Speaker Profile
M.D., Professor, U. of Pittsburgh
Biography
Dr.Alexanderani is an Assistant Professor of Pathology at the department of pathology, University of Pittsburgh School of Medicine, specializing in Computational Pathology and Artificial Intelligence at the Computational Pathology and AI Center of Excellence. He directs a quality assurance AI program dedicated to advancing pathology through cutting-edge multimodal machine learning algorithms, focusing on "Pathomics" to uncover histopathological features in digital images and develop next-generation theragnostic tools that enhance precision medicine.
As a physician-scientist, Dr. Alexanderani has significantly contributed to the field by holding numerous patents, grants, receiving prestigious awards, and authoring book chapters and manuscripts in high-impact journals, along with platform presentations at major national and international conferences. Prior to his role at University of Pittsburgh, he was the inaugural fellow in Computational Pathology and AI at Weill Cornell, where he received the prestigious NIHT32 award on the Pathologist Scientist track and the iDEA-iTECH award in precision medicine and computational biology.
Session Abstract – PMWC 2026 Silicon Valley
Track Chair:
Sharat Israni, UCSF
PMWC Award Ceremony
• Regina Barzilay, MIT
• Joe Petro, Microsoft
• Curtis P. Langlotz, Stanford University
Keynote: The Future of AI in Medical Imaging
• Curtis P. Langlotz, Stanford University
From Foundation Models to Digital Twins: AI Reshaping Clinical Imaging
• Chair: Alexander Weir, Canon Medical
• Regina Barzilay, MIT
• Joe Petro, Microsoft
• Curtis P. Langlotz, Stanford University
Fireside Chat
• Eric Horvitz, Microsoft
• Curtis P. Langlotz, Stanford University
Getting Real Results with AI: Better Molecules, Smarter Devices, Faster Innovation
• Martin Stumpe, Danaher
Keynote: AI Tools for Cancer Diagnostics and Treatment
• Regina Barzilay, MIT
Core AI Methods for Precision Medicine Foundations
• Chair: Sharat Israni, UCSF
• James Zou, Stanford University
From Multimodal Data to Clinical Digital Twins: Linking Imaging, Omics, and Decisions
• Stephen Quake, Stanford
AI & Omics Foundation Models Powering Translational Research
• Chair: Janusz Dutkowski, Data4Cure
• Alex Moreau, Champions Oncology
• Jadwiga Bienkowska, Pfizer
AI-Enhanced Imaging: Radiomics, Radiogenomics, and Simulation
• Chair: Chris Hare, Canon Medical
• Ángel Alberich-Bayarri, Quibim
• Kevin Blyth, University of Glasgow
• Maria del Mar Alvarez-Torres, Columbia University
Clinical Workflow Integration & Decision Support in Imaging
• Chair: Sharat Israni, UCSF
• David S. Liebeskind, UCLA
• Rajesh Shah, UCSF
• Roxana Daneshjou, Stanford University
• Mohammad Alexanderani, U Pitt
AI-Powered Serverless HPC for Scientific Discovery
• Fengbo Ren, Fovus
