Program Chairs

 

Fei-Fei Li, PhD

Co-Director, Stanford Human-Centered AI (HAI) Institute

Professor of Computer Science

Arnold Milstein, MD, MPH

Director, Clinical Excellence Research Center

Professor of Medicine

Scientific Committee

Abstract reviewers

Ehsan Adeli, PhD

Postdoctoral Research Fellow, Psychiatry, Stanford

Ehsan is a postdoctoral researcher and a NIH Fellow at Stanford University, working at the intersection of Machine Learning, Computer Vision, Computational Neuroscience, and Medical Image Analysis in the School of Medicine and the Stanford AI Lab (SAIL).

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Previously, he has worked at the University of North Carolina at Chapel Hill and the Robotics Institute, Carnegie Mellon University, Pittsburgh, PA.

 

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Ingo Beinlich, MD, MS

Partner, Cidar Health Care LLC

Ingo Beinlich is the co-founder of Cidar Health Care LLC. Prior to founding Cidar, Dr. Beinlich was a principal advisor with Coopers & Lybrand European pharmaceutical group. He founded one of the first electronic data capture companies and is licensed as an anesthesiologist from the University of Bonn, Germany.

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He received his masters in Medical Computer Science from Stanford University.

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Tanzeem Choudhury, PhD

Professor, Computing and Information Science Cornell/CornellTech
Co-founder, HealthRhythms, Inc.

Tanzeem Choudhury is a professor in Computing and Information Sciences at Cornell University. Dr. Choudhury is also a co-founder of HealthRhythms Inc, a company whose mission is to add the layer of behavioral health into all of healthcare. 

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At Cornell, she directs the People-Aware Computing group, which works on inventing the future of technology-assisted wellbeing. Tanzeem received her PhD from the Media Laboratory at MIT. She has been awarded the MIT Technology Review TR35 award, NSF CAREER award, TED Fellowship, Kavli fellowship, ACM Distinguished Membership, and Ubicomp 10 year Impact Award. For more information, please visit: http://pac.cs.cornell.edu

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Nick Foti, PhD

Research Engineer, