Biography
Sharat Israni previously was Executive Director, Data Science, at Stanford Medicine. A long serving Technology executive, Sharats teams pioneered the use of Big Data. He served as VP of Data at Yahoo (19992008) and Intuit (201013), which pioneered Big Data Science to reinvent their products. He led Digital Media systems for broadcast interactive TV at Silicon Graphics; and Data teams at IBM and HP. Sharat has been PI for NSF, NIH and RCUK workshops on Data Science topics in Biomedicine, and is a peer reviewer of some scientific journals.

Biography
Regina Barzilay is a pioneering leader in developing machine learning methods for drug discovery and clinical AI. .Her groundbreaking work has produced AI models for early cancer detection and therapeutic discovery that have redefined what is possible in clinical diagnostics and biomedical innovation. At MITs Computer Science and Artificial Intelligence Laboratory and as AI Faculty Lead for the Jameel Clinic, she has advanced methods that detect breast and lung cancer earlier and more accurately, forecast adverse drug effects before human trials, and accelerate the design of novel therapeutics.Her research blends cutting-edge machine learning with a commitment to responsible integration of AI into precision medicine, ensuring these technologies are safe, equitable, and impactful for patients worldwide. Barzilays contributions have earned her numerous honors, including the MacArthur Fellowship, election to the National Academy of Medicine, the National Academy of Engineering and recognition as one of the most influential voices shaping the future of AI in healthcare.

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Biography
James an Associate Professor of Biomedical Data Science and, by courtesy, of Computer Science and Electrical Engineering at Stanford University. James works on making AImore reliable, human-compatible and statistically rigorous, and am especially interested in applications in human disease and health. James received his Ph.D from Harvard in 2014, and was at one time a member of Microsoft Research, a Gates Scholar at Cambridge and a Simons fellow at U.C. Berkeley. James joined Stanford in 2016 and am excited to also be a Chan-Zuckerberg Investigator. We are also a part of the Stanford AI Lab. His research is supported by two Chan-Zuckerberg Biohub Investigator Awards, the Sloan Fellowship, the NSF CAREER Award, a Top Ten Clinical Achievement Award and faculty awards from Google, Adobe and Amazon.

Biography
Chris Hare is an Executive Director of Business Planning at Canon Medical Informatics, a global leader in medical diagnostic imaging and healthcare IT solutions. With over 15 years of experience in the healthcare and life science industry, he has a proven track record of driving strategic vision, business growth, and portfolio expansion across diverse markets and technologies. Chris's core competencies include corporate strategy, business development, MA, product management, and emerging technologies such as AI, genomics, and precision medicine. He has led and contributed to multiple corporate initiatives that have resulted in significant revenue growth, market penetration, customer satisfaction, and competitive advantage for Canon Medical and its subsidiaries. He is passionate about leveraging his technical and business expertise to create innovative solutions that improve the quality of life for all people.

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Radiomics Radiogenomics: Harnessing Precision Imaging for Oncology
Step into the future of medical imaging and consider the transformative impact of precision medicine, where radiology, pathology, oncology, and data science converge to deliver personalized cancer care. Discover how radiomics and radiogenomics are redefining cancer diagnosis and explore the integration of advanced imaging, AI, and molecular data to deliver personalized lung cancer treatment.

Biography
Dr. Olivier Gevaert is an Associate Professor at Stanford University at the Stanford Center for Biomedical Informatics Research in the Departments of Medicine and Biomedical Data Science. Dr. Gevaerts research is at the forefront of precision medicine, utilizing machine learning and artificial intelligence to integrate diverse biomedical data typessuch as imaging, genomic, and clinical data. His work has implications for oncology, where he applies informatics techniques to enhance the understanding of cancer progression and to tailor treatments based on patient data.A prolific researcher, Dr. Gevaert has published extensively on topics related to biomedical data science, AI in healthcare, and the development of novel computational methods to improve decision-making. He has received recognition for his contributions to the fields of data science and biomedical informatics.Dr. Gevaerts groundbreaking work continues to drive innovation at the intersection of technology and healthcare, pushing the boundaries of how data can be leveraged to improve patient outcomes.

