Faculty working in this area
| Faculty | website | |
|---|---|---|
| Kenneth Chiu | kchiu@binghamton.edu | |
| Weiying Dai | wdai@binghamton.edu | |
| Yincheng Jin | yjin5@binghamton.edu | |
| Zhen Xie | zxie@binghamton.edu | |
| Lijun Yin | lyin@binghamton.edu | |
| Nancy Guo | nguo1@binghamton.edu | |
| Zhaohan Xi | zxi1@binghamton.edu |
Highlights in this area
researches medical imaging, healthcare bioinformatics, biomedical image processing,
functional magnetic resonance imaging (fMRI), machine learning and pattern recognition.
She co-directs the Center for Advanced Magnetic Resonance Imaging Sciences (CAMRIS).
She is working on the aging-related brain patterns, imaging biomarkers for schizophrenia
and diabetes, formation of brain folding patterns, automatic sleep stage learning,
and LLM and deep learning on fMRI image registration and image reconstruction.
researches HCI, accessibility and healthcare to make people be healthier and live in more intelligent environment. Toward this vision, he develops novel machine learning models and apply them to enable human-centered AI, such as understanding human actions and people鈥檚 daily activities; and advance health monitoring and develop new accessibility for deaf and hard-of-hearing (DHH) community.
researches high-performance computing (HPC) with a focus on the interaction between machine learning algorithms and system-level performance optimization.
- System for Machine Learning: building modern ML/DL algorithms and systems on heterogeneous and parallel HPC architectures (e.g., GPUs and AI accelerators).
- High-Performance Computing: automatic performance optimization on HPC applications with the aid of machine learning.
- Scientific Machine Learning: accelerating HPC applications using machine learning-based approximation.
researches affective computing, human emotion analysis, biometrics and human computer interaction. He leads the Graphics and Image Computing (GAIC) Laboratory. He is working on the automatic detection of emotion and behavior status using multimodal approaches for health-care in collaborating with a medical practitioner.
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Dr. Guo develops AI/ML algorithms that utilize big data for prediction and decision-making.
Her research includes software reliability and precision medicine. Her recent research
focuses on developing and applying foundation AI models for biomarker and drug discovery
for cancer treatment. Examples of her algorithms include Dempster-Shafer belief networks
and non-negative matrix factorization/Monte Carlo Simulation for modeling multi-omics
pathways and networks.
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At CRAFT Lab, our research is dedicated to developing AI agents for cross-disciplinary
scenarios, such as healthcare decision support, with a strong emphasis on responsibility,
reliability, trustworthiness, and transparency. We strive to stay at the forefront
of technological innovation while bridging the gap between advancements and real-world
implementation. Our approach integrates humans throughout the entire lifecycle of
these AI systems to ensure ethical and effective deployment. CRAFT Lab is actively
seeking new members passionate about cross-disciplinary research and responsible AI
development. Our current focus includes LLM-as-Agent frameworks, multimodality, multi-agent
systems, and LLM security. For research opportunities and potential collaborations,
please simply contact the lab director, Dr. (email: zxi1@binghamton.edu).