.
  • Rukayat Erinfolami and Aravind Prakash, “Devil is Virtual: Reversing Virtual Inheritance in C++ Binaries”, Proceedings of the 27th ACM Conference on Computer and Communications Security, 2020 (CCS'20), Orlando, FL, November 2020.
  • Yue Zhang, David Defazio, and Arti Ramesh “RelEx: A Model-Agnostic Relational Model Explainer,” AAAI Conference on AI, Ethics, and Society (AIES), May 2021.
  • Shawn Bailey, Yue Zhang, Arti Ramesh, Jennifer Golbeck, and Lise Getoor. “A Structured and Linguistic Approach to Understanding Recovery and Relapse in AA.” ACM Transactions on the Web (TWEB), January 2021. 
  • Yue Zhang and Arti Ramesh. “Learning Fairness-aware Relational Structures.” European Conference on Artificial Intelligence (ECAI), September 2020. 
  • Yue Zhang and Arti Ramesh. “Struct-MMSB: Mixed Membership Stochastic Blockmodels with Interpretable Structured Priors”, European Conference on Artificial Intelligence (ECAI), September 2020.
  • Raushan Raj, Anand Seetharam, Arti Ramesh, “Ensemble Regression Models for Short-term Prediction of Confirmed COVID-19 Cases”, in Proceedings of the AI for Social Good Workshop, June 2020.
  • Gissella Bejarano, Adita Kulkarni, Xianzhi Luo, Anand Seetharam, Arti Ramesh, “DeepER: A Deep Learning based Emergency Resolution Time Prediction System”, in proceedings of the IEEE International Conference of Cyber, Physical and Social Computing (CPSCom), November 2020.
  • Raushan Raj, Arti Ramesh, Anand Seetharam, David DeFazio, “SWIFT: A Non-Emergency Response Prediction System using Sparse Gaussian Conditional Random Fields,”  Published in Elsevier Pervasive and Mobile Computing, January 2021.
  • Swaroop Gowdra Shanthakumar, Anand Seetharam, Arti Ramesh, “Analyzing Societal Impact of COVID-19: A Study During the Early Days of the Pandemic”, in proceedings of the IEEE International Symposium on Social Computing and Networking (SocialCom), December 2020.
  • Necati Ayan, Nilson L. Damasceno, Sushil Chaskar, Peron R. de Sousa, Arti Ramesh, Anand Seetharam, Antonio. A. de. A. Rocha, “Understanding Human Mobility during COVID-19 using Cellular Network Traffic”, published in the IFIP Networking Conference, (Short Paper), June 2021. 
  • Necati Ayan, Sushil Chaskar, Anand Seetharam, Arti Ramesh, Antonio. A. de. A. Rocha “COVID-19 Case Prediction using Cellular Network Traffic”, published in the IFIP Networking Conference, (Short Paper), June 2021.
  • Adita Kulkarni, Anand Seetharam, “QoE-aware Assignment and Scheduling of Multiple Video Streams in Heterogeneous Cellular Networks”, in proceedings of the IEEE Global Internet Symposium, (held in conjunction with IEEE INFOCOM 2021), May 2021. 
  • Raushan Raj, Adita Kulkarni Anand Seetharam, Arti Ramesh, “Wireless Channel Quality Prediction using Sparse Gaussian Conditional Random Fields”, in proceedings of the IEEE International Consumer Communications and Networking Conference (CCNC), January 2021.
  • Adita Kulkarni, Anand Seetharam, “QoE-aware Video Streaming in Heterogeneous Cellular Networks” in proceedings of the IEEE International Consumer Communications and Networking Conference, (CCNC) (Poster), January 2021.
  • Anand Seetharam, “Understanding the impact of COVID-19 on education and some tips to improve online teaching.” In Proceedings of the ACM SIGCOMM Networking Education Workshop, August 2020.
  • Swaroop Gowdra Shanthakumar, Anand Seetharam, Arti Ramesh, “Understanding the Socio-Economic Disruption in the United States during COVID-19’s Early Days,” in Proceedings of the AI for Social Good Workshop, June 2020.
  • Adita Kulkarni, Anand Seetharam, “On the Design and Analysis of Caching and Routing Algorithms in Information-centric Networks,” in proceedings of the EAI International Conference on Ad Hoc Networks (AdHocNets), November 2020.
  • Junyang Shi, Mo Sha, and Xi Peng, “Adapting Wireless Mesh Network Configuration from Simulation to Reality via Deep Learning based Domain Adaptation”, USENIX Symposium on Networked Systems Design and Implementation (NSDI), April 2021, acceptance ratio: 15.6%.
  • Xia Cheng, Junyang Shi, Mo Sha, and Linke Guo, “Launching Smart Selective Jamming Attacks in WirelessHART Networks”, IEEE International Conference on Computer Communications (INFOCOM), May 2021, acceptance ratio: 19.9%.
  •  Xia Cheng, Junyang Shi, and Mo Sha, “Cracking Channel Hopping Sequences and Graph Routes in Industrial TSCH Networks”, ACM Transactions on Internet Technology (TOIT), Special Issue on Evolution of IoT Networking Architectures,  Vol. 20, Issue 3, pp. 23:1-23:28, September 2020.
  • Junyang Shi and Mo Sha, “Parameter Self-Adaptation for Industrial Wireless Sensor-Actuator Networks”, ACM Transactions on Internet Technology (TOIT), Special Issue on Evolution of IoT Networking Architectures,  Vol. 20, Issue 3, pp. 28:1-28:25, September 2020.
  •  Di Mu, Yitian Chen, Junyang Shi, and Mo Sha, “Runtime Control of LoRa Spreading Factor for Campus Shuttle Monitoring”, IEEE International Conference on Network Protocols (ICNP), October 2020, acceptance ratio: 16.7%.
  • Yu Sun, Jiaxin Lei, Seunghee Shin, and Hui Lu. “Baoverlay: a block-accessible overlay file system for fast and efficient container storage”. In Proceedings of the 11th ACM Symposium on Cloud Computing (SoCC ‘20). Association for Computing Machinery, New York, NY, USA, 90–104. DOI:https://doi.org/10.1145/3419111.3421291, 2020.
  • Pei, Qi and Seunghee Shin. “Efficient Split Counter Mode Encryption for NVM.” 2021 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS): 93-95, March 2021.
  • Sujoy Sikdar, Xiaoxi Guo, Haibin Wang, Lirong Xia, and Yongzhi Cao. “Sequential Mechanisms for Multi-type Resource Allocation”. Proceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems, International Foundation for Autonomous Agents and Multiagent Systems, Richland, SC, pp.1209-1217, May 2021.
  • Li, M., Luo, L., Sikdar, S. et al. “Optimized collusion prevention for online exams during social distancing”. npj Sci. Learn. 6, 5. https://doi.org/10.1038/s41539-020-00083-3, March 2021.
  • Guo, X., Sikdar, S., Wang, H. et al. “Probabilistic serial mechanism for multi-type resource allocation”. Auton Agent Multi-Agent Syst 35, 15. https://doi.org/10.1007/s10458-021-09495-w, April 2021.
  • Hosseini, H., Menon, V., Shah, N., & Sikdar, S. “Necessarily Optimal One-Sided Matchings”. Proceedings of the AAAI Conference on Artificial Intelligence, 35(6), pp.5481-5488, May 2021.
  • Hosseini, H., Sikdar, S., Vaish, R., & Xia, L. “Fair and Efficient Allocations under Lexicographic Preferences”. Proceedings of the AAAI Conference on Artificial Intelligence, 35(6), pp.5472-5480, May 2021.
  • Zongpai Zhang, Wen-Ming Luh, Wenna Duan, Grace D. Zhou, George Weinschenk, Adam K. Anderson, Weiying Dai. “Longitudinal effects of meditation on brain resting-state functional connectivity”. Scientific Reports volume 11, Article number: 11361, 2021.
  •  Fang, Kaiming, and Guanhua Yan. “Paging storm attacks against 4G/LTE networks from regional Android botnets: rationale, practicality, and implications.” In Proceedings of the 13th ACM Conference on Security and Privacy in Wireless and Mobile Networks, pp. 295-305. 2020. (Acceptance ratio: 26.0%), July 2020. 
  •  Fang, Kaiming, and Guanhua Yan. “IoTReplay: Troubleshooting COTS IoT Devices with Record and Replay.” In 2020 IEEE/ACM Symposium on Edge Computing (SEC), pp. 193-205. IEEE, 2020. (Acceptance ratio: 21.9%), November 2020.
  •  Herath, J. Dinal, Ping Yang, and Guanhua Yan. “Real-Time Evasion Attacks against Deep Learning-Based Anomaly Detection from Distributed System Logs.” In Proceedings of the Eleventh ACM Conference on Data and Application Security and Privacy, pp.29-40. April 2021.
  • Jeffrey M. Girard, Jeff Cohn, Lijun Yin, and Louis-Philippe Morency, “Reconsidering the Duchenne Smile: Formalizing and Testing Hypotheses About Eye Constriction, Smile Characteristics, and Positive Emotion, Affective Science”, 2:32-47, Springer (official journal of the Society for Affective Science), January 2021.
  • Huiyuan Yang, Taoyue Wang, and Lijun Yin, “Adaptive Multimodal Fusion for Facial Action Units Recognition”, ACM Multimedia 2020  (long paper), October 2020.
    Zheng Zhang, Taoyue Wang, and Lijun Yin, “Region of Interest Based Graph Convolution: A Heatmap Regression Approach for Action Units Detection,” ACM Multimedia 2020 (long paper), October 2020. 
  • Umur Ciftci, Ilke Demir, and Lijun Yin, “FakeCatcher: Detection of Synthetic Portrait Videos Using Biological Signals”, IEEE Transactions on Pattern Analysis and Machine Intelligence, (17 pages) doi: 10.1109/TPAMI.2020.3009287, July 2020.
  •  Umur Ciftci, Ilke Demir, and Lijun Yin, “How do the Hearts of Deep fakes Beat?  Deep Fake Source Detection via Interpreting Residuals with Biological Signals”, IEEE/IAPR International Joint Conference on Biometrics (IJCB), September 2020. 
  •  Zhihua Li, Zheng Zhang, and Lijun Yin, “SAT-Net: Self-Attention and Temporal Fusion for Facial Action Unit detection”, IEEE/IAPR International Conference on Pattern Recognition (ICPR,) January 2021.
  • Zongpai Zhang, Huiyuan Yang, Lijun Yin, David Alsop, and Weiying Dai, “Image registration of perfusion MRI using deep learning networks”, 2021 International Society for Magnetic Resource in Medicine (ISMRM), May 2021.
  •  Yanchen Guo, Zongpai Zhang, Shichun Chen, Lijun Yin, David Alsop, and Weiying Dai, “Removing structured noises from dynamic arterial spin labeling images”, 2021 International Society for Magnetic Resource in Medicine (ISMRM), May 2021.
  • Huiyuan Yang and Lijun Yin, “RE-Net: A Relation Embedded Deep Model for Action Unit Detection”, 15th Asian Conference on Computer Vision (ACCV), 2020.
  •  FX Xin, XR Tong, Lei Yu, “Agent Trust Boost via Reinforcement Learning DQN”, Journal of Computer Research and Development 6, 1227-1238, October 2020.
  • MS Islam, KN Khasawneh, N. Abu-Ghazaleh, D. Ponomarev, Lei Yu, “Efficient Hardware Malware Detectors that are Resilient to Adversarial Evasion”, IEEE Transactions on Computers, doi: 10.1109/TC.2021.3068873, March 2021.
  • Jun Song, Yueyang Wang, Siliang Tang, Zhigang Chen, Zhongfei Zhang, Tong Zhang, and Fei Wu, “Local-Global Memory Neural Network for Medication Prediction”, IEEE Transactions on Neural Networks and Learning Systems, DOI: 10.1109/TNNLS.2020.2989364, Volume 32, Issue 4, Pages 1723 - 1736, April 2021.
  • Bin Li, Jian Tian, Zhongfei Zhang, Hailin Feng, and Xi Li, “Multitask Non-Autoregressive Model for Human Motion Prediction”, IEEE Transactions on Image Processing}, Volume 30, Number 11, Pages 2562 - 2574, 2020, DOI:10.1109/TIP.2020.3038362, November 2020. 
  •  Zhong Ji, Xuejie Yu, Yunlong Yu, Yanwei Pang, and Zhongfei Zhang, “Improved Prototypical Networks for Few-Shot Learning”, Pattern Recognition Letters, Volume 140, Pages 81 - 87, December 2020.
  • Xiang Deng and Zhongfei Zhang, “Is the Meta-Learning Idea Able to Improve the Generalization of Deep Neural Networks on the Standard Supervised Learning?” Proc. the 25th International Conference on Pattern Recognition, (ICPR 2020), Milan, Italy, January 2021.
  • Tao Jin, Siyu Huang, Ming Chen, Yingming Li, and Zhongfei Zhang, “SBAT: Video Captioning with Sparse Boundary-Aware Transformer”, Proc. the 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence, (IJCAI-PRICAI 2020), Yokohama, Japan, January 2021. (12.8% acceptance rate)
  • Baiyun Cui, Yingming Li, and Zhongfei Zhang, “BERT-Enhanced Relational Sentence Ordering Network”, Proc. the 2020 Conference on Empirical Methods in Natural Language Processing, (EMNLP 2020), November 2020. (22.4% acceptance rate)
  • Zhong Ji, Kevin Chen, Junyue Wang, Yunlong Yu, and Zhongfei Zhang, “Multi-Modal Generative Adversarial Network for Zero-Shot Learning”, Knowledge-Based Systems, Volume 197, DOI: 10.1016/j.knosys.2020.105847, June 2020.
  • Dingyi Zhang, Yingming Li, and Zhongfei Zhang, “Deep Metric Learning with Spherical Embedding”, Proc. the 34th Conference on Neural Information Processing Systems, (NeurIPS 2020), Vancouver, Canada, December 2020. (20% acceptance rate)
  • Xiang Deng and Zhongfei Zhang, “Learning with Retrospection”, Proc. 35th International Conference on Artificial Intelligence, (AAAI 2021), Virtual Conference, February 2021. (18.7% acceptance rate)
  • Tao Jin, Yingming Li, and Zhongfei Zhang, “Dual Low-Rank Multimodal Fusion”, Proc. the 2020 Conference on Empirical Methods in Natural Language Processing, (EMNLP 2020), November 2020. (22.4% acceptance rate)
  •  Yunlong Yu, Zhong Ji, Jungong Han, and Zhongfei Zhang, “Episode-based Prototype Generating Network for Zero-Shot Learning”, Proc. IEEE International Conference on Computer Vision and Pattern Recognition, (CVPR 2020), Virtual Conference, June 2020. (22% acceptance rate)
  •  Yan Ding, Xiaohan Zhang, Xingyue Zhan, and Shiqi Zhang, “Task-Motion Planning for Safe and Efficient Urban Driving”. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Las Vegas, NV, October 2020.
  • Keting Lu, Shiqi Zhang, Peter Stone, and Xiaoping Chen, “Learning and Reasoning for Robot Dialog and Navigation Tasks”. The Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL), Special Session on Situated Dialogue with Virtual Agents and Robots, July 2020.
  • Yan Cao, Keting Lu, Xiaoping Chen, and Shiqi Zhang, “Adaptive Dialog Policy Learning with Hindsight and User Modeling”. The Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL), July 2020.
  • Shih-Yun Lo, Shiqi Zhang, and Peter Stone, “The PETLON Algorithm to Plan Efficiently for Task-Level-Optimal Navigation”. Journal of Artificial Intelligence Research (JAIR), Vol 69, pp.471-500, October 2020.
  • Kishan Chandan, Vidisha Kudalkar, Xiang Li, and Shiqi Zhang, “ARROCH: Augmented Reality for Robots Collaborating with a Human”. IEEE International Conference on Robotics and Automation (ICRA), Xi’an, China, May-June 2021.
• 2019-20
  • Baumgartner, J., Zannettou, S., Squire, M., & Blackburn, J. “The Pushshift Telegram Dataset”. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 14, pp. 840-847), May 2020.
  • Chatzakou, D., Leontiadis, I., Blackburn, J., Cristofaro, E. D., Stringhini, G., Vakali, A., & Kourtellis, N. “Detecting cyberbullying and cyberaggression in social media”. ACM Transactions on the Web (TWEB), 13(3), 1-51, October 2019
  •  Papasavva, A., Zannettou, S., De Cristofaro, E., Stringhini, G., & Blackburn, J. “Raiders of the Lost Kek: 3.5 Years of Augmented 4chan Posts from the Politically Incorrect Board”. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 14, pp. 885-894), May 2020. 
  •  Zannettou, S., Caulfield, T., Bradlyn, B., De Cristofaro, E., Stringhini, G., & Blackburn, J. “Characterizing the Use of Images in State-Sponsored Information Warfare Operations by Russian Trolls on Twitter”. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 14, pp. 774-785), May 2020.
  •  Papadamou, K., Papasavva, A., Zannettou, S., Blackburn, J., Kourtellis, N., Leontiadis, I., Stringhini, G. and Sirivianos, M. “Disturbed YouTube for kids: Characterizing and detecting inappropriate videos targeting young children”. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 14, pp. 522-533), May 2020.
  • Mariconti, E., Suarez-Tangil, G., Blackburn, J., De Cristofaro, E., Kourtellis, N., Leontiadis, I., Serrano, J.L. and Stringhini, G. "You Know What to Do" Proactive Detection of YouTube Videos Targeted by Coordinated Hate Attacks”. Proceedings of the ACM on Human-Computer Interaction, 3(CSCW), pp.1-21, November 2019.
  •  Zannettou, S., Finkelstein, J., Bradlyn, B., & Blackburn, J. “A Quantitative Approach to Understanding Online Antisemitism”. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 14, pp. 786-797), May 2020.
  •  Mittos, A., Zannettou, S., Blackburn, J., & De Cristofaro, E. “And We Will Fight for Our Race!” A Measurement Study of Genetic Testing Conversations on Reddit and 4chan. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 14, pp. 452-463), May 2020.
  • Philip Dexter, Bedri Sendir, Kenneth Chiu. “Detecting and Reacting to Anomalies in Relaxed Uses of Raft”. 20th IEEE/ACM International Symposium on Cluster, Cloud and Internet Computing (CCGRID), May 2020.
  •  Jasper Baur, Gabriel Steinberg, Alex Nikulin, Kenneth Chiu, Timothy S. de Smet. “Applying Deep Learning to Automate UAV-Based Detection of Scatterable Landmines”. Remote. Sens. 12(5): 859, March 2020.
  • Ali  Eker, Barry  Williams, Kenneth  Chiu, Dmitry V Ponomarev. “Controlled Asynchronous GVT: Accelerating Parallel Discrete Event Simulation on Many-Core Clusters”. ICPP 2019: Proceedings of the 48th International Conference on Parallel Processing, Kyoto, Japan, August 2019.
  • Angel Beltre, Shehtab Zaman, Kenneth Chiu, Sudhakar Pamidighantam, Xingye Qiao, Madhusudhan Govindaraju. “Towards Run Time Estimation of the Gaussian Chemistry Code for SEAGrid Science Gateway”, Poster paper, 2020. 
  • Weiying Dai, M Chen, W Duan, L Zhao, NR Bolo, C Tamminga, BA Clementz, GD Pearlson, DC Alsop, M Keshavan. ”Abnormal perfusion fluctuation and perfusion connectivity in bipolar disorder measured by dynamic arterial spin labeling”. Bipolar Disorder. 22(4):401-410, June 2020. 
