University of Florida’s Intelligent Critical Care Center (IC3) recently welcomed two new researchers to their growing staff.
Pinaki Sarder, PhD, is IC3’s new Associate Director of Imaging and an Associate Professor of Quantitative Health in the Department of Medicine. His research focuses on computational bio-imaging using cutting-edge AI and machine learning tools.
The University of Florida’s approach of studying AI from different directions has created a wonderful opportunity for researchers from multiple disciplines to collaborate and solve important problems of our current times.
Dr. Pinaki Sarder
Dr. Sarder comes to UF after seven years at the University of Buffalo, where he was an associate professor with specialties in medical imaging analysis and statistical data analysis, and post-doc positions at Harvard University and Washington University in St. Louis.
His most recent publication appeared in Communications Medicine in August, but Dr. Sarder is already busy collaborating with researchers around the world who are focused on the fusion of spatial omics and imaging data to define normal healthy (“reference”) cells and to study the intersection of these reference cells and disease cells in the context of chronic kidney diseases.
Wei Shao, PhD, is IC3’s new Assistant Director of AI Imaging Research and an Assistant Professor of AI for Quantitative Health in the Department of Medicine. His research focuses on developing artificial intelligence methods in medical imaging to improve patient care.
I am excited to join IC3 and contribute to the development of artificial intelligence in medical imaging research and education at IC3 and across UF.
Dr. Wei Shao
Dr. Shao comes to UF after a three-year stint at Stanford University as a Postdoctoral Research Fellow in deep learning and medical imaging.
His research has been published in top-tier journals such as Medical Image Analysis and IEEE Transactions on Medical Imaging. Dr. Shao’s current projects include developing machine learning algorithms to accurately and quickly diagnose diseases in medical images and integrating image processing algorithms into clinical workflows.