Biography
Angel Alberich-Bayarris has 15 years of experience in the field of medical imaging and computer vision,he possesses deep knowledge of the challenges and opportunities in diagnostics and drug development. He has worked in the development of several algorithms for Imaging Biomarkers analysis that promoted the creation of the company QUIBIM (Quantitative Imaging Biomarkers in Medicine), focused in the creation of a platform for the analysis of Imaging Biomarkers. Alberich-Bayarri is the author of more than 100 articles in prestigious international journals, author of 20 book chapters and editor of 2 books. He is the inventor of 7 patents and has received numerous international awards for his innovative work, including the MIT Innovators Under 35 in 2015.

Biography
Joe Petro leads innovation, strategy, product, engineering, and customer success teams delivering integrated AI healthcare experiences that enhance the clinician–patient relationship, improve outcomes, and expand access to care. His organization develops generative AI–powered clinical workflow and productivity solutions for physicians, nurses, radiologists, and revenue cycle professionals—including Microsoft Dragon Copilot, Dragon Medical One, PowerScribe, and PowerShare—along with the platform that supports extensibility and democratization of AI through an expansive healthcare-specific partner ecosystem.

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Biography
Dr. Langlotz is Professor of Radiology, Medicine, and Biomedical Data Science, and Senior Associate Vice Provost for Research at Stanford University. He also serves as Director of the Center for Artificial Intelligence in Medicine and Imaging (AIMI Center), which comprises over 250 faculty at Stanford who conduct interdisciplinary machine learning research to promote health. Dr. Langlotz's laboratory develops machine learning methods to detect disease and eliminate diagnostic errors. He has led many national and international efforts to improve medical imaging, including the RadLex terminology standard and the Medical Imaging and Data Resource Center (MIDRC), a U.S. national imaging research resource.

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The Future of AI in Medical Imaging
We will learn how AI will change the practice of medical imaging using current examples from the research laboratory, assess the shortcomings of AI that will limit the application of these new methods, and predict the effects of AI on the radiologist workforce.

Biography
Dr. Langlotz is Professor of Radiology, Medicine, and Biomedical Data Science, and Senior Associate Vice Provost for Research at Stanford University. He also serves as Director of the Center for Artificial Intelligence in Medicine and Imaging (AIMI Center), which comprises over 250 faculty at Stanford who conduct interdisciplinary machine learning research to promote health. Dr. Langlotz's laboratory develops machine learning methods to detect disease and eliminate diagnostic errors. He has led many national and international efforts to improve medical imaging, including the RadLex terminology standard and the Medical Imaging and Data Resource Center (MIDRC), a U.S. national imaging research resource.

Biography
Kevin Blyth is Professor of Respiratory Medicine in the School of Cancer Sciences at the University of Glasgow. He splits his time between the Wolfson Wohl Cancer Research Centre, the CRUK Scotland Institute and the Queen Elizabeth University Hospital, where he leads the Glasgow Pleural Disease Unit. He founded the Macmillan Scottish Mesothelioma Network, which coordinates care and access to clinical trials for patients across Scotland and is National Clinical Lead for Mesothelioma. He leads the PREDICT-Meso International Accelerator Network, funded by Cancer Research UK (160 investigators from 100 institutions in 17 countries) He is academic lead of the UKRI-funded Living Lab Radiogenomic Project, which is developing AI precision medicine tools suitable for use by industry and academic partners. He is recent ex-Chair of the European Respiratory Society Thoracic Oncology Assembly (11.2), a member of the IASLC Mesothelioma Committee, a Trustee of Mesothelioma UK and an Associate Editor of Thorax.

Biography
Dr. Langlotz is Professor of Radiology, Medicine, and Biomedical Data Science, and Senior Associate Vice Provost for Research at Stanford University. He also serves as Director of the Center for Artificial Intelligence in Medicine and Imaging (AIMI Center), which comprises over 250 faculty at Stanford who conduct interdisciplinary machine learning research to promote health. Dr. Langlotz's laboratory develops machine learning methods to detect disease and eliminate diagnostic errors. He has led many national and international efforts to improve medical imaging, including the RadLex terminology standard and the Medical Imaging and Data Resource Center (MIDRC), a U.S. national imaging research resource.

Biography
Regina Barzilay is a pioneering leader in developing machine learning methods for drug discovery and clinical AI. .Her groundbreaking work has produced AI models for early cancer detection and therapeutic discovery that have redefined what is possible in clinical diagnostics and biomedical innovation. At MIT’s Computer Science and Artificial Intelligence Laboratory and as AI Faculty Lead for the Jameel Clinic, she has advanced methods that detect breast and lung cancer earlier and more accurately, forecast adverse drug effects before human trials, and accelerate the design of novel therapeutics. Her research blends cutting-edge machine learning with a commitment to responsible integration of AI into precision medicine, ensuring these technologies are safe, equitable, and impactful for patients worldwide. Barzilay’s contributions have earned her numerous honors, including the MacArthur Fellowship, election to the National Academy of Medicine, the National Academy of Engineering and recognition as one of the most influential voices shaping the future of AI in healthcare.