  • S Soman, Weiying Dai, L Dong, E Hitchner, K Lee, BD Baughman, SJ Holdsworth, P Massaband, JV Bhat, ME Moseley, A Rosen, W Zhou, G Zaharchuk. “Identifying cardiovascular risk factors that impact cerebrovascular reactivity: An ASL MRI study”. Journal of Magnetic Resonance Imaging, 51 (3), 734-747, March 2020
  • Yang Gao, Varun V. Soman, Jack P. Lombardi, Pravakar P. Rajbhandari, Tara P. Dhakal, Dale Wilson, Mark Poliks, Kanad Ghose, James N. Turner, Zhanpeng Jin, "Heart Monitor Using Flexible Capacitive ECG Electrodes," in IEEE Transactions on Instrumentation and Measurement. (Early Access) 10.1109/TIM.2019.2949320, October 2019.
  • Varun Soman, Yasser Khan, Madina Zabran, Mark Schadt, Paul Hart, Michael Shay, Frank Egitto, Konstantinos Papathomas, Natasha A. D. Yamamoto, Donggeon Han, Ana C. Arias, Kanad Ghose, Mark D. Poliks, and James N. Turner "Reliability Challenges in Fabrication of Flexible Hybrid Electronics for Human Performance Monitors: A System Level Study," in IEEE Transactions on Components, Packaging and Manufacturing Technology, 9(9), 2019.10.1109/TCPMT.2019.2919866, September 2019.
  • Anuroop Desu, Udaya Puvvadi, Tyler Stachecki, Shane Case and Kanad Ghose. “Hybrid AC/DC Powered Data Centers: A Workload Based Perspective”, in Proc. 17-th IEEE Int’l. Conference on Industrial Informatics, (INDIN 2019), pp.1411-1418, July 2019.
  • Adriano Garcia, Sandeep Mittal, Ed Kiewra and Kanad Ghose, “A Convolutional Neural Network Feature Detection Approach to Autonomous Quadrotor Indoor Navigation”, in Proc. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp.74-81, November 2019. 
  • Udaya Puvaddi, Anuroop Desu, Tyler Stachecki, Kanad Ghose and Bahgat Sammakia, “An Adaptive Approach for Dealing with Flow Disruption in Virtualized Water-Cooled Data Centers”, in Proc. IEEE CLOUD 2019 Conference, pp.296-300, July 2019.
  • Sandeep S Mittal, Madina Zabran, Kanad Ghose, James N Turner.“Low-Power Discreetly-Wearable Smart ECG Patch with On-Board Analytics.”  The 2020 IEEE International Symposium on Medical Measurements and Applications (MeMeA), pp.1-6, June 2020.
  • K. Cheng, S. Doddamani, T. Chiueh, Y. Li, Kartik Gopalan, "Directvisor: Virtualization for Bare-metal Cloud", International Conference on Virtual Execution Environments (VEE), Lausanne, Switzerland, March 2020.
  •  Tianlin Li, Kartik Gopalan, Ping Yang, "ContainerVisor: Customized Control of Container Resources", IEEE International Conference on Cloud Engineering (IC2E), 2019, Prague, Czech Republic, June 2019. 
  • A. Vora, P.-X. Thomas, R. Chen, K. D. Kang, “CSI Classification for 5G Via Deep Learning”. In Proceedings of the IEEE Vehicular Technology Conference, Honolulu, Hawaii, USA, September 2019.
  •  K. D. Kang, “Towards Efficient Real-Time Decision Support at the Edge”, In Proceedings of the ACM/IEEE Workshop on Hot Topics on Web of Things at the 4th ACM/IEEE Symposium on Edge Computing, Washington DC, November 2019.
  • Xi Chen, Minghao Zhao, Xinlei Yang, Zhenhua Li, Yao Liu, Zhenyu Li, Yunhao Liu, “The Cask Effect of Multi-source Content Delivery: Measurement and Mitigation”, Proceedings of the 39th IEEE International Conference on Distributed Computing Systems (IEEE ICDCS 2019), Dallas, TX, July 2019.
  • Nan Jiang, Yao Liu, Tian Guo, Wenyao Xu, Viswanathan Swaminathan, Lisong Xu, Sheng Wei, “QuRate: Power-Efficient Mobile Immersive Video Streaming”. Proceedings of the 11th ACM Multimedia Systems Conference (ACM MMSys 2020), Istanbul, Turkey, June 8-11, 2020.
  • Mengbai Xiao, Shuoqian Wang, Chao Zhou, Li Liu, Zhenhua Li, Yao Liu, Songqing Chen, Lucile Sassatelli, Gwendal Simon Companion Paper for “MiniView Layout for Bandwidth-Efficient 360-Degree Video”, Proceedings of the 27th ACM International Conference on Multimedia (ACM MM 2019) (Reproducibility Paper), Nice, France, October 2019.
  • Yao Liu, Chao Zhou, Shuoqian Wang, Mengbai Xiao, Poster: “FFmpeg360 for 360-Degree Videos: Edge-Based Transcoding, View Rendering, and Visual Quality Comparison”, Proceedings of the 4th ACM/IEEE Symposium on Edge Computing (SEC 2019), Washington DC, November 2019.
  • Xianglong Feng, Yao Liu, Sheng Wei, “LiveDeep: Online Viewport Prediction for Live Virtual Reality Streaming Using Lifelong Deep Learning”, Proceedings of the 2020 IEEE Conference on Virtual Reality and 3D User Interfaces (VR) (IEEE VR 2020), Atlanta, GA, March 2020.
  • John Henry Burns, Xiaozhou Liang, Yu David Liu, “Adaptive Variables for Declarative UAV Planning,” The 12th International Workshop on Context-Oriented Programming, May 2020.
  •  Jeff Eymer, Philip Dexter, Yu David Liu, “Toward Lazy Evaluation in a Graph Database,” International Workshop on Incremental Computing, October 2019.
  • Bo Sang, Pierre-Louis Roman, Patrick Eugster, Hui Lu, Srivatsan Ravi, Gustavo Petri, “PLASMA: Programmable Elasticity for Stateful Cloud Computing Applications.” In Proc. 15th European Conference on Computer Systems, (EuroSys 2020), Heraklion, Greece, online,(43/234 = 18.4%), April 2020. 
  • Gourav Rattihalli, Madhusudhan Govindaraju, Hui Lu, Devesh Tiwari, “Exploring Potential for Non-Disruptive Vertical Auto Scaling and Resource Estimation in Kubernetes.” In Proc. IEEE International Conference for Cloud Computing (Cloud 2019), Milan, Italy, July 2019. 
  • Jiaxin Lei, Kun Suo, Hui Lu, Jia Rao, “Tackling Parallelization Challenges of Kernel Network Stack for Container Overlay Networks”, In Proc. 11th USENIX Workshop on Hot Topics in Cloud Computing (HotCloud 2019), Renton, WA, (22/59 = 37.3%), July 2019.
  • Mohammad Khasawneh and Patrick H. Madden. “Hill Climbing with Trees: Detail Placement for Large Windows”. In Proceedings of the 2020 International Symposium on Physical Design (ISPD ’20). Association for Computing Machinery, New York, NY, USA, pp.9–16. DOI: , March 2020.
  • Joshua Steinberg, David Wynen, Monte McCollum, Patrick H. Madden. “Smartphone Apps for the Arts and Beyond”. 2020 ASEE St. Lawrence Section Annual Conference, April 2020.
    Xiaoyue Tang, Cong Zhang, Weiyi Meng, Kai Wang. “Joint User Mention Behavior Modeling for Mentionee Recommendation”. Applied Intelligence, 50:2449-2464, March 2020.
  • Liang Zhu, Ye Cheng, Yu Wang, Qin Ma and Weiyi Meng. “Evaluating Top-N Join Queries with Real-time Entity Resolution”. 5th Annual International Conference on Information System and Artificial Intelligence (ISAI 2020), Hangzhou, China, May 2020.
  • Daniel Townley and Dmitry Ponomarev, “SMT-COP: Defeating Side-Channel Attacks on Execution Units in SMT Processors”, IEEE/ACM International Conference on Parallel Architectures and Compilation Techniques (PACT), Best Paper Nominee, September 2019.
  • Anh Quach and Aravind Prakash. “Bloat Factors and Binary Specialization.” In CCS workshop on Forming an Ecosystem Around Software Transformation (FEAST'19), London, UK, November 2019.
  • Rukayat Erinfolami and Aravind Prakash. “DeClassifier: Class-Inheritance Inference Engine for Optimized C++ Binaries”. Proceedings of the 14th ACM ASIA Conference on Computer and Communications Security (AsiaCCS'19), Auckland, NZ, July 2019.
  • Rukayat Erinfolami, Anh Quach and Aravind Prakash.”On Design Inference from Binaries Compiled using Modern C++ Defenses”. Proceedings of the 22nd International Symposium on Research in Attacks, Intrusions and Defenses (RAID'19), Beijing, China, September 2019.
  • Yue Zhang and Arti Ramesh. “Learning Interpretable Relational Structures of Hinge-loss Markov Random Fields”. International Joint Conference on Artificial Intelligence (IJCAI), August 2019.
    David DeFazio and Arti Ramesh. “Adversarial Model Extraction of Graph Neural Networks”. AAAI Workshop on Deep Learning on Graphs: Methodologies and Applications (DLGMA), January 2020. 
  • Gissella Bejarano*, Adita Kulkarni*, Raushan Raushan*, Anand Seetharam, Arti Ramesh          (* Joint First Authors). "SWaP - Probabilistic Graphical and Deep Learning Models for Water Consumption Prediction." In Proceedings of ACM Buildsys, September 2019.
  • Adita Kulkarni, Anand Seetharam, “QuickR: A Novel Routing Strategy for Wireless Mobile Information-centric Networks”, in Proceedings of the IEEE International Performance Computing and Communications Conference (IPCCC), 2019.
  • Yasra Chandio, Anand Seetharam, Aditya Mishra. “GridPeaks: Employing Distributed Energy Storage for Grid Peak Reduction”, in Proceedings of the IEEE International Green and Sustainable Computing Conference (IGSC), 2019.
  •  Adita Kulkarni, Anand Seetharam, Arti Ramesh, “DeepFit: Deep Learning based Fitness Center Equipment Use Modeling and Prediction,” in Proceedings of the EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (Mobiquitous), November 2019.
  • Raushan Raj, Anand Seetharam, and Arti Ramesh. “Ensemble Regression Models for Short-term Prediction of Confirmed COVID-19 Cases.” AI for Social Good Workshop, May 2020.
  • Anand Seetharam. “Understanding the impact of COVID-19 on education and some tips to improve online teaching," in Proceedings of the ACM SIGCOMM Networking Education Workshop, May 2020.
  • Adita Kulkarni, Anand Seetharam, Arti Ramesh, J. Dinal Herath, “DeepChannel - Wireless Channel Quality Prediction using Deep Learning”, in IEEE Transactions on Vehicular Technology, Volume 69, Issue 1, February 2020.
  •  Swaroop Gowdra Shanthakumar, Anand Seetharam, Arti Ramesh, “Understanding the Socio-Economic Disruption in the United States during COVID-19’s Early Days,” in Proceedings of the AI for Social Good Workshop, May 2020.
  • Xia Cheng, Junyang Shi, and Mo Sha. “Cracking the Graph Routes in WirelessHART Networks”. ACM Asia Conference on Computer and Communications Security (AsiaCCS '19), July 2019 (Poster).
  • Di Mu, Yunpeng Ge, Mo Sha, Steve Paul, Niranjan Ravichandra, and Souma Chowdhury. “Robust Optimal Selection of Radio Type and Transmission Power for Internet of Things”. ACM Transactions on Sensor Networks (TOSN), Vol. 15, Issue 4, pp. 39:1-39:25, July 2019.
  • Junyang Shi, Mo Sha, and Zhicheng Yang. “Distributed Graph Routing and Scheduling for Industrial Wireless Sensor-Actuator Networks”. IEEE/ACM Transactions on Networking (TON), Vol. 27, Issue 4, pp. 1669-1682, August 2019.
  • Junyang Shi, Xingjian Chen, and Mo Sha. “Enabling Direct Messaging from LoRa to ZigBee in the 2.4 GHz Band for Industrial Wireless Networks''. IEEE International Conference on Industrial Internet (ICII'19), acceptance ratio: 23/138 = 16.7%, November 2019.
  •  Junyang Shi, Di Mu, and Mo Sha. “LoRaBee: Cross-Technology Communication from LoRa to ZigBee via Payload Encoding”. IEEE International Conference on Network Protocols (ICNP'19), acceptance ratio: 30/210 = 14.2%, October 2019.
  • Fernando, Dinuni, Siddharth Kulshrestha, J. Dinal Herath, Nitin Mahadik, Yanzhe Ma, Changxin Bai, Ping Yang, Guanhua Yan, and Shiyong Lu. "SciBlock: A Blockchain-Based Tamper-Proof Non-Repudiable Storage for Scientific Workflow Provenance." In 2019 IEEE 5th International Conference on Collaboration and Internet Computing (CIC), pp.81-90. IEEE, December 2019.
  • Herath, J. Dinal, Changxin Bai, Guanhua Yan, Ping Yang, and Shiyong Lu. "RAMP: Real-Time Anomaly Detection in Scientific Workflows." In 2019 IEEE International Conference on Big Data (Big Data), pp. 1367-1374. IEEE, December 2019.
  • Saeid Mofrad, lshtiaq Ahmed, Shiyong Lu, Ping Yang, Heming Cui, Fengwei Zhang, “SecDATAVIEW: A Secure Big Data Workflow Management System for Heterogeneous Computing Environments”. Annual Computer Security Applications Conference (ACSAC), (Acceptance rate: 22.6%, received ACM artifact evaluated functional badge), December 2019.
  • Huiyuan Yang, Taoyue Wang, and Lijun Yin, “Set Operation Aided Network for Action Units Detection”, IEEE International Conference on Automatic Face and Gesture Recognition (FG), May 2020.
  • Kaoning Hu, Lijun Yin, Tianyang Wang, “Temporal Inter-frame Pattern Analysis for Static and Dynamic Hand Gesture Recognition”, IEEE International Conference on Image Processing (ICIP), September 2019.
  • Xiaotian Li, Xiang Zhang, Huiyuan Yang, Wenna Duan, Weiying Dai, and Lijun Yin. “An EEG-Based Multi-Modal Emotion Database with Both Posed and Authentic Facial Actions for Emotion Analysis”, IEEE International Conference on Automatic Face and Gesture Recognition (FG), May 2020.
  • Rohith Krishnan Pillai, Laszlo Attila Jeni, Huiyuan Yang, Zheng Zhang, Lijun Yin, and Jeffrey F Cohn, “2nd 3D face alignment in the wild challenge (3DFAW-Video): dense reconstruction from video”,  The 2nd Workshop and Challenge on 3D Face Alignment in the Wild (3DFAW-Video, in conjunction with IEEE International Conference on Computer Vision (ICCV), October 2019.
  • Ertugrul, J. Cohn, L. Jeni, Z. Zhang,  Lijun Yin, and Q. Ji, “Cross-domain AU Detection:Domains, Learning Approaches, and Measures”,  IEEE Transactions on Biometrics, Behavior, and Identity Science, Vol. 2, No. 2, pp.158-171, April, 2020 (Best of FG’19).
  • Saurabh Hinduja, Shaun Canavan, and Lijun Yin, “Recognizing Perceived Emotions from Facial Expressions”, IEEE International Conference on Automatic Face and Gesture Recognition (FG), May 2020.
  • Umur Ciftci and Lijun Yin, “Heart-rate based face synthesis for pulse estimation”, 14thInternational Symposium on Visual Computing, p540-551, November 2019.
  • Jeff Girard, Gayatri Shandar, Zhun Liu, Jeff Cohn, Lijun Yin, and Louis-Philippe Morency, “Reconsidering the Duchenne Smile: Indicator of Positive Emotion or Artifact of Smile Intensity?” 8thInternational Conference on Affective Computing and Intelligent Interaction (ACII), 2019  (Association for the Advancement of Affective Computing), October 2019.
  • Faxin Qi, Xiangrong Tong, Lei Yu, Yingjie Wang. “Personalized project recommendations: using reinforcement learning”, Journal on Wireless Communications and Networking, 1, 1-17, December 2019.
  • Andrew Cohen, Xingye Qiao, Lei Yu, Elliot Way, Xiangrong Tong. “Diverse Exploration via Conjugate Policies for Policy Gradient Methods”. AAAI 2019: 3404-3411, February 2020.
  • Daniel Townley, Khaled N Khasawneh, Dmitry Ponomarev, Nael Abu-Ghazaleh, Lei Yu. “LATCH: A Locality-Aware Taint CHecker”. Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture, 969-982, October 2019.
  • Saeid Amiri, Sujay Bajracharya, Cihangir Goktolga, Jesse Thomason, and Shiqi Zhang, “Augmenting Knowledge through Statistical, Goal-oriented Human-Robot Dialog”, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, November 2019.
  • Saeid Amiri, Mohammad S. Shirazi, and Shiqi Zhang, “Learning and Reasoning for Robot Sequential Decision Making under Uncertainty”, The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI), New York, New York, USA, (oral, 5.2% acceptance rate), February 2020.
  • Yuqian Jiang, Fangkai Yang, Shiqi Zhang, and Peter Stone, “Task-Motion Planning with Reinforcement Learning for Adaptable Mobile Service Robots”, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Macau, China, November 2019.
  • Lida Zhu, Shichao Liu, Fuxi Zhu, and Zhongfei Zhang, “NEEF: Network Embedding with Edge Features, Proc.”, The 12th International Conference on Knowledge Science, Engineering, and Management (KSEM 2019), Athens, Greece, August 2019.
  • Baiyun Cui, Yingming Li, Ming Chen, and Zhongfei Zhang, “Fine-tune BERT with Sparse Self-Attention Mechanism”, Proc. International Conference on Empirical Methods on Natural Language Processing and the 9th Joint International Conference on Natural Language Processing, (EMNLP-IJCNLP 2019), Hong Kong, China, (23.8% acceptance rate), November 2019.
  • Yingming Li, Ming Yang, and Zhongfei Zhang, “A Survey of Multi-View Representation Learning”, IEEE Transactions on Knowledge and Data Engineering, Volume 31, Number 10, Pages 1863-1883, 2019, DOI: 10.1109/TKDE.2018.2872063, October 2019.
  • Tao Jin, Siyu Huang, Yingming Li, and Zhongfei Zhang, “Low-Rank HOCA: Efficient High-Order Cross-Modal Attention for Video Captioning”, Proc. International Conference on Empirical Methods on Natural Language Processing and the 9th Joint International Conference on Natural Language Processing, (EMNLP-IJCNLP 2019), Hong Kong, China, (23.8% acceptance rate), November 2019.
  • Tao Jin, Siyu Huang, Yingming Li, and Zhongfei Zhang, “Recurrent Convolutional Video Captioning with Global and Local Attention”, Neurocomputing, Volume 370, Number 12, Pages 118-127, December 2019.
  • Siyu Huang, Xi Li, Zhongfei Zhang, Fei Wu, and Junwei Han, “User-Ranking Video Summarization with Multi-Stage Spatio-Temporal Representation”, IEEE Transactions on Image Processing, DOI: 10.1109/TIP.2018.2889265, Volume 28, Number 6, Pages 2654-2664, June 2019.
  • Yunlong Yu, Zhong Ji, Jichang Guo, Zhongfei Zhang, “Zero-Shot Learning via Latent Space Encoding”, IEEE Transactions on Cybernetics, Volume 49, Number 10, Pages 3755-3766, October, 2019, DOI:10.1109/TCYB.2018.2850750, October 2019.
  • Shengkang Yu, Xi Li, Xueyi Zhao, Zhongfei Zhang, and Fei Wu, “A bilinear ranking SVM for knowledge based relation prediction and classification”, IEEE Transactions on Big Data, Volume 5, Number 4, Pages 588-600, IEEE Computer Society Press, DOI: 10.1109/TBDATA.2018.2843766, December 2019.
• 2018-19

