Healthcare, Biomedical, and Scientific Computing

Faculty working in this area

Faculty Email website
Kenneth Chiu kchiu@binghamton.edu Chiu's Group
Weiying Dai wdai@binghamton.edu Dai's Group
Yincheng Jin yjin5@binghamton.edu Jin's Group
Zhen Xie zxie@binghamton.edu Xie's Group
Lijun Yin lyin@binghamton.edu Graphics and Image Computing Laboratory

Highlights in this area

Weiying Dai 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.  

Yincheng Jin 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‚Äôs daily activities; and advance health monitoring and develop new accessibility for deaf and hard-of-hearing (DHH) community.  

Zhen Xie 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.  

Lijun Yin 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.