Seminar by Dr. Shaoting ZHANG from SenseTime and Shanghai Artificial Intelligence Laboratory

Current medical artificial intelligence algorithms face several bottlenecks, including challenges in addressing long-tail diseases, high annotation costs, and limited knowledge transferability. In this talk, we will introduce our research on a versatile medical AI foundation model, which leverages large-scale cross-modal, cross-center, and cross-disease data. Additionally, we will showcase our recent achievements in areas such as vision, language, multimodal learning, and new drug discovery.

Dr. Shaoting Zhang is the VP and Deputy Head of Research at SenseTime. He also serves as the Head of Smart Health and the Principal Scientist at Shanghai Artificial Intelligence Laboratory. Before joining SenseTime, he was an associate professor at UNC Charlotte. He received PhD in Computer Science from Rutgers, M.S. from Shanghai Jiao Tong University, and B.E. from Zhejiang University. He has dedicated nearly 20 years to robust and large-scale medical image analytics and earned many awards, including multiple Young Scientist Awards and nominations in MICCAI, one of the most cited articles in Medical Image Analysis, and the Ralph E. Powe Junior Faculty Enhancement Award from Oak Ridge Associated Universities. He has published over 100 papers, with 15,000 citations and H-Index 60. He is on the editorial board of Medical Image Analysis and Neurocomputing, and a senior member of the IEEE.