  • Muraoka, K., Hanson, P., Frank, E., Jiang, M., Chiu, K. and Hamilton, D. “A data mining approach to evaluate suitability of dissolved oxygen sensor observations for lake metabolism analysis”. Limnol. Oceanogr. Methods, 16: 787-801, October 2018.

  • Ali Eker, Barry Williams, Nitesh Mishra, Dushyant Thakur, Kenneth Chiu, Dmitry Ponomarev, Nael Abu-Ghazaleh, “Performance Implications of Global Virtual Time Algorithms on a Knights Landing Processor”, 22nd IEEE/ACM International Symposium on Distributed Simulation and Real-Time Applications (DS-RT), Madrid, Spain, October 2018.

  • P. Dexter, K. Chiu and B. Sendir, “An Error-Reflective Consistency Model for Distributed Data Stores”, 2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS), Rio de Janeiro, Brazil, May 2019, pp. 728-737.

  • Yuheng Chen, Wenna Duan, Parshant Sehrawat, Vaibhav Chauhan, Freddy J Alfaro, Anna Gavrieli, Xingye Qiao, Vera Novak, Weiying Dai. “Improved perfusion pattern score association with type 2 diabetes severity using machine learning pipeline: Pilot study”. Journal of Magnetic Resonance Imaging. March 2019, 49:834-844.

  • Li Zhao, David C Alsop, John A Detre, Weiying Dai. “Global fluctuations of cerebral blood flow indicate a global brain network independent of systemic factors”. Journal of Cerebral Blood Flow & Metabolism; February 2019:39:302-312.

  • Sadegh Khalili, Ghazal Mohsenian, Anuroop Desu, Kanad Ghose, Bahgat Sammakia, “Airflow Management Using Active Air Dampers in Presence of a Dynamic Workload in Data Centers”, Proc. 35-th. Semi-Therm Symposium, March 2019 (best paper award winner).

  • Mohammad. I. Tradat,  Udaya L.N. Puvvadi, Bahgat G. Sammakia, Kanad Ghose,  Mahmoud Ibrahim, Andrew Calder, Thomas Peddle, Mark Seymour and Husam A. Alissa, "The Impact of Cold Aisle Containment Pressure Relief on IT Availability", in Proc. 17th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm), May 2019.

  • Ravi Theja Gollapudi, Gokturk Yuksek and Kanad Ghose, “Cache-Aware Dynamic Classification and Scheduling for Linux”, in Proc. 22nd. IEEE Symposium on Low-Power and High-Speed Chips and Systems Coolchips (Coolchips 22), April, 2019.

  • Adriano Garcia, Sandeep Mittal, Ed Kiewra and Kanad Ghose, “A Convolutional Neural Network Vision System Approach to Indoor Autonomous Quadrotor Navigation”, in Proc. IEEE 2019 International Conference on Unmanned Aircraft Systems (ICUAS), June 2019.

  • Ozgur Kilic, Spoorti Doddamani, Aprameya Bhat, Hardik Bagdi, Kartik Gopalan, "Overcoming Performance Bottlenecks in Large-VCPU Virtual Machines", In MASCOTS 2018, September 2018, Milwaukee, WI.

  • Dinuni Fernando, Jonathan Turner, Kartik Gopalan, Ping Yang, "Live Migration Ate My VM: Recovering a Virtual Machine After Failure of Post-Copy Live Migration", In INFOCOM 2019, April 2019, Paris, France. 

  • Gourav Rattihalli, Madhusudhan Govindaraju, Devesh Tiwari,"Towards Enabling Dynamic Resource Estimation and Correction for Improving Utilization in an Apache Mesos Cloud Environment", in the 19th IEEE/ACM International Symposium on Cluster and Grid Computing (CCGrid), May 2019.

  • Pankaj Saha, Angel Beltre and Madhusudhan Govindaraju, "Tromino: Demand and DRF Aware Muti-Tenant Queue Manager for Apache Mesos Cluster", in the 11th IEEE/ACM Conference on Utility and Cloud Computing (UCC 2018), December 2018.

  • Bedri Sendir, Madhu Govindaraju, Rei Odaira and H. Peter Hofstee, "CAPI-Flash Accelerated Persistent Read Cache for Apache Cassandra", in the 2018 IEEE International Conference on Cloud Computing (IEEE CLOUD 2018), July 2018.

  •  Pankaj Saha, Angel Beltre, Piotr Uminski and Madhusudhan Govindaraju, "Evaluation of Docker Containers for Scientific Workloads in Cloud", in Practice and Experience in Advanced Research Computing (PEARC), July 2018.

  • Pankaj Saha, Angel Beltre and Madhusudhan Govindaraju, "Exploring the Fairness and Resource Distribution in an Apache Mesos Environment", in the 2018 IEEE International Conference on Cloud Computing (IEEE CLOUD 2018), July 2018.

  • Pradyumna Kaushik, Akash Kothawale, Abhishek Jain, Renan DelValle, and Madhusudhan Govindaraju, "Analysis of Dynamically Switching Energy-Aware Scheduling Policies for Varying Workloads", in the 2018 IEEE International Conference on Cloud Computing (IEEE CLOUD 2018), July 2018.

  • P. Kapoor, A. Vora, K. D. Kang, “Detecting and Mitigating Spoofing Attack against an Automotive Radar”, In Proceedings of the IEEE Vehicular Technology Conference, August 27 - 30, 2018, Chicago, USA.

  • F. Chai, K. D. Kang, A New Power Analysis Attack and a Countermeasure in Embedded Systems, In Proceedings of the IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference, November 8 - 10, 2018, Columbia University, New York, USA.

  • A. Vora, K. D. Kang, "Downlink Scheduling and Resource Allocation for 5G MIMO Multicarrier Systems," In Proceedings of the IEEE 1st 5G World Forum (5GWF '18), July 9 - 11, 2018, Santa Clara, California, USA.

  • A. Vora, K. D. Kang, "Index Modulation with PAPR and Beamforming for 5G MIMO-OFDM," In Proceedings of the IEEE 1st 5G World Forum (5GWF '18), July 9 - 11, 2018, Santa Clara, California, USA.

  • A. Vora, K. D. Kang, “Effective 5G Wireless Downlink Scheduling and Resource Allocation in Cyber-Physical Systems”, MDPI Technologies, 6(4), 105, 2018.

  • Di Mu, Mo Sha, Kyoung-Don Kang, and Hyungdae Yi, “Energy-Efficient Radio Selection and Data Partitioning for Real-Time Data Transfer”, IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS'19), May 2019. (Best Paper Award Nominee)

  •  Xi Chen, Zhenhua Li, Zhenyu Li, Tianyin Xu, Ennan Zhai, Yao Liu, Minghao Zhao, and Yunhao Liu. “POSTER: Minimizing the Cask Effect of Multi-Source Content Delivery”, Proceedings of the 26th International Symposium on Quality of Service (IWQoS), Banff, Alberta, Canada, June 4-6, 2018.

