Alexander Sicular

Richard Chen

Cao Gang

Xu Yan

Hao Chen

Peter Schueffler

Lee Cooper

Chuan Xu

Savitri Krishnamurthy

David Zhang

Gareth Turner

Desiree Abdurachim

Tan Char Loo

Giovanni Lujan

Dr Lujan holds dual board certification in Anatomic and Clinical Pathology, and he is also certified by The American Board of Artificial Intelligence in Medicine. His clinical expertise is in Gastrointestinal Pathology. He completed a Surgical Pathology fellowship at The Johns Hopkins Medical Institutions after graduating from the Pathology residency program at The University of Texas Southwestern Medical Center. Dr Lujan has held previous academic appointments at The Johns Hopkins University School of Medicine and The University of Texas Southwestern Medical School. He was director of a GI fellowship program for several years.

Guanglei Zhang

Thaker Harshwardhan

Liansheng Wang

Chuan Xu

Xu Yan

Lewis Hassell

Zaibo Li

His practice and academic interests are breast/gynecological pathology, cytopathology and digital pathology. He completed his residency, fellowship in Breast/Gynecologic Pathology and Cytopathology at UPMC, Pittsburgh, PA. He has published more than 150 scientific articles and many book chapters. He is currently served as section or associate editor/editorial board for several Pathology Journals and served in multiple national society committees. He has presented lectures on many national/international pathology conferences and teaching courses.

Khor Li Yan

Xiangxue Wang

Hao Wang

Naoko Tsuyama

Arvind Rao

Arvind Rao is an Associate Professor in the Department of Computational Medicine and Bioinformatics at the University of Michigan. His group uses image analysis and machine learning methods to link image-derived phenotypes with genetic data, across biological scale (i.e. single cell, tissue and radiology data). Such methods have found application in radiogenomics, drug repurposing based on phenotypic screens and spatial profiling in tissue, as well as in spatial transcriptomics. Arvind received his PhD in Electrical Engineering and Bioinformatics from the University of Michigan, specializing in transcriptional genomics, and was a Lane Postdoctoral Fellow at Carnegie Mellon University, specializing in bioimage informatics.

Ahmed Fadiel

Dr. Fadiel has more than 20 years of research experience in cancer molecular biology and bioinformatics developing protein interaction networks and pathway models to increase understanding of cancer progression. His research and development work in academia and industry used molecular dynamics simulations to study structural aspects of drug/target/ligand interactions. Dr. Fadiel has experience integrating and analyzing high throughput data and developing computational methods and tools for analyzing and incorporating these data. Dr. Fadiel has developed many novel bioinformatics algorithms and tools for Oncology Data Analysis, including digital pathology and AI-based Oncology GIS. Dr. Fadiel has 15 years of experience in teaching bioinformatics and computational biology.