Biography
A Global HealthTech Executive specializing in AI innovation and digital transformation, Dr. Alexander (Sandy) Weir brings over 25 years of experience leading cutting-edge initiatives across public and private sectors. His leadership has spanned start-ups and enterprise environments, positioning him as a key figure in scaling AI-driven platforms, modernizing healthcare systems, and aligning technology with strategic business goals. As a Global Senior Program Manager at Canon Medical Research Europe, Dr. Weir directed multi-million-pound global programs in AI and precision informatics, helping to establish Canons AI Centre of Excellence and steering complex product development lifecycles. He also led health IT governance frameworks, integrating next-gen diagnostics, NLP, and bioinformatics across global RD teams. Sandy holds an Eng.D in Applied Photonics and a B.Eng. in Electrical Electronic Engineering, both from Heriot-Watt University. He is a Chartered Engineer (CEng) and research committee member with the Scottish Funding Council, and an Honorary Research Fellow at the University of Glasgow.

Biography
Janusz Dutkowski is Founder and CEO of Data4Cure, Inc. a company focused on combining systems biology, machine learning and AI to facilitate continuous translation of biomedical data to knowledge. His background is in mathematics and computer science and he has been working at the intersection of mathematics, computer science and biology to develop new data driven technologies to advance the discovery of new biomarkers and precision based therapies. His research contributions include the development of methods for multiscale analysis of molecular networks and integrative methods for biomarker discovery from multidimensional data. He has co authored over 20 research papers published in scientific journals including Nature Biotechnology, Science and Cell.

Biography
Joe Petro leads innovation, strategy, product, engineering, and customer success teams delivering integrated AI healthcare experiences that enhance the clinician–patient relationship, improve outcomes, and expand access to care. His organization develops generative AI–powered clinical workflow and productivity solutions for physicians, nurses, radiologists, and revenue cycle professionals—including Microsoft Dragon Copilot, Dragon Medical One, PowerScribe, and PowerShare—along with the platform that supports extensibility and democratization of AI through an expansive healthcare-specific partner ecosystem.

Biography
Dr. Langlotz is Professor of Radiology, Medicine, and Biomedical Data Science, and Senior Associate Vice Provost for Research at Stanford University. He also serves as Director of the Center for Artificial Intelligence in Medicine and Imaging (AIMI Center), which comprises over 250 faculty at Stanford who conduct interdisciplinary machine learning research to promote health. Dr. Langlotz's laboratory develops machine learning methods to detect disease and eliminate diagnostic errors. He has led many national and international efforts to improve medical imaging, including the RadLex terminology standard and the Medical Imaging and Data Resource Center (MIDRC), a U.S. national imaging research resource.

Biography
Sharat Israni previously was Executive Director, Data Science, at Stanford Medicine. A long serving Technology executive, Sharats teams pioneered the use of Big Data. He served as VP of Data at Yahoo (19992008) and Intuit (201013), which pioneered Big Data Science to reinvent their products. He led Digital Media systems for broadcast interactive TV at Silicon Graphics; and Data teams at IBM and HP. Sharat has been PI for NSF, NIH and RCUK workshops on Data Science topics in Biomedicine, and is a peer reviewer of some scientific journals.

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 fractional flow to predict risk of ischemia and reperfusion hemorrhage.

Biography
Dr. Jadwiga Bienkowska is a Head of Computational Biology at Pfizer, Oncology Research and Development (ORD). Dr. Bienkowska has over 20 years of experience working in Pharma and Biotech. Over her career she has built and led teams of biologists, data scientists and engineers applying at-scale Computation, Machine Learning and AI to drug development problems.At ORD Dr. Bienkowska focuses on development of breakthrough therapies for Cancer. Dr. Bienkowskas team works with biologists and clinicians on decoding multimodal data into interpretable models of mechanisms driving cancer progression and resistance to treatment. Insights generated by these models accelerate drug development through new target discovery, MOA studies, patient, and biomarker selection strategies. Dr. Bienkowska holds a PhD in Physics from the University of Chicago and completed postdoctoral training at Harvard Medical School and Dana Farber Cancer Institute.