  • Chao Zhou, Zhenhua Li, Joe Osgood, and Yao Liu. “On the Effectiveness of Offset Projections for 360-Degree Video Streaming”, ACM Transactions on Multimedia Computing, Communications, and Applications (ACM TOMM), Volume:14, Issue:3s, August 2018.

  • Mengbai Xiao, Shuoqian Wang, Chao Zhou, Li Liu, Zhenhua Li, Yao Liu, and Songqing Chen.  “MiniView Layout for Bandwidth-Efficient 360-Degree Video”, Proceedings of the 26th ACM International Conference on Multimedia (ACM MM), Seoul, Korea, October 22-26, 2018.

  • Zhenhua Li, Yongfeng Zhang, Yunhao Liu, Tianyin Xu, Ennan Zhai, Yao Liu, Xiaobo Ma, Zhenyu Li. “A Quantitative and Comparative Study of Network-Level Efficiency for Cloud Storage Services”, ACM Transactions on Modeling and Performance Evaluation of Computing Systems (ACM TOMPECS), Volume 4 Issue 1, March 2019.

  • Ao Xiao, Yunhao Liu, Yang Li, Feng Qian, Zhenhua Li, Sen Bai, Yao Liu, Tianyin Xu, Xianlong Xin. “An In-depth Study of Commercial MVNO: Measurement and Optimization”, Proceedings of the 17th ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys), Seoul, Korea, June 17-21, 2019.

  • Anthony Canino and Yu David Liu and Hidehiko Masuhara, "Stochastic Energy Optimization for Mobile GPS Applications,'' In Proceedings of the 26th ACM SIGSOFT Conference on Foundations of Software Engineering (FSE 2018), November 2018.

  •  Anthony Canino and Yu David Liu, "Toward a Language Design for Energy Prediction." In International Workshop on Modern Language Runtimes, Ecosystems, and VMs (MoreVMs'19), April 2019.

  • Yu Sun, Hui Lu, Abhinav Srivastava, Cong Xu, “ShadeNF: A Platform for Online Network Function Verification”, Proceedings of the 9th ACM Symposium on Cloud Computing (SoCC 2018) Poster, Carlsbad, CA, October 2018.

  • Hui Lu, Abhinav Srivastava, Yu Sun, “ShadeNF: Testing Online Network Functions”, In Proc. IEEE International Conference on Cloud Engineering (IC2E 2019), Prague, Czech Republic, June 2019.

  • Spoorti Doddamani, Piush Sinha, Hui Lu, Tsu-Hsiang K Cheng, Hardik H Bagdi, Kartik Gopalan, “Fast and Live Hypervisor Replacement”, Proceedings of the 15th ACM SIGPLAN/SIGOPS international conference on Virtual Execution Environments (VEE'19) , Providence, Rhode Island, April 2019. 

  • Piush Sinha, Spoorti Doddamani, Hui Lu, Kartik Gopalan, “mWarp: Accelerating Intra-Host Live Container Migration via Memory Warping”, Invited Paper, IEEE INFOCOM WorkShops: DCPerf 2019: Big Data and Cloud Performance Workshop, Paris, France, April 2019. 

  •  Khasawneh, Mohammad and Madden, Patrick H. “HydraRoute: A Novel Approach to Circuit Routing”, Proceedings of the 2019 on Great Lakes Symposium on VLSI (GLSVLSI '19), Tysons Corner, VA, USA, May 2019.

  • Weiyi Meng. “Metasearch Engines”. Encyclopedia of Database Systems (2nd ed.), edited by Ling Liu and M. Tamer Ozsu, July 2018.

  • Kai Wang, Weiyi Meng, Jiang Bian, Shijun Li, and Sha Yang. “Spatial Context-aware User Mention Behavior Modeling for Mentionee Recommendation”. Neural Networks, 106:152-167, October 2018.

  • Liang Zhu, Weipeng Lu, Qin Ma, and Weiyi Meng. Region-tree Based Sorted List Indexing for Real-time Entity Resolution in n-Dimensional Data Space. Proc. Of 2018 International Conference on Information Technology and Applications (ITA 2018), Guilin, China, October 2018.

  • Kai Wang, Weiyi Meng, Shijun Li, Sha Yang. “Multi-Modal Mention Topic Model for Mentionee Recommendation”. Neurocomputing, 325:190-199, January 2019.

  • Yongquan Dong, Eduard Dragut, Weiyi Meng. “Normalization of Duplicate Records from Multiple Sources”. IEEE Transactions on Knowledge and Data Engineering, 31(4):769-782, April 2019.

  • Nael Abu-Ghazaleh, Dmitry Ponomarev, Dmitry Evtyushkin, “How the Spectre and Meltdown Hacks Really Worked?”, IEEE Spectrum, March 2019. 

  • Khaled Khasawneh, Esmaeil Koruyekh, Chengyu Song, Dmitry Evtyushkin, Dmitry Ponomarev and Nael Abu-Ghazaleh, “SafeSpec: Banishing the Spectre of a Meltdown with Leakage-Free Speculation”, Design Automation Conference (DAC), Las Vegas, NV, June, 2019.

  • Atsuko Shimizu, Daniel Townley, Mohit Joshi, Dmitry Ponomarev, “EA-pLRU: Enclave-Aware Cache Replacement”, in Workshop on Hardware and Architecture Support for Security and Privacy (HASP), held in conjunction with ISCA 2019, June 2019.

  • Anh Quach, Lok Kwong Yan and Aravind Prakash. “Debloating Software through Piece-Wise Compilation and Loading”, Proceedings of the 27th Annual Usenix Security Symposium (Security'18), Baltimore, Maryland, August 2018.

  •  Yue Zhang and Arti Ramesh, "Fine-grained Analysis of Cyberbullying using Weakly-Supervised Topic Models", Data Science and Advanced Analytics (DSAA), October 2018.

  • Arti Ramesh and Lise Getoor, "Topic Evolution Models for Long-running MOOCs", Web Information Systems Engineering (WISE), November 2018.

  • Gissella Bejarano, David Defazio, Arti Ramesh, "A Deep Latent Generative Model for Energy Disaggregation", AAAI, January 2019.

  • Arti Ramesh, Dan Goldwasser, Bert Huang, Hal Daume III, and Lise Getoor, "Interpretable Engagement Models for MOOCs using Hinge-loss Markov Random Fields", IEEE Transactions on Learning Technologies (TLT), January 2019.

  • Raphael Luciano de Pontes, Aditya Mishra, Anand Seetharam, Arti Ramesh, Mridula Shekhar “GreenPeaks: Employing renewables to effectively cut load in electric grids” in Proceedings of IEEE SMARTCOMP 2018, June 2018.

  • Gissella Bejarano, Mayank Jain, Arti Ramesh, Anand Seetharam, Aditya Mishra “Predictive Analytics for Smart Water Management in Developing Regions ” in Proceedings of IEEE SMARTCOMP Smart Industries Workshop, June 2018.

  • David DeFazio, Arti Ramesh Anand Seetharam, “NYCER: A Non-Emergency Response Predictor for NYC using Sparse Gaussian Conditional Random Fields”, in Proceedings of the EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (Mobiquitous), November 2018.

  •  J. Dinal Herath, Anand Seetharam, Arti Ramesh, “ Deep Learning Model for Wireless Channel Quality Prediction”, in Proceedings of the IEEE International Conference on Communications (ICC), May 2019.

  • J. Dinal Herath, Anand Seetharam, “A Markovian Model for Analyzing Opportunistic Request Routing in Wireless Cache Networks”, in IEEE Transactions on Vehicular Technology, Volume 68, Issue 1, January 2019.

  • Adita Kulkarni, Anand Seetharam, “Exploiting Correlations in Request Streams: A Case for Hybrid Caching in Cache Networks”, in Proceedings of the IEEE International Conference on Local Computer Networks (LCN), October 2018. 

  • Bitan Banerjee∗, Adita Kulkarni∗, Anand Seetharam, “Greedy Caching: An Optimized Content Placement Strategy for Information-centric Networks”, in Elsevier Computer Networks, Volume 140, Pages 78 – 91, July 2018. (∗Joint First Author) 

  • Adita Kulkarni, Anand Seetharam, “Evaluating the Benefits of Caching and Stateless Forwarding in Mobile Information-centric Networks”, in proceedings of the IEEE/ACM International CSymposium on Architectures for Networking and Communications Systems (ANCS), 2018.

  •  Anubhab Banerjee, Bitan Banerjee, Anand Seetharam, Chintha Tellambura, “Content search and routing under custodian unavailability in information-centric networks”, in Elsevier Computer Networks, Volume 141, Pages 92 – 101, August 2018.

  •  Xia Cheng, Junyang Shi, and Mo Sha, “Cracking the Channel Hopping Sequences in IEEE 802.15.4e-Based Industrial TSCH Networks”, ACM/IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI'19), April 2019.

  • Zhicheng Yang, Parth H Pathak, Jianli Pan, Mo Sha, and Prasant Mohapatra, “Sense and Deploy: Blockage-aware Deployment of Reliable 60 GHz mmWave WLANs”, IEEE International Conference on Mobile Ad-hoc and Sensor Systems (MASS'18), October 2018.

  • Xiaonan Zhang, Pei Huang, Linke Guo, and Mo Sha, Incentivizing Relay Participation for Securing IoT Communication,   IEEE International Conference on Computer Communications (INFOCOM'19), April 2019.

  •  Xia Cheng and Mo Sha, POSTER: Cracking the TSCH Channel Hopping in IEEE 802.15.4e, ACM Conference on Computer and Communications Security (CCS'18), October 2018. (Poster).

  •  Junyang Shi, Mo Sha, and Zhicheng Yang, DiGS: Distributed Graph Routing and Scheduling for Industrial Wireless Sensor-Actuator Networks, IEEE International Conference on Distributed Computing Systems (ICDCS'18) research tracks, July 2018.

  • Junyang Shi and Mo Sha, Parameter Self-Configuration and Self-Adaptation in Industrial Wireless Sensor-Actuator Networks, IEEE International Conference on Computer Communications (INFOCOM'19), April 2019.

  • Di Mu, Mo Sha, Kyoung-Don Kang, and Hyungdae Yi, Energy-Efficient Radio Selection and Data Partitioning for Real-Time Data Transfer, IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS'19), May 2019.

  •  Zhicheng Yang, Parth H Pathak, Mo Sha, Tingting Zhu, Junai Gan, Pengfei Hu, and Prasant Mohapatra, On The Feasibility of Estimating Soluble Sugar Content using Millimeter-wave, ACM/IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI'19), April 2019.

  • S. Shin, M. LeBeane, Y. Solihin and A. Basu, "Neighborhood-Aware Address Translation for Irregular GPU Applications," 2018 51st Annual IEEE/ACM International Symposium on Microarchitecture (MICRO), Fukuoka, October 2018, pp. 352-363.

  • Yunus Kucuk, Nikhil Patil, Zhan Shu and Guanhua Yan, “BigBing: Privacy-Preserving Cloud-Based Malware Classification Service,” Proceedings of the 2nd IEEE Symposium on Privacy-Aware Computing (PAC’18), Washington DC, USA, September 2018.

  • Kaiming Fang and Guanhua Yan, “Emulation-Instrumented Fuzz Testing of 4G/LTE Android Mobile Devices Guided by Reinforcement Learning,” Proceedings of the 23rd European Symposium on Research in Computer Security (ESORICS’18). Barcelona, Spain. September 3-7, 2018. (Acceptance ratio: 20%).

  • Zhan Shu and Guanhua Yan, “Ensuring Deception Consistency for FTP Services Hardened against Advanced Persistent Threats,” Proceedings of The 5th ACM Workshop on Moving Target Defense (MTD’18). In conjunction with the 25th ACM Conference on Computer and Communications Security (CCS’18), Toronto, Canada, October 2018.

  • Jiaqi Yan, Guanhua Yan, and Dong Jin. "Classifying malware represented as control flow graphs using deep graph convolutional neural networks." 49th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE, Acceptance rate: 21.4%. June 2019.

  • Tianlin Li, Kartik Gopalan, Ping Yang. “ContainerVisor: Customized Control of Container Resources”, IEEE International Conference on Cloud Engineering (IC2E), May 2019.

  •  Peng Liu, Zheng Zhang, Huiyuan Yang, and Lijun Yin, “Thermal Empowered Multi-Task Network for Facial Action Unit Detection”, IEEE Winter Conf. on Applications of Computer Vision (WACV 2019), Waikoloa Village, Hawaii, January 2019.

  •  Zheng Zhang, Shuangfei Zhai, Lijun Yin, “Identity-based Adversarial Training of Deep CNNs for Facial Action Unit Recognition”, British  Machine Vision Conference (BMVC), Sept 2018, Newcastle, UK.

  • Huiyuan Yang and Lijun Yin, “Learning Temporal Information From A Single Image For AU Detection”, The 14th IEEE International Conference on Automatic Face and Gesture Recognition (FG), May 2019.

  • I. Ertugrul, J. Cohn, L. Jeni, Z. Zhang,  L. Yin, and Q. Ji, “Cross-domain AU Detection: Domains, Learning Approaches, and Measures”, The 14th IEEE International Conference on Automatic Face and Gesture Recognition (FG), May 2019 (Best paper of FG 2019).

  • Michael J. Reale, Benjamin Klinghoffer, Micah Church, Hannah Szmurlo, Lijun Yin, “Facial Action Unit Analysis through 3D Point Cloud Neural Networks”,  The 14th IEEE International Conference on Automatic Face and Gesture Recognition (FG), May 2019.

  •  Shaun Canavan, Marvin Andujar, Lijun Yin, Anton Nijholt, and Elizabeth Schotter, “Ubiquitous Emotion Recognition with Multimodal Mobile Interfaces”,  The 1st workshop on Ubiquitous Emotion Recognition with Multimodal Mobile Interfaces (UERMMI 2018) in conjunction with UbiComp 2018 - ACM Conference on Pervasive and Ubiquitous Computing, Oct 2018.

  • Andrew Cohen, Xingye Qiao, Lei Yu, Elliot Way, and Xiangrong Tong. "Diverse Exploration via Conjugate Policies for Policy Gradient Methods". In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI-19), January 2019.

  • Shih-Yun Lo, Shiqi Zhang, and Peter Stone. “PETLON: Planning Efficiently for Task-Level-Optimal Navigation”. In proceedings of the International Conference on Autonomous Agents and Multiagent Systems (AAMAS), July 2018 [Best Robotics Paper Award]

  • Saeid Amiri, Suhua Wei, Shiqi Zhang, Jivko Sinapov, Jesse Thomason, and Peter Stone. “Multi-modal Predicate Identification using Dynamically Learned Robot Controllers”. In proceedings of the International Joint Conference on Artificial Intelligence (IJCAI), July 2018.

  • Yuqian Jiang, Shiqi Zhang, Piyush Khandelwal, and Peter Stone. “Task Planning in Robotics: an Empirical Comparison of PDDL- and ASP-based Systems”. Frontiers of Information Technology and Electronic Engineering, Special Issue on Intelligent Robots, April 2019.

  • Keting Lu, Shiqi Zhang, and Xiaoping Chen. “Goal-oriented Dialogue Policy Learning from Failures”. In proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI), February 2019.

