Dr. Shen is a computer scientist and informatician working in the fields of machine learning, medical image computing, bioinformatics and big data science in biomedicine. The central theme of his lab is focused on developing computational and informatics methods for integrative analysis of multimodal imaging data, high throughput omics data, cognitive and other biomarker data, electronic health record data, and rich biological knowledge (e.g., pathways and networks), with applications to various complex disorders such as Alzheimer's disease. The goal is twofold: (1) advance computer science and bioinformatics by producing novel algorithms for analyzing large scale heterogeneous data sets; and (2) provide important new insights into the phenotypic characteristics and genetic mechanisms of normal and/or disordered biological structures and functions to impact the development of new diagnostic, therapeutic and preventative approaches. Further information about Dr. Shen's research activities is available at http://www.med.upenn.edu/shenlab/.

Dr. Shen's work has been continuously supported by the NIH and NSF. He has served on a variety of scientific journal editorial boards, grant review committees, and organizing committees of professional meetings in medical image computing and biomedical informatics. He served as the Executive Director of the Medical Image Computing and Computer Assisted Intervention (MICCAI) Society between 2016 and 2019. He is a fellow of the American Institute for Medical and Biological Engineering (AIMBE).