Biography
Dr. Martin Stumpe serves as the CTO CAIO of Danaher Corporation, where he leads the transformation to make Danaher and its operating companies fully AI- and Tech-enabled. Before joining Danaher, Dr. Stumpe served as the CAIO at Tempus, where he led the development of AI algorithms from NGS and digital pathology to improve clinical context and decision-making for better patient care. Prior to Tempus, Dr. Stumpe founded and led the Cancer Pathology project at Google, which uses artificial intelligence to increase the accuracy in image-based cancer detection and grading. Earlier in his career, Dr. Stumpe was part of the Kepler team at NASA Ames Research Center; and before that, he was a postdoctoral researcher at Stanford University focusing on molecular dynamics simulations to study chaperone-induced protein folding. Dr. Stumpe holds a PhD in Computational and Theoretical Physics from the Max Planck Institute for Biophysical Chemistry in Goettingen, Germany

Talk
TBD
TBD (coming soon)

Biography
Rajesh Shah, MD, earned his medical degree at The University of Chicago Pritzker School of Medicine in 2004, followed by a diagnostic radiology residency at University of Illinois Medical Center in Chicago (2009) and a vascular and interventional radiology fellowship at Stanford University Hospital in 2010. Since 2023 he has been Director of Interventional Radiology at the California Pacific Medical Center, Clinical Associate Professor at Stanford University, and an Interventional Radiologist at the VA Palo Alto Health Care System, where he has served in various leadership roles. Prior experience includes private practice and faculty roles at Weill Cornell Medical College and Memorial Sloan-Kettering Cancer Center in New York City. As an educator, Dr. Shah has mentored junior IR faculty at the VA Palo Alto, Stanford University, and at the California Pacific Medical Center. He has mentored trainees on research grants and created the VA resident rotation and mini-fellowship for IR-bound residents. Dr. Shah serves as the Society for Interventional Radiology (SIR) Division Councilor for Quality and Performance Improvement overseeing several committees dedicated to quality. In this role, he developed the Quality Improvement program for the SIR, and launched the VIRTEX Clinical Data Analytics Platform. Dr. Shah was appointed as affiliated faculty at the Stanford Center for Artificial Intelligence in Medicine and Imaging (AIMI) and was awarded an AIMI grant to investigate machine learning in radiomics which has led to publications on machine learning in radiomics for lung cancer. He has published research on hepatocellular carcinoma, small-cell lung cancer, and embolic therapies. He is a Fellow of the Society of Interventional Radiology and active in the Society of Interventional Radiology and the American College of Radiology.

Biography
Alex Moreau is a senior leader at Champions Oncology, where he drives strategic partnerships and platform-enabled innovation in oncology target discovery and translational biomarker research. With over a decade of experience at the intersection of science and technology, he has led and supported oncology drug discovery programs across several world-leading CROs and advised biotechnology companies in gene editing and next-generation sequencing (NGS) through various consulting roles. Alex holds a PhD in Neuroscience from Université Paris-Saclay (France) and completed his postdoctoral research in experimental gene therapy at University College London (UK).

Biography
Dr. Daneshjou studied Bioengineering at Rice University before matriculating to Stanford School of Medicine where she completed her MD and a PhD in Genetics with Dr. Russ Altman as part of the medical scientist training program. She completed dermatology residency at Stanford as part of the research track and completed a postdoc in Biomedical Data Science with Dr. James Zou. She currently is the assistant director of the Center of Excellence for Precision Heath Pharmacogenomics, director of informatics for the Stanford Skin Innovation and Interventional Research Group (SIIRG), a founding member of the Translational AI in Dermatology (TRAIND) group, and a faculty affiliate of Human-centered Artificial Intelligence (HAI) and the AI in Medicine and Imaging (AIMI) centers.

Biography
Maria del Mar Alvarez-Torres is a Computational Biologist specializing in Integrative Cancer Research at the Program of Mathematical Genomics, Columbia University. Her multidisciplinary work combines genomics, artificial intelligence, and medical imaging to explore tumor evolution and treatment responses. With a particular focus on aggressive and heterogenous cancers like glioblastoma and B-cell lymphomas, Mary has led collaborative projects since her PhD, including multicenter studies with dozens of institutions. Her goal is to bridge cutting-edge technology and cancer research to better understand cancer mechanisms and improve treatment strategies.

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.