  • Christopher Amato, Haitham Bou Ammar, Elizabeth Churchill, Erez Karpas, Takashi Kido, Mike Kuniavsky, WF Lawless, Francesca Rossi, Frans A Oliehoek, Stephen Russell, Keiki Takadama, Siddharth Srivastava, Karl Tuyls, Philip Van Allen, K Brent Venable, Peter Vrancx, and Shiqi Zhang, Reports on the 2018 AAAI Spring Symposium Series, AI Magazine, 39(4), pp. 29-35, December 2018.

  • Sridharan M, Gelfond M, Shiqi Zhang, Wyatt J. “REBA: A refinement-based architecture for knowledge representation and reasoning in robotics”. Journal of Artificial Intelligence Research, 65:87-180, June 2019.

  •  Yunlong Yu, Zhong Ji, Xi Li, Jichang Guo, Zhongfei Zhang, Haibin Ling, Fei Wu, “Transductive Zero-Shot Learning with a Self-Training Dictionary Approach”, IEEE Transactions on Cybernetics, Volume 48, Number 10, Pages 2908-2929, October 2018.

  • Zhongang Qi, Tianchun Wang, Guojie Song, Weisong Hu, Xi Li, and Zhongfei Zhang, “Deep Air Learning: Interpolation, Prediction, and Feature Analysis of Fine-Grained Air Quality”, IEEE Transactions on Knowledge and Data Engineering, IEEE Computer Society Press, Volume 30, Number 12, December 2018, Pages 2285-2297.

  • Bin Li, Xi Li, Zhongfei (Mark) Zhang, “Spatio-Temporal Graph Routing for Skeleton-Based Action Recognition”, Proc. 33rd AAAI Conference on Artificial Intelligence, (AAAI 2019), Honolulu, Hawaii, USA, January 2019.

  • Yaqing Zhang, Xi Li, Zhongfei (Mark) Zhang, “Learning a Key-Value Memory Co-Attention Matching Network for Person Re-Identification”, Proc. 33rd AAAI Conference on Artificial Intelligence, (AAAI 2019), Honolulu, Hawaii, USA, January 2019.

  • Siliang Tang, Fei Wu, Yueting Zhuang, Zhongfei (Mark) Zhang, “Cross-relation Cross-bag Attention for Distantly-supervised Relation Extraction”, Proc. 33rd AAAI Conference on Artificial Intelligence, (AAAI 2019), Honolulu, Hawaii, USA, January 2019.

  • Yunlong Yu, Zhong Ji, Yanwei Fu, Jichang Guo, Yanwei Pang, Zhongfei (Mark) Zhang, “Stacked Semantics-Guided Attention Model for Fine-Grained Zero-Shot Learning”, Proc. 32nd Conference on Neural Information Processing Systems, (NIPS 2018), Montreal, Canada, December 2018.

  • Zeshang Zhang, Yingming Li, Zhongfei (Mark) Zhang, “Relative Attribute Learning with Deep Attentive Cross-image Representation”, Proc. 10th Asian Conference on Machine Learning, (ACML 2018), Beijing, China, November 2018.

  • Ming Chen, Yingming Li, Zhongfei (Mark) Zhang, “Two-View Transformer Network for Video Captioning”, Proc. 10th Asian Conference on Machine Learning, (ACML 2018), Beijing, China, November 2018.

  • Baiyun Cui, Yingming Li, Ming Chen, and Zhongfei (Mark) Zhang, “Deep Attentive Sentence Ordering Network”, Proc. International Conference on Empirical Methods on Natural Language Processing, (EMNLP 2018), Brussels, Belgium, November 2018.

  • Siyu Huang, Xi Li, Zhi-Qi Cheng, Zhongfei (Mark) Zhang, and Alexander Hauptmann, “GNAS: A Greedy Neural Architecture Search Method for Multi-Attribute Learning”, Proc. ACM International Conference on Multimedia, (ACM MM 2018), Seoul, Korea, October 2018.

  •   Jiajiong Cao, Yingming Li, and Zhongfei (Mark) Zhang, “CELEB-500K: A Large Training Dataset for Face Recognition”, Proc. IEEE International Conference on Image Processing, (ICIP 2018), Athens, Greece, October 2018.

  • Jiangtao Yin, Lixin Gao, and Zhongfei Zhang, “Scalable Distributed Nonnegative Matrix Factorization with Block-wise Updates”, IEEE Transactions on Knowledge and Data Engineering, IEEE Computer Society Press, December 2018.

  • Xingran Zhou, Siyu Huang, Bin Li, Yingming Li, Jiachen Li, Zhongfei Zhang, “Text Guided Person Image Synthesis, Proc.”, IEEE International Conference on Computer Vision and Pattern Recognition, (CVPR 2019), Long Beach, CA, USA, (25% acceptance rate), June 2019.

• 2017-18
  • M Cavallari, W Dai, CR Guttmann, DS Meier, LH Ngo, TT Hshieh, TG Fong, E Schmitt, DZ Press, TG Travison, ER Marcantonio, RN Jones, SK Inouye, DC Alsop, "Longitudinal diffusion changes following postoperative delirium in older people without dementia", Neurology, 89(10), 1020-1027, August 2017.
  • W Dai, W Duan, FJ Alfaro, A Gavrieli, F Kourtelidis, V Novak, "The resting perfusion pattern associates with functional decline in type 2 diabetes", Neurobiology of aging, 60, 192-201, Feb 2018.
  • Sami Alkharabsheh, Udaya L. N. Puvvadi, Bharath Ramakrishnan, Kanad Ghose and Bahgat Sammakia, "Failure Analysis of Direct Liquid Cooling System in Data Centers", Jrnl. of Electronics Packaging 140(2), 020902, Paper No: EP-17-1094; doi: 10.1115/1.4039137, January 2018.
  • Adriano Garcia and Kanad Ghose, "Autonomous Indoor Navigation of a Stock Quadcopter with Off-Board Control", Proc. IEEE Research and Education on Unmanned Aerial Systems, peer-reviewed workshop (24% acceptance rate), October 2017, pp. 132-137.
  • Bharath Ramakrishnan, Sami Alkharabsheh, Yaser Hadad, Paul R. Chiarot1, Kanad Ghose, Bahgat Sammakia, Vadim Gektin, Wang Chao, "Experimental Investigation of Direct Liquid Cooling of a Two-Die Package", Proc. IEEE 2018 Smi-Therm (May 2018), pp. 42-49.
  • Kartik Gopalan, Rohith Kugve, Hardik Bagdi, Yaohui Hu, Dan Williams, Nilton Bila, "Multi-hypervisor Virtual Machines: Enabling an Ecosystem of Hypervisor-level Services", USENIX Annual Technical Conference (USENIX ATC), July 2017, Santa Clara, CA, USA.
  • Hardik Bagdi, Rohith Kugve, Kartik Gopalan, "HyperFresh: Live Refresh of Hypervisors Using Nested Virtualization", ACM Asia-Pacific Workshop on Systems (APSys), September 2017, Mumbai, India.
  • Gourav Rattihalli, Pankaj Saha, Madhusudhan Govindaraju and Devesh Tiwari, "Two stage cluster for resource optimization with Apache Mesos", in MTAGS17: 10th Workshop on Many-Task Computing on Clouds, Grids, and Supercomputers, to be held in conjunction with Supercomputing 2017, at Denver, Colorado on November 17th, 2017.
  • Renan DelValle, Pradyumna Kaushik, Abhishek Jain, Jessica Hartog, Madhusudhan Govindaraju, "Electron: Towards Efficient Resource Management on Heterogeneous Clusters with Apache Mesos", in proceedings of the IEEE International Conference on Cloud Computing (CLOUD), Applications Track, July 2017.
  • Renan Delvalle, Pradyumna Kaushik, Abhishek Jain, Jessica Hartog, Madhusudhan Govindaraju, "Exploiting Efficiency Opportunities Based on Workloads with Electron on Heterogeneous Clusters", in The 10th IEEE/ACM International Conference on Utility and Cloud Computing (UCC 2017), October 2017.
  • Pankaj Saha, Angel Beltre, Madhusudhan Govindaraju, "Scylla: A Mesos Framework for Container Based MPI Jobs", accepted for publication in MTAGS17: 10th Workshop on Many-Task Computing on Clouds, Grids, and Supercomputers, held in conjunction with Supercomputing 2017, at Denver, Colorado on November 17th, 2017.
  • KD Kang, L Chen, H Yi, B Wang, M Sha, "Real-Time Information Derivation from Big Sensor Data via Edge Computing", Big Data and Cognitive Computing, Special Issue on Cognitive Services Integrating with Big Data, Clouds and IoT, Vol. 1, Issue 5, pp. 1-24, October, 2017.
  • D. Fernando, K. D. Kang, Y. Zhou, "An Adaptive Closed-Loop Approach for Timely Data Services," In Proceedings of the 23rd IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA '17), August 16 - 18, 2017, Hsinchu, Taiwan.
  • K. D. Kang, Enhancing Timeliness and Saving Power in Real-Time Databases, Real-Time Systems, Volume 54, Issue 2, pp. 484-513, April, 2018.
  • Chao Zhou, Zhenhua Li, and Yao Liu. "A Measurement Study of Oculus 360 Degree Video Streaming", Proceedings of the 8th ACM Multimedia Systems Conference (Research Track) (MMSys 2017), Best Student Paper Award, Taipei, Taiwan, June 20-23, 2017.
  • Mengbai Xiao, Chao Zhou, Yao Liu, and Songqing Chen, "OpTile: Toward Optimal Tiling in 360-Degree Video Streaming", Proceedings of the 2017 ACM on Multimedia Conference (MM 2017), Mountain View, CA, October 23-27, 2017.
  • Zhen Lu, Zhenhua Li, Jian Yang, Tianyin Xu, Ennan Zhai, Yao Liu, and Christo Wilson. "Accessing Google Scholar under Extreme Internet Censorship: A Legal Avenue," Proceedings of the 18th ACM/IFIP/USENIX International Middleware Conference (Industrial Track) (Middleware 2017), Las Vegas, NV, December 11-15, 2017.
  • He Xiao, Zhenhua Li, Ennan Zhai, Tianyin Xu, Yang Li, Yunhao Liu, Quanlu Zhang, and Yao Liu. "Towards Web-based Delta Synchronization for Cloud Storage Services," Proceedings of the 16th USENIX Conference on File and Storage Technologies (FAST 2018), Oakland, CA, February 12-15, 2018.
  • Chao Zhou, Mengbai Xiao, and Yao Liu. "ClusTile: Toward Minimizing Bandwidth in 360-Degree Video Streaming", Proceedings of the 2018 IEEE International Conference on Computer Communications (INFOCOM 2018), Honolulu, HI, April 15-19, 2018.
  • Mengbai Xiao, Chao Zhou, Viswanathan Swaminathan, Yao Liu, and Songqing Chen. "BAS-360: Exploring Spatial and Temporal Adaptability in 360-Degree Videos over HTTP/2. Proceedings of the 2018 IEEE International Conference on Computer Communications (INFOCOM 2018), Honolulu, HI, April 15-19, 2018
  • Gustavo Pinto, Anthony Canino, Fernando Castor, Guoqing Xu, Yu David Liu, "Understanding and Overcoming Parallelism Bottenecks in ForkJoin Applications," ACM Conference on Automated Software Engineering (ASE), November 2017.
  • Liang Zhu, Xu Du, Qin Ma, Weiyi Meng, Haibo Liu. "Keyword Search with Real-Time Entity Resolution in Relational Databases". 2018 International Conference on Big Data Management (ICBDM 2018), Macau, China, February 2018.
  • Jesse Elwell, Dmitry Evtyushkin, Nael Abu-Ghazaleh, Dmitry Ponomarev, Ryan Riley, "Hardening Extended Memory Access Control Schemes with Self-Verified Address Spaces", International Conference on Computer-Aided Design (ICCAD), Irvine, CA, November 2017.
  • Khaled Khasawneh, Nael Abu-Ghazaleh, Dmitry Ponomarev, Lei Yu. "RHMD: Evasion-Resilient Hardware Malware Detectors", 50th International Symposium on Microarchitecture (MICRO), Boston, MA, October 2017.
  • Dmitry Evtyushkin, Ryan Riley, Nael Abu-Ghazaleh, Dmitry Ponomarev. "Branch Scope: A New Side-Channel Attack on Directional Branch Predictor", 23rd ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), Williamsburg, VA, March 2018.
  • Anh Quach, Rukayat Erinfolami, David Demicco and Aravind Prakash. "A Multi-OS Cross-Layer Study of Bloating in User Programs, Kernel and Managed Execution Environments", ACM CCS workshop on Forming an Ecosystem Around Software Transformation, 2017 (FEAST'17), Dallas, Texas, November 2017.
  • Anh Quach, Matthew Cole and Aravind Prakash. "Supplementing Modern Software Defenses with Stack-Pointer Sanity", Proceedings of the 33rd Annual Computer Security Applications Conference (ACSAC'17), Orlando, Florida, December 2017.
  • Anand Seetharam and Arti Ramesh, "On the Goodput of Flows in Heterogeneous Mobile Networks", Elsevier Computer Networks Journal, February 2018.
  • Yue Zhang, Arti Ramesh, Jennifer Golbeck, Dhanya Sridhar, and Lise Getoor. "A Structured Approach to Understanding Recovery and Relapse in AA", WWW, April 2018.
  • Arpita Chakraborty, Yue Zhang, and Arti Ramesh, "Understanding Types of Cyberbullying in an Anonymous Messaging Application", WWW Workshop on Cybersafety, April 2018.
  • Raphael Luciano de Pontes, Aditya Mishra, Anand Seetharam, Arti Ramesh, "GreenPeaks - Employing renewables to effectively cut load in electric grids". IEEE SMARTCOMP, June 2018.
  • Gissella Bejarano, Mayank Jain, Arti Ramesh, Anand Seetharam, Aditya Mishra, "Predictive Analytics for Smart Water Management in Developing Regions," IEEE SMARTCOMP Smart Industries Workshop, June 2018.
  • Swapnoneel Roy, Bassam Matloob, Anand Seetharam, A. Rameshbabu, W. C. O 'Dell, W. I. Davis "Biometrics Data Security Techniques for Portable MobileDevices - A Case Study" in Springer INAE Letters, October 2017.
  • Dinal Herath, Anand Seetharam "Analyzing Opportunistic Request Routing in Wireless Cache Networks" in IEEE ICC, May 2018.
  • Bitan Banerjee*, Adita Kulkarni*, Anand Seetharam "Greedy Caching: An Optimized Content Placement Strategy for Information-centric Networks" (* Joint First Authors) in Elsevier Computer Networks, June 2018.
  • Sibendu Paul, Anand Seetharam, Amitava Mukherjee, Mrinal Naskar "Investigating the Impact of Cache Pollution Attacks in Heterogeneous Cellular Networks" in Proceedings of IEEE ICNP, May 2017.
  • Anand Seetharam. "On Caching and Routing in Information-centric Networks," IEEE Communications Magazine, March 2018.
  • Anubhab Banerjee, Bitan Banerjee, Anand Seetharam, Chintha Tellambura "Content search and routing under custodian unavailability in information-centric networks" in Elsevier Computer Networks, 2018.
  • Chengjie Wu, Dolvara Gunatilaka, Mo Sha, and Chenyang Lu, "Real-Time Wireless Routing for Industrial Internet of Things", ACM/IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI'18), April 2018.
  • Tianming Zhao, Jian Liu, Yan Wang, Hongbo Liu, Yingying Chen, "PPG-based Finger-level Gesture Recognition Leveraging Wearables", in Proceedings of IEEE International Conference on Computer Communications (IEEE INFOCOM 2018), Honolulu, HI, USA, April 2018.
  • Chen Wang, Jian Liu, Yingying Chen, Hongbo Liu, Yan Wang, "Towards In-baggage Suspicious Object Detection Using Commodity WiFi", Proceedings of IEEE International Communications and Network Security (CNS 2018), Beijing, China, May/June 2018. (Best Paper Award).
  • Chen Wang, Xiaonan Guo, Yingying Chen, Yan Wang, Bo Liu, Personal PIN Leakage from Wearable Devices, IEEE Transactions on Mobile Computing (IEEE TMC), Volume 17, Issue 3, Pages 646-660, May 2018.
  • Guanhua Yan, Junchen Lu, Zhan Shu, and Yunus Kucuk."ExploitMeter: Combining Fuzzing with Machine Learning for Automated Evaluation of Software Exploitability", Proceedings of the 1st IEEE Symposium on Privacy-Aware Computing Washington DC, USA August 1-3, 2017.
  • W. Li, F. Abtahi, Z. Zhu, Lijun Yin, "EAC-Net: Deep Nets with Enhancing and Cropping for Facial Action Unit Detection", IEEE Transactions on Pattern Analysis and Machine Intelligence, 1(10):1-14, January 2018.
  • Omowunmi A Sadik, Idris Yazgan, Orhan Eroglu, Peng Liu, Sarah T. Olsen, Alecia M. Moser, Hakan Cengiz, Phillip G. Sander, Courage Tsiagbe, Kei Harada, Saeed Bajwa, Christian D. Tvetenstrand, Lijun Yin, and Peter Gerhardstein, "Objective Pain Analysis Using Serum Cyclooxygenase-2 and Inducible Nitric Oxide Synthase in American Patients", Clinica Chimica Acta - International Journal of Clinical Chemistry and Diagnostic laboratory Medicine, 484, May 2018: 278-283 (Elsevier).
  • H. Yang, U. Ciftci, L. Yin, "Facial Expression Recognition by De-expression Residue Learning", IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2018.
  • Huiyuan Yang, Zheng Zhang, and Lijun Yin, "Identity-Adaptive Facial Expression Recognition Through Expression Regeneration Using Conditional Generative Adversarial Networks", 13th IEEE International Conference on Automatic Face and Gesture Recognition (FG), May, 2018.
  • Peng Liu, Idris Yazgan, Sarah T. Olsen, Alecia M. Moser, Umur A. Ciftci, Saeed Bajwa, Christian D. Tvetenstrand, Peter Gerhardstein, Omowunmi A Sadik, and Lijun Yin, Clinical Valid Pain Database with Biomarker and Visual Information for Pain Level Analysis, 13th IEEE International Conference on Automatic Face and Gesture Recognition (FG), May, 2018.
  • Huiyuan Yang and Lijun Yin, "CNN based 3D facial expression recognition using masking and landmark features", 7th International Conference on Affective Computing and Intelligent Interaction (ACII2017), San Antonio, Texas, Oct. 2017 (The Association for the Advancement of Affective Computing (AAAC).
  • Shaun Canavan, Melanie Chen, Song Chen, Robert Valdez, Miles Yaeger, Huiyi Lin, and Lijun Yin, "Combining gaze and demographic feature descriptors for autism classification," IEEE International Conference on Image Processing (ICIP), Beijing, China, Sept. 2017.
  • Shaun Canavan, Walter Keyes, Ryan Mccormick, Julie Kunnumpurath, Tanner Hoelzel, and Lijun Yin, "Hand gesture recognition using a skeleton-based feature representation with a random regression forest", IEEE International Conference on Image Processing (ICIP), Beijing, China, Sept. 2017.
  • Andrew Cohen, Lei Yu, and Robert Wright. "Diverse Exploration for Fast and Reliable Policy Improvement". In Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18), New Orleans, LA, February 2018.
  • Pengzhan Hao, Yongshu Bai, Xin Zhang, and Yifan Zhang. "EdgeCourier: An Edge-hosted Personal Service for Low-bandwidth Document Synchronization in Mobile Cloud Storage Services". The 2nd ACM/IEEE Symposium on Edge Computing (ACM/IEEE SEC). San Jose, CA, USA, 2017.
  • Yongshu Bai, Pengzhan Hao, and Yifan Zhang. "Case for Web Service Bandwidth Reduction on Mobile Devices with Edge-hosted Personal Services." The 37th IEEE International Conference on Computer Communications (IEEE INFOCOM). Honolulu, HI, USA, 2018.
  • Zhong Ji, Yuzhong Xie, Yanwei Pang, Lei Chen, Zhongfei Zhang, "Zero-Shot Learning with Multi-Battery Factor Analysis," Signal Processing, Volume 138, Pages 265-272, September, 2017.
  • Siyu Huang, Xi Li, and Zhongfei Zhang, Fei Wu, Shenghua Gao, Rongrong Ji, and Junwei Han,
  • "Body Structure Aware Deep Crowd Counting," IEEE Transactions on Image Processing, IEEE Computer Society Press, Volume 27, Number 3, Pages 1049 - 1059, March 2018.
  • Yueting Zhuang, Jun Song, Fei Wu, Xi Li, Zhongfei Zhang, and Yong Rui, "Multi-Modal Deep Embedding via Hierarchical Grounded Compositional Semantics," IEEE Transactions on Circuits and Systems for Video Technology, IEEE Signal Processing Society Press, Volume 28, Number 1, pages 76 - 89, January 2018.
  • Jun Song, Jun Xiao, Fei Wu, Hai Shan, Tong Zhang, Zhongfei Zhang, Wenwu Zhu, "Hierarchical Contextual Attention Recurrent Neural Network for Map Query Suggestion," IEEE Transactions on Knowledge and Data Engineering, IEEE Computer Society Press, Volume 29, Number 9, Pages 1888 - 1901, September 2017.
  • Zhouzhou He, Xi Li, Zhongfei Zhang, Fei Wu, Xin Gang, Yaqing Zhang, Ming-Hsuan Yang, Yueting Zhuang, "Data-Dependent Label Distribution Learning for Age Estimation," IEEE Transactions on Image Processing, IEEE Computer Society Press, Volume 26, Issue 8, Pages 3846-3859, August 2017.
  • Te Pi, Xi Li, Zhongfei Zhang, Xueyi Zhao, Meng Wang, Xuelong Li, Philip S. Yu, "Learning Bregman Distance Functions for Structural Learning to Rank," IEEE Transactions on Knowledge and Data Engineering, IEEE Computer Society Press, Volume 29, Issue 9, Pages 1916-1927, September 2017.
  • Yingming Li and Zhongfei (Mark) Zhang, "Learning with Incomplete Labels," Proc. the 32nd AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, February 2018.
  • Chaojie Mao, Yingming Li, Zhongfei (Mark) Zhang, Yaqing Zhang, and Xi Li, "Multi-Channel Pyramid Person Matching Network for Person Re-Identification," Proc. the 32nd AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, February, 2018.
  • Jiajiong Cao, Yingming Li, Xi Li, and Zhongfei (Mark) Zhang, "FR-ANet: A Face Recognition Guided Facial Attribute Classification Network," Proc. the 32nd AAAI Conference on Artificial Intelligence, New Orleans, Louisiana, USA, February 2018.
  • Chaojie Mao, Yingming Li, Zhongfei (Mark) Zhang, Yaqing Zhang, and Xi Li, "Pyramid Person Matching Network for Person Re-Identification," Proc. 9th Asian Conference on Machine Learning, Seoul, Korea, November 2017.
  • Baiyun Cui, Yingming Li, Yaqing Zhang, and Zhongfei (Mark) Zhang, "Text Coherence Analysis Based on Deep Neural Network," Proc. ACM International Conference on Information and Knowledge Management, Singapore City, Singapore, November, 2017.
  • Te Pi, Xi Li, and Zhongfei (Mark) Zhang, "Boosted Zero-Shot Learning with Semantic Correlation Regularization," Proc. International Joint Conference on Artificial Intelligence, Melbourne, Australia, August 2017.
