Dr. Kewei Chen is a research professor at School of Health Solutions, ASU. He got his Ph.D. Degree in Biomathematics, UCLA. He is the founding Director, the Computational Image Analysis and Research Program, Banner Alzheimer’s Institute (BAI), former director of DMSC, Arizona ADRC under NACC. Currently he also serves as a scientific consultant to BAI; and holds research professorships at Uni of Arizona.
Dr. Chen is well-known for his biostatistics and neuroimaging expertise with his involvement in ML/AI/DL. He developed multiple statistical methods to address the challenges related to medical research. Using and developing neuroimaging analytic/statistical techniques in PET, MRI and functional MRI, his methodological research interests also include PET tracer kinetic modeling, measuring local and global volume changes using various MRI techniques, brain functional connectivity, multi-modal data integration, optimally tracking amyloid/glucose change over time and as sensitive biomarkers for clinical trials. His primary scientific interests have been the studies of human brain functions and diseases such as AD especially its prevention.
He has been involved in multiple research projects as PI, co-PI or key personnel, and authored numerous publications with H-index of 108 reported in Google Scholar or 92 at ResearchGate (as of June, 2024). Research.com lists his ranking 6741 world-wide, and 3663 in the United State of America as of 2024.
Dr. Kewei Chen is a research professor at School of Health Solutions, ASU. He got his Ph.D. Degree in Biomathematics, UCLA. He is the founding Director, the Computational Image Analysis and Research Program, Banner Alzheimer’s Institute (BAI), former director of DMSC, Arizona ADRC under NACC. Currently he also serves as a scientific consultant to BAI; and holds research professorships at Uni of Arizona.
Dr. Chen is well-known for his biostatistics and neuroimaging expertise with his involvement in ML/AI/DL. He developed multiple statistical methods to address the challenges related to medical research. Using and developing neuroimaging analytic/statistical techniques in PET, MRI and functional MRI, his methodological research interests also include PET tracer kinetic modeling, measuring local and global volume changes using various MRI techniques, brain functional connectivity, multi-modal data integration, optimally tracking amyloid/glucose change over time and as sensitive biomarkers for clinical trials. His primary scientific interests have been the studies of human brain functions and diseases such as AD especially its prevention.
He has been involved in multiple research projects as PI, co-PI or key personnel, and authored numerous publications with H-index of 108 reported in Google Scholar or 92 at ResearchGate (as of June, 2024). Research.com lists his ranking 6741 world-wide, and 3663 in the United State of America as of 2024.