Speaker Profile
Biography
David S. Liebeskind, MD, FAHA, FAAN is Professor of Neurology at the University of California, Los Angeles (UCLA) where he serves as the Associate Neurology Director of the UCLA Stroke Center and the Neurology Director of the Stroke Imaging Program. He is Co-Director of the UCLA Cerebral Blood Flow Laboratory and Director of the UCLA Vascular Neurology Residency Program. He trained in chemical engineering at Columbia University and completed his MD at New York University School of Medicine. Postgraduate medical training included internship at Beth Israel Hospital, Boston and neurology residency at UCLA. After his residency, he completed a fellowship in stroke and cerebrovascular disease at UCLA and subsequently joined the faculty in the Departments of Neurology and Radiology at the University of Pennsylvania. He has maintained extensive clinical activity across a broad range of cerebrovascular disorders ranging from carotid disease to unusual causes of stroke. Clinical expertise includes cerebral venous thrombosis, arterial dissection, moyamoya syndrome and other causes of stroke in the young. His principal research interests include novel neuroimaging approaches to elucidate fundamental pathophysiologic correlates of cerebrovascular disease in humans with a particular focus on the collateral circulation. His work on collateral perfusion in acute ischemic stroke draws on advances in noninvasive, multimodal CT and MRI and detailed analyses of digital subtraction angiography. He directs an angiography and imaging core laboratory that has participated in central readings of MERCI, Multi MERCI, IMS-III, TREVO EU and TREVO 2. His research on collaterals in intracranial atherosclerosis complements his work on acute stroke, utilizing computational fluid dynamic modeling and estimates of fractionalflow to predict risk of ischemia and reperfusion hemorrhage.
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