  • Shuangfei Zhai, Hui Wu, Abhishek Kumar, Yu Cheng, Yongxi Lu, Zhongfei Zhang, Rogerio Feris, "S3Pool: Pooling with Stochastic Spatial Sampling," Proc. IEEE International Conference on Computer Vision and Pattern Recognition, Honolulu, Hawaii, USA, July 2017.
• 2016-17
  • W. Dai, T. Fong, R. Jones, E. Marcantonio, E. Schmitt, SK. Inouye, DC. Alsop. "Effects of Arterial Transit Time on Cerebral Blood Flow Quantification Using Arterial Spin Labeling in an Elderly Cohort", Journal of Magnetic Resonance Imaging 45(2):472-481, February 2017.
  • X. Zheng, W. Dai, D. C. Alsop, G. Schlaug. "Modulating transcallosal and intrahemispheric brain connectivity with tDCS: Implications for interventions in Aphasia", Restorative Neurology and Neuroscience 34(4): 519-530, July 2016.
  • L. Zhao, W. Dai, S. Soman, DB. Hackney, ET. Wong, PM. Robson, DC. Alsop. "Using Anatomic Magnetic Resonance Image Information to Enhance Visualization and Interpretation of Functional Images: A Comparison of Methods Applied to Clinical Arterial Spin Labeling Images", IEEE Transactions on Medical Imaging, 36(2): 487-496, 2017.
  • TT. Hshieh, W. Dai, M. Cavallari, CRG. Guttmann, DS. Meier, Eva M Schmitt, Bradford C. Dickerson, Daniel Z. Press, Edward R. Marcantonio, Richard N. Jones, Yun Ray Gou, Thomas G. Travison, Tamara G. Fong, Long Ngo, Sharon K. Inouye, David C. Alsop, SAGES Study Group. "Cerebral blood flow MRI in the nondemented elderly is not predictive of post-operative delirium but is correlated with cognitive performance", Journal of Cerebral Blood Flow & Metabolism, 37(4): 1386-1397, April 2017.
  • Yasser Khan, Mohit Garg, Qiong Gui, Mark Schadt, Abhinav Gaikwad, Donggeon, Han, Natasha A. D. Yamamoto, Paul Hart, Robert Welte, William Wilson, Steve Czarnecki, Mark Poliks, Zhanpeng Jin, Kanad Ghose, Frank Egitto, James Turner, and Ana C. Arias. "Flexible Hybrid Electronics: Direct Interfacing of Soft and Hard Electronics for Wearable Health Monitoring," Journal of Advanced Functional Materials, 26(47):8764-8775, December 2016.
  • Kartik Gopalan and Rohit Kugve and Hardik Bagdi and Yaohui Hu and Daniel Williams and Nilton Bila, "Multi-Hypervisor Virtual Machines: Enabling an Ecosystem of Hypervisor-level Services," USENIX Annual Technical Conference (USENIX ATC'17), 2017, Santa Clara, CA.
  • Dinuni Fernando, Hardik Bagdi, Yaohui Hu, Ping Yang, Kartik Gopalan, Charles Kamhoua, and Kevin Kwiat, Quick Eviction of Virtual Machines Through Proactive Live Snapshots, Full paper, IEEE/ACM International Conference on Utility and Cloud Computing (UCC), 2016.
  • Bedri Sendir, Madhusudhan Govindaraju, Rei Odaira, Peter Hofstee, "Optimized Durable Commitlog for Apache Cassandra Using CAPI-Flash", in proceedings of the IEEE International Conference on Cloud Computing (CLOUD), Research Track, June 2016.
  • Pankaj Saha, Madhusudhan Govindaraju, Suresh Marru, Marlon Pierce, ''Extended Abstract: MultiCloud Resource Management using Apache Mesos for Planned Integration with Apache Airavata'', accepted for presentation and publication at the Science Gateways Workshop, November 2016.
  • K. D. Kang, "Reducing Deadline Misses and Power Consumption in Real-Time Databases", IEEE Real-Time Systems Symposium (RTSS '16), Porto, Portugal, November 2016.
  • Haris Ribic and Yu David Liu, "AEQUITAS: Coordinated Energy Management Across Parallel Applications,'' Proceedings of the International Conference on Supercomputing (ICS 2016), June 2016.
  • Philip Dexter, Yu David Liu and Kenneth Chiu, "Lazy Graph Processing in Haskell,'' Proceedings of the ACM SIGPLAN Haskell Symposium (Haskell 2016), September 2016.
  • Yuheng Long, Yu David Liu and Hridesh Rajan, "First-Class Effect Reflection for Effect-Guided Programming," ACM SIGPLAN Conference on Object-Oriented Programming, Systems, Languages and Applications (OOPSLA 2016), October 2016.
  • Gustavo Pinto, Kenan Liu, Fernando Castor and Yu David Liu, "A Comprehensive Study on the Energy Efficiency of Java Thread-Safe Collections," Proceedings of the International Conference on Software Maintenance and Evolution (ICSME 2016), October 2016.
  • Yu David Liu and Lukasz Ziarek, "Toward Energy-Aware Programming for Unmanned Aerial Vehicles.'' In International Workshop on Software Engineering for Smart Cyber-Physical Systems (SEsCPS 2017), affiliated with ICSE 2017, May 2017.
  • Yao Liu, Mengbai Xiao, Ming Zhang, Xin Li, Mian Dong, Zhan Ma, Zhenhua Li, Lei Guo, and Songqing Chen. "Content-Adaptive Display Power Saving for Internet Video Applications on Mobile Devices", ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM), 12(5), December 2016.
  • Chao Zhou, Zhenhua Li, and Yao Liu. "A Measurement Study of Oculus 360 Degree Video Streaming". Best Student Paper Award, Proceedings of the 8th ACM Multimedia Systems Conference (Research Track) (MMSys 2017), Taipei, Taiwan, June 2017.
  • Yue Zhang, Yao Liu. "Buffer-Based Reinforcement Learning for Adaptive Streaming", Proceedings of the 37th IEEE International Conference on Distributed Computing Systems (ICDCS 2017), June 2017.
  • Jiaqi Li, Weiyi Meng, Hongyan Liu, Shengyun Sun, Jun He, Zhicheng Dou, and Xiaoyong Du. "Mining Time-Sensitive Queries and their Sensitivities from Query Log". 4th CCF Big Data Conference, Lanzhou, China, October 2016.
  • Liang Zhu, Feifei Liu, Weiyi Meng, Qin Ma, Yu Wang, and Fang Yuan. "Evaluating Top-N Queries in n-Dimensional Normed Spaces". Information Sciences, 374:255-275, December 2016.
  • Jing Yuan, Lihong He, Eduard Dragut, Weiyi Meng, Clement Yu. "Result Merging for Structured Queries on the Deep Web with Active Relevance Weight Estimation". Information Systems, 64:93-103, March 2017.
  • Dmitry Evtyushkin, Dmitry Ponomarev, "Covert Channels through Random Number Generators: Mechanisms, Capacity Estimation and Mitigations", 23rd ACM Conference on Computer and Communications Security (CCS), Vienna, Austria, October 2016.
  • Dmitry Evtyushkin, Dmitry Ponomarev, Nael Abu-Ghazaleh, "Jump Over ASLR: Attacking Branch Predictors to Bypass ASLR", 49th International Symposium on Microarchitecture (MICRO), Taipei, Taiwan, October 2016.
  • Mehmet Kayaalp, Khaled Khasawneh, Hodjat Asghari-Esfeden, Jesse Elwell, Nael Abu-Ghazaleh, Dmitry Ponomarev, Aamer Jaleel, "RIC: Relaxed Inclusion Caches for Mitigatikng LLC Side-Channel Attacks", 54th Design Automation Conference (DAC), Austin, TX, June 2017.
  • Meltem Ozsoy, Khaled N. Khasawneh, Caleb Donovick, Iakov Gorelik, Nael B. Abu-Ghazaleh, Dmitry Ponomarev, "Hardware-Based Malware Detection Using Low-Level Architectural Features", IEEE Transactions on Computers, 65(11): 3332-3344, November 2016.
  • Barry Williams, Dmitry Ponomarev, Nael Abu-Ghazaleh, Philip Wilsey, "Performance Characterization of Parallel Discrete Event Simulation on Knights Landing Processor", ACM SIGSIM Conference on Principles of Advanced Discrete Simulation (SIGSIM-PADS), Singapore, May 2017.
  • Xunchao Hu, Aravind Prakash, Jinghan Wang, Rundong Zhou, Yao Cheng, and Heng Yin "Semantics-Preserving Dissection of JavaScript Exploits via Dynamic JS-Binary Analysis". 19th Symposium on Research in Attacks, Intrusions and Defenses (RAID'16), September 2016.
  • Andrew Henderson, Lok Kwong Yan, Xunchao Hu, Aravind Prakash, Heng Yin, and Stephen McCamant. "DECAF: A Platform-Neutral Whole-System Dynamic Binary Analysis Platform," IEEE Transactions on Software Engineering (TSE), February 2017.
  • Mostafa Dehghan, Bo Jiang, Anand Seetharam, Ting He, Theodoros Salonidis, Jim Kurose, Don Towsley, Bo Jiang, Ramesh Sitaraman, "On the Complexity of Optimal Request Routing and Content Caching in Heterogeneous Cache Networks", IEEE/ACM Transactions on Networking, June 2017.
  • Bitan Banerjee, Anand Seetharam, Chintha Tellambura, "Greedy Caching: A Latency-aware Caching Strategy for Information-centric Networks", Proceedings of IFIP Networking 2017, June 2017.
  • Adita Kulkarni, Anand Seetharam. "Impact of Mobility on Performance of Caching Strategies in Information-centric Networks", Proceedings of ACM Mobisys Women Workshop 2017, June 2017.
  • Bitan Banerjee, Anand Seetharam, Amitava Mukherjee, Mrinal Naskar. "Characteristic time Routing in Information-centric Networks", Elsevier Computer Networks, February 2017.
  • Dolvara Gunatilaka, Mo Sha, and Chenyang Lu, "Impacts of Channel Selection on Industrial Wireless Sensor-Actuator Networks", IEEE Conference on Computer Communications (INFOCOM'17), May 2017.
  • Mo Sha, Dolvara Gunatilaka, and Chenyang Lu, "Empirical Study and Enhancements of Industrial Wireless Sensor-Actuator Network Protocols", IEEE Internet of Things Journal, 4(3):696-704, June 2017.
  • Di Mu, Yunpeng Ge, Mo Sha, Steve Paul, Niranjan Ravichandra, and Souma Chowdhury, "Adaptive Radio and Transmission Power Selection for Internet of Things", ACM/IEEE International Symposium on Quality of Service (IWQoS'17), June 2017.
  • Kirby, Ellington, Seoyoon Park, Yan Wang, and Yingying Chen. "HearHere: smartphone based audio localization using time difference of arrival." Proceedings of the 22nd Annual International Conference on Mobile Computing and Networking, pp. 509-510. ACM, 2016.
  • Guanhua Yan, Yunus Kucuk, Max Slocum, and David C. Last. "A Bayesian cognitive approach to quantifying software exploitability based on reachability testing." Proceedings of the 19th Information Security Conference (ISC'16), Hawaii, USA, September 2016.
  • Guanhua Yan. "Improving efficiency of link clustering on multi-core machines." Proceedings of the International Conference on Distributed Computing Systems (ICDCS'17), Atlanta, Georgia, USA, June 2017.
  • Luyang Liu, Hongyu Li, Jian Liu, Cagdas Karatas, Yan Wang, Marco Gruteser, Yingying Chen, Richard Martin, "BigRoad: Scaling Massive Road Data Acquisition for Dependable Self-Driving," Proceedings of the 15th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys 2017), Niagara Falls, NY, USA, June 2017.
  • Jian Liu, Yingying Chen, Marco Gruteser, Yan Wang, "VibSense: Sensing Touches on Ubiquitous Surfaces through Vibration," in Proceedings of the 14th IEEE International Conference on Sensing, Communication, and Networking (SECON 2017), San Diego, CA, USA, June 2017.
  • W. Li, Z. Zhu, F. Abtahi, and L. Yin. "EAC-Net: A Region-based Deep Enhancing and Cropping Approach for Facial Action Unit Detection". 12th IEEE International Conference on Automatic Face and Gesture Recognition (FG), May 2017.
  • M. Valstar, E. Lozano, J. Cohn, L. Jeni, J. Girard, Z. Zhang, L. Yin, and M. Pantic. "FERA 2017 - Addressing Head Pose in the Third Facial Expression Recognition and Analysis Challenge", 12th IEEE International Conference on Automatic Face and Gesture Recognition (FG), May 2017.
  • L. Jeni, S. Tulyakov, L. Yin, N. Sebe, J. F. Cohn. "The First 3D Face Alignment in the Wild (3DFAW) Challenge", European Conference on Computer Vision (ECCV), Amsterdam, Netherlands, Oct. 2016.
  • Yongshu Bai, Xin Zhang, and Yifan Zhang. "Improving Cloud Storage Usage Experience for Mobile Applications", 7th ACM SIGOPS Asia-Pacific Workshop on Systems (ACM APSys), Hong Kong, China, August 2016.
  • Yongshu Bai and Yifan Zhang. "StoArranger: Enabling Efficient Usage of Cloud Storage Services on Mobile Devices", 37th IEEE International Conference On Distributed Systems (IEEE ICDCS), Atlanta, GA, USA, June 2017.
  • Yifan Zhang, Yunxin Liu, Xuanzhen Liu, and Qun Li. "Enabling Accurate and Efficient Modeling-based CPU Power Estimation for Smartphones", IEEE/ACM International Symposium on Quality of Service (IEEE/ACM IWQoS), Vilanova i la Geltru, Spain, June 2017.
  • Pengzhan Hao, Yongshu Bai, Xin Zhang, and Yifan Zhang. "EPS - Edge-hosted Personal Services for Mobile Users", Poster, 15th ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys), Niagara Falls, NY, USA, June 2017.
  • Xin Zhang, Yongshu Bai, Pengzhan Hao, and Yifan Zhang. "Securing Device Inputs for Smartphones Using Hypervisor Based Approach", Poster, 15th ACM International Conference on Mobile Systems, Applications, and Services (ACM MobiSys), Niagara Falls, NY, USA, June 2017.
  • Yaqing Zhang, Xi Li, Liming Zhao, and Zhongfei (Mark) Zhang. "Semantics-aware Deep Correspondence Structure Learning for Robust Person Re-identification", Proc. International Joint Conference on Artificial Intelligence (IJCAI 2016), NYC, NY, USA, July 2016.
  • Te Pi, Xi Li, Zhongfei (Mark) Zhang, Deyu Meng, Fei Wu, Jun Xiao, Yueting Zhuang. "Self-Paced Boost Learning for Classification", Proc. International Joint Conference on Artificial Intelligence (IJCAI 2016), NYC, NY, USA, July 2016.
  • Yingming Li, Ming Yang, Zenglin Xu, and Zhongfei (Mark) Zhang. "Multi-view Learning with Limited and Noisy Tagging", Proc. International Joint Conference on Artificial Intelligence (IJCAI 2016), NYC, NY, USA, July 2016.
  • Shuangfei Zhai, Keng-Hao Chang, Ruofei (Bruce) Zhang, and Zhongfei (Mark) Zhang. "DeepIntent: Learning Attentions for Online Advertising with Recurrent Neural Networks", Proc. ACM International Conference on Knowledge Discovery and Data Mining (ACM KDD 2016), San Francisco, CA, USA, August 2016.
  • Fei Wu, Zhuhao Wang, Zhongfei Zhang, Yi Yang, Jiebo Luo, Wenwu Zhu, and Yueting Zhang. "Weakly Semi-supervised Deep Learning for Multi-label Image Annotation", IEEE Transactions on Big Data, 1(3):109-122, September 2016.
  • Shuangfei Zhai, Yu Cheng, and Zhongfei (Mark) Zhang. "Doubly Convolutional Neural Networks", Proc. Advances in Neural Information Processing Systems (NIPS 2016), Barcelona, Spain, December 2016.
  • Siyu Huang, Xi Li, Zhongfei Zhang, Zhouzhou He, Fei Wu, Jinhui Tang, and Yueting Zhuang. "Deep Learning Driven Visual Path Prediction from a Single Image", IEEE Transactions on Image Processing, 26(12):5892-5904, December 2016.
  • Yueting Zhuang, Jun Song, Fei Wu, Xi Li, Zhongfei Zhang, and Yong Rui. "Multi-Modal Deep Embedding via Hierarchical Grounded Compositional Semantics", IEEE Transactions on Circuits and Systems for Video Technology, December 2016.
  • Xueyi Zhao, Xi Li, Zhongfei Zhang, Chunhua Shen, Yueting Zhang, Lixin Gao, and Xuelong Li. "Scalable Linear Visual Feature Learning Via Online Parallel Nonnegative Matrix Factorization", IEEE Transactions on Neural Networks and Learning Systems, 27(12):2628-2642, December 2016.
  • Peiguang Jing, Zhong Ji, Yunlong Yu, Zhongfei Zhang. "Visual Search Reranking with Relevant Local Discriminant Analysis", Neurocomputing, December 2016.
  • Yingming Li, Ming Yang, and Zhongfei (Mark) Zhang. "Learning with Feature Network and Label Network Simultaneously", Proc. AAAI International Conference on Artificial Intelligence (AAAI 2017), San Francisco, CA, USA, February 2017.
  • Nana Li, Shuangfei Zhai, and Zhongfei (Mark) Zhang. "Structural Correspondence Learning Based on Distributed Representation of Words for Cross-lingual Sentiment Classification", Proc. AAAI International Conference on Artificial Intelligence, AAAI 2017, San Francisco, CA, USA, February 2017.
  • Hanqi Wang, Yueting Zhuang, Jun Xiao, Fei Wu, Yi Yang, Weiming Lu, Zhongfei Zhang. "Bag-of-Discriminative-Words (BoDW) Representation via Topic Modeling", IEEE Transactions on Knowledge and Data Engineering, 29(5):977-990, May 2017.
• 2015-16
  • Haris Ribic and Yu David Liu, “AEQUITAS: Coordinated Energy Management Across Parallel Applications,” In Proceedings of the International Conference on Supercomputing (ICS), June 2016.
  • Mehmet Kayaalp, Nael Abu-Ghazaleh, Dmitry Ponomarev, Aamer Jaleel, "A High-Resolution Side-Channel Attack on Last Level Cache”, 53rd Design Automation Conference (DAC), Austin, TX, June 2016. Best Paper Nominee
  • F. Chai, T. Zhu, K. D. Kang, A Link-Correlation-Aware Cross-Layer Protocol for IoT Devices, IEEE International Conference on Communications (ICC '16), Kuala Lumpur, Malaysia, May 23 - 27, 2016.
  • Chenyang Lu, Abusayeed Saifullah, Bo Li, Mo Sha, Humberto Gonzalez, Dolvara Gunatilaka, Chengjie Wu, Lanshun Nie, and Yixin Chen. “Real-Time Wireless Sensor-Actuator Networks for Industrial Cyber-Physical Systems.” Proceedings of the IEEE, Special Issue on Industrial Cyber Physical Systems, Vol. 104, Issue 5, pp. 1013-1024, May 2016.
  • Qian Feng, Aravind Prakash, Minghua Wang, Curtis Carmony and Heng Yin. “ORIGEN: Automatic Extraction of Offset-Revealing Instructions for Cross-Version Memory Analysis”. In Proceedings of the 11th ACM Asia Conference on Computer and Communications Security (AsiaCCS’16), Xi’an, China, May 2016.
  • U. Deshpande, D. Chan, T-Y. Guh, J. Edouard, K. Gopalan, N. Bila, “Agile Live Migration of Virtual Machines”, In International Conference on Parallel and Distributed Systems (IPDPS), May 2016. (Acceptance Rate: 23%).
  • Chen Wang, Xiaonan Guo, Yan Wang, Yingying Chen, Bo Liu. “Friend or Foe? Your Wearable Devices Reveal Your Personal PIN.” The 11th ACM Symposium on Information, Computer and Communications Security (ASIACCS), May 2016.
  • Chunhua Shen, Xi Li, Anthony R. Dick, Zhongfei Zhang, Yueting Zhang, “Online Metric-Weighted Linear Representations for Robust Visual Tracking”, IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Computer Society Press, Volume 38, Number 5, Pages 931 - 950, May 2016.
  • Nemati, K., Alissa, H.A., Puvvadi, U., Murray, B. T., Sammakia, B., Ghose, K., “Experimental characterization of a Rear Door Heat exchanger with localized containment,” Proc. 15th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm), May 2016, pp.710-719.
  • Alissa, H. A., Nemati, K., U Puvvadi, U., Sammakia, B. G., Ghose, K., Seymour, M. J., Tipton, R., Ken Schneebeli, K., “Empirical analysis of blower cooling failure in containment: Effects on IT performance,” Proc. 15th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems (ITherm), May 2016, pp. 1426-1434.
  • Wensheng Wu, Weiyi Meng, Weifeng Su, Quangyou Zhou, Yao-Yi Chiang. “Q2P: Discovering Query Templates via Autocompletion.” ACM Transactions on the Web (TWEB), 10(2):10, May 2016.
  • Xian Li, Weiyi Meng, Clement Yu. “Verification of Fact Statements with Multiple Truthful Alternatives.” 12th International Conference on Web Information Systems and Technologies (WEBIST), Rome, Italy, April 2016.
  • Shuangfei Zhai, Keng-Hao Chang, Ruofei (Bruce) Zhang, and Zhongfei (Mark) Zhang, “Attention Based Recurrent Neural Networks for Online Advertising”, Proc. ACM International Conference on WWW, Montreal, Quebec, Canada, April, 2016, (25% acceptance rate).
  • Cagdas Karatas, Luyang Liu, Hongyu Li, Jian Liu, Yan Wang, Sheng Tan, Jie Yang, Yingying Chen, Marco Gruteser, Richard Martin. “Leveraging Wearables for Steering and Driver Tracking.” IEEE International Conference on Computer Communications (INFOCOM), April 2016.
  • Chengjie Wu, Dolvara Gunatilaka, Abusayeed Saifullah, Mo Sha, Paras Babu Tiwari, Chenyang Lu, Yixin Chen. “Maximizing Network Lifetime of WirelessHART Networks under Graph Routing.” IEEE International Conference on Internet-of-Things Design and Implementation (IoTDI'16), April 2016 (acceptance ratio: 20.8%).
  • Jeff Bush, Khaled Z. Mahmoud, Mohammad A. Khasawneh, Timothy N. Miller, “NyuziRaster: Optimizing Rasterizer Performance and Energy in the Nyuzi Open Source GPU,” International Symposium on Performance Analysis of Systems and Software (ISPASS), April 2016, Uppsala, Sweden.
  • Dan Williams, Yaohui Hu, Umesh Deshpande, Nilton Bila, Kartik Gopalan, Hani Jamjoom, "Enabling Efficient Hypervisor-as-a-Service Clouds with Ephemeral Virtualization", In International Conference on Virtual Execution Environments (VEE), April 2016.
  • Yao Liu, Mengbai Xiao, Ming Zhang, Xin Li, Mian Dong, Zhan Ma, Zhenhua Li, Songqing Chen. “GoCAD: GPU-Assisted Online Content Adaptive Display Power Saving for Mobile Devices in Internet Streaming”, The 25th International World Wide Web Conference (WWW), April 2016. (Acceptance rate: 16%)
  • Dmitry Evtyushkin, Dmitry Ponomarev, Nael Abu-Ghazaleh. “Understanding and Mitigating Covert Channels through Branch Predictors.” ACM Transactions on Architecture and Code Optimization (ACM TACO), Vol. 13, Issue 1, March 2016.
  • Pankaj Saha, Madhusudhan Govindaraju, Suresh Marru, Marlon E. Pierce: Integrating Apache Airavata with Docker, Marathon, and Mesos. Concurrency and Computation: Practice and Experience 28(7): 1952-1959, March 2016.
  • P.M. Robson, A.J. Madhuranthakam, M.P. Smith, M.R.M. Sun, W. Dai,"Volumetric Arterial Spin-labeled Perfusion Imaging of the Kidneys with a Three-dimensional Fast Spin Echo Acquisition", Academic radiology 23 (2): 144-154, Feb. 2016
  • (Book) J. Nepkie, J. Aini, R. DeCarlo, D. DiRienzo, T. Good, F. Hildebrand, D. Pesta, William Ziegler; Internships and Co-ops: A Guide for Planning, Implementation, and Assessment; State University of New York, May, 2016; http://system.suny.edu/media/suny/content-assets/documents/faculty-senate/Internship-Guide-FINAL-(3.22.16).pdf
  • M. Cavallari, W. Dai, C.R.G. Guttmann, D.S. Meier, L.H. Ngo, T.T. Hshieh, "Neural substrates of vulnerability to postsurgical delirium as revealed by presurgical diffusion MRI", Brain, Feb, 2016.
  • Yingming Li, Ming Yang, and Zhongfei (Mark) Zhang, “Learning with Marginalized Corrupted Features and Labels Together”, Proc. AAAI International Conference on Artificial Intelligence, Phoenix, AZ, USA, February, 2016, (26% acceptance rate).
  • Shuangfei Zhai and Zhongfei (Mark) Zhang, “Semi-supervised Auto encoder for Sentiment Analysis”, Proc. AAAI International Conference on Artificial Intelligence, Phoenix, AZ, USA, February, 2016, (26% acceptance rate).
  • Elif Dede, Bedri Sendir, Pinar Kuzlu, John Richard Weachock, Madhusudhan Govindaraju, Lavanya Ramakrishnan, “Processing Cassandra Datasets with Hadoop-Streaming Based Approaches”, IEEE Transactions on Services Computing (TSC) 9(1):46-58, 2016.
  • Z. Zhang, J. Girard, Y. Wu, X. Zhang, P. Liu, U. Ciftci, S. Canavan, M. Reale, A. Horowitz, H. Yang, J. Cohn, Q. Ji, and L. Yin,  Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2016 (acceptance rate 25%)
  • S. Tulyakov, X. Alameda-Pineda, E. Ricci, L. Yin, N. Sebe, and J. Cohn, Self-Adaptive Matrix Completion for Heart Rate Estimation from Face Videos under Realistic Conditions, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) 2016 (acceptance rate 4% for oral)
  • Y. Zhou, K. D. Kang, "Deadline Assignment and Feedback Control for Differentiated Real-Time Data Services", IEEE Transactions on Knowledge and Data Engineering, Volume 27, Issue 12, pages 3245-3257, December, 2015.
  • Abusayeed Saifullah, Dolvara Gunatilaka, Paras Tiwari, Mo Sha, Chenyang Lu, Bo Li, Chengjie Wu, and Yixin Chen. “Schedulability Analysis under Graph Routing in WirelessHART Networks.” IEEE Real-Time Systems Symposium (RTSS'15), December 2015 (acceptance ratio: 22.5%)
  • Aravind Prakash and Heng Yin. “Defeating ROP Through Denial of Stack Pivot.” Proceedings of Annual Computer Security Applications Conference (ACSAC’15), Los Angeles, CA, December 2015.
  • Jesse Elwell, Ryan Riley, Nael Abu-Ghazaleh, Dmitry Ponomarev, Iliano Cervesato. “Rethinking Memory Permissions for Protection Against Cross-Layer Attacks.” ACM Transactions on Architecture and Code Optimization (ACM TACO), Volume 12, Issue 4, Article No.56, December 2015.
  • U. L. N. Puvvadi, K. Di Benedetto, A. Patil, K. D. Kang, Y. Park, "Cost-Effective Security Support in Real-Time Video Surveillance", IEEE Transactions on Industrial Informatics, Volume 11, Issue 6, pages 1457 - 1465, December, 2015.
  • Jianli Pan, Raj Jain, Subharthi Paul, Tam Vu, Abusayeed Saifulla, Mo Sha. “An Internet of Things Framework for Smart Energy in Buildings: Designs, Prototype, and Experiments.” IEEE Internet of Things Journal, Vol. 2, Issue 6, pp. 527-537, December 2015.
  • Jessica Hartog, Renan Delvalle, Madhusudhan Govindaraju, Michael J. Lewis: Performance Analysis of Adapting a MapReduce Framework to Dynamically Accommodate Heterogeneity. Transactions on Large-Scale Data- and Knowledge-Centered Systems (TLSDKCS) 20:108-130 Dec. 2015.
  • Alissa, H.A., Nemati, K., Sammakia, B. G., Ghose, K., Seymour, M., King, D. and Tipton, R., “Ranking and Optimization of CAC and HAC Leakage Using Pressure Controlled Models,” Proc. ASME 2015 International Mechanical Engineering Congress and Exposition (IMECE), Nov. 2015.
  • Yi Xu, Yilin Zhu, Zhongfei (Mark) Zhang, Yaqing Zhang, Philip S. Yu, “Convex Approximation to the Integral Mixture Models Using Step Functions”, Proc. IEEE International Conference on Data Mining, Atlantic City, NJ, USA, November, 2015, (8.4% acceptance rate).
  • Khaled Khasawneh, Meltem Ozsoy, Caleb Donovick, Nael Abu-Ghazaleh and Dmitry Ponomarev. “Ensemble Learning for Low-level Hardware-Supported Malware Detection.” 18th International Symposium on Research in Attacks, Intrusions and Defenses (RAID), Kyoto, Japan, November 2015, pp.3-25. 
  • W. Dai, G. Varma, R Scheidegger, D.C. Alsop. "Quantifying fluctuations of resting state networks using arterial spin labeling perfusion MRI", Journal of Cerebral Blood Flow & Metabolism 36(3):463-473, Nov. 2015.
  • G. Chen, K. D. Kang, "Win-Fit: Efficient Intersection Management via Dynamic Vehicle Batching and Scheduling," IEEE International Conference on Connected Vehicles and Expo (ICCVE '15), Shenzhen, China, October 19 - 23, 2015.
  • Yi Xu, Zhongfei (Mark) Zhang, Yaqing Zhang, Philip S. Yu, “Sensor Network Partitioning based on Homogeneity”, Proc. IEEE International Conference on Data Science and Analytical Analysis, Paris, France, October, 2015, (22% acceptance rate).
  • Xueyi Zhao, Xi Li, Zhongfei Zhang, “Joint Structural Learning to Rank with Deep Linear Feature Learning”, IEEE Transactions on Knowledge and Data Engineering, Volume 27, Number 10, Pages 2756 - 2769, Oct 2015.
  • Jing Wang, Clement Yu, Philip Yu, Bing Liu, and Weiyi Meng. “Diversionary Comments under Blog Posts.” ACM Transactions on the Web (TWEB), 9(4):18, October 2015.
  • Liang Zhu, Qin Ma, Weiyi Meng, Mingqian Yang, and Fang Yuan. “An Experimental Evaluation of Aggregation Algorithms for Processing Top-K Queries.” 15th IEEE International Conference on Computer and Information Technology (CIT-2015), pp.326-333, Liverpool, England, UK, October 2015.
  • Zhenhua Li, Christo Wilson, Tianyin Xu, Yao Liu, Zhen Lu, and Yinlong Wang. “Offline Downloading in China: A Comparative Study”, The 15th ACM Internet Measurement Conference (IMC), Oct. 2015.
  • Shaun Canavan, Peng Liu, Xing Zhang, and Lijun Yin. “Landmark Localization on 3D/4D Range Data Using a Shape Index-Based Statistical Shape Model with Global and Local Constraints.” Computer Vision and Image Understanding (Special issue on Shape Representations Meet Visual Recognition), Vol. 139, Oct. 2015. P136-148.
  • Ed Novak, Yutao Tang, Zijiang Hao, Qun Li, Yifan Zhang, "Physical Media Covert Channels on Smart Mobile Devices", ACM Ubicomp 2015, Osaka, Japan, Sep. 7-11, 2015.
  • Alkharabsheh, S., Fernandes, J., Gebrehiwot, B., Agonafer, D., Ghose, K., Ortega, A., Joshi, Y., Sammakia, B., “Brief Overview of Recent Developments in Thermal Management in Data Centers,” ASME Journal of Electronic Packaging, Vol. 137, No. 4, Sept. 2015.
  • Xueyi Zhao, Xi Li, and Zhongfei Zhang, “Multimedia Retrieval via Deep Learning to Rank”, Proc. IEEE International Conference on Image Processing, Quebec City, Canada, September, 2015.
  • Zhouzhou He, Zhongfei Zhang, Chunming Chen, and Zhenggang Wang, “E-Commerce Business Model Mining and Prediction,” Frontiers of Information Technology and Electronic Engineering, Springer, Volume 16, Number 9, Pages 707-719, Sept 2015.
  • S. Canavan, L. Yin, P. Liu, and X. Zhang, “Feature Detection and Tracking on Geometric Mesh Data Using a Combined Global and Local Shape Model for Face and Facial Expression Analysis.” International Conference of Biometrics, Theory, Applications and Systems, (BTAS’15), Sept., 2015.
  • Qingyuan Liu, Eduard Dragut, Arjun Mukherjee, and Weiyi Meng. “FLORIN - A System to Support (Near) Real-Time Applications on User Generated Content for Daily News.” International Conference on Very Large Data Bases (VLDB), Demo Paper, pp.1944-1947, Hawaii, September 2015.
  • Zhong Ji, Yunlong Yu,  Yanwei Pang, Yingming Li, Zhongfei Zhang, “Marginal Fisher Regression Classification for Face Recognition”, Proc. Pacific-Rim Conference on Multimedia, Gwangju, Korea, September, 2015.
  • Umesh Deshpande, Danny Chan, Steven Chan, Kartik Gopalan, Nilton Bila, "Scatter-Gather Live Migration of Virtual Machines", In IEEE Transactions on Cloud Computing, September 2015, DOI: 10.1109/TCC.2015.2481424 http://ieeexplore.ieee.org/document/7274710/
  • Jian Li, Zhenhua Li, Yao Liu, Zhi-Li Zhang. “Twin Clouds Make Smoothness for Transoceanic Video Telephony”, The 44th International Conference on Parallel Processing (ICPP), Sept. 2015.
  • X. Zhang, Z. Zhang, D. Hipp, L. Yin, and P. Gerhardstein, “Perception Driven 3D Facial Expression Analysis Based on Reverse Correlation and Normal Component”, AAAC 6th International Conference on Affective Computing and intelligent Interaction (ACII 2015) (Association for the Advancement of Affective Computing), Sept. 2015.
  • Xin Zhang and Yongshu Bai, Yifan Zhang, "Uses of Hardware Virtualization for Secure and Trusted Computing: A Review", Smart Computing Review, vol.5, no.4, August 2015.
  • X. Zhang, U. Ciftci, and L. Yin. “Mouth Gesture based Emotion Awareness and Interaction in Virtual Reality.” ACM SIGGRAPH, August 2015.
  • Hongxu Zhang, Yufeng Wang, Chiu C. Tan, Yifan Zhang. "mQual: A Mobile Peer-to-Peer Network Framework Supporting Quality of Service", IEEE ICDCS 2015, poster session, June 29 - July 2, 2015. 
  • Siliang Tang, Fei Wu, Si Li, and Zhongfei (Mark) Zhang, “Sketch the Storyline with CHARCOAL: a Non-parametric Approach”, Proc. International Joint Conference on Artificial Intelligence, Buenos Aires, Argentina, July, 2015, (28.8% acceptance rate).
  • Mengbai Xiao, Yao Liu, Lei Guo, Songqing Chen. “Reducing Display Power Consumption for Real-time Video Calls on Mobile Devices”, 2015 International Symposium on Low Power Electronics and Design (ISLPED), July 2015.
• 2014-15
  • Garcia, A., Mattison, E., & Ghose, K. “High-speed vision-based autonomous indoor navigation of a quadcopter,” in Proc. Unmanned Aircraft Systems (ICUAS), 2015. International Conference on (pp. 338-347). IEEE. Publication date: 09/Jun/15
  • Tianlin Li, Yaohui Hu, Ping Yang, Kartik Gopalan, "Privacy-preserving Virtual Machines", 31th Annual Computer Security Applications Conference (ACSAC), Dec. 2015, Los Angeles, CA.
  • Dmitry Evtyushkin, Dmitry Ponomarev and Nael Abu-Ghazaleh. “Covert Channels through Branch Predictors: A Feasibility Study.”  4th Workshop on Hardware and Architecture Support for Security and Privacy (HASP), held in conjunction with ISCA, Portland, OR, June 2015. 
  • Yaohui Hu, Sanket Panhale, Tianlin Li, Emine Ugur Kaynar, Danny Chan, Umesh Deshpande, Ping Yang, Kartik Gopalan, "Performance Analysis of Encryption in Securing the Live Migration of Virtual Machines", In IEEE Cloud, Jun 2015.
  • Stachecki, T.J., & Ghose, K., “Short-term Load Prediction and Energy-Aware Load Balancing for Data Centers Serving Online Requests,” in Proc. Resource-Efficient Cloud Computing Workshop, held in conjunction with Intl. Symposium on Computer Architecture (peer-reviewed, 27% acceptance rate), June 2015.
  • Chauhan, A., Sammakia, B., & Ghose, K. (2015, March). “Transient power analysis to estimate the thermal time lag of a microprocessor hot spot,” in Proc. Thermal Measurement, Modeling & Management Symposium (SEMI-THERM), March 2015, pp.75-81.
  • Kai Wang, Guoqing Xu, Zhendong Su, Yu David Liu. "GraphQ: Graph Query Processing with Abstraction Refinement," USENIX ATC, 2015.
  • Afram, F., & Ghose, K. “Flexcore: A Reconfigurable Processor Supporting Flexible, Dynamic Morphing,” in Proc. IEEE Int’l. Conf. on High-Performance Computing, pp.30-39, doi:10.1109/HiPC.2015.37.
  • Yuheng Long, Yu David Liu, Hridesh Rajan, "Intensional Effect Polymorphism," ECOOP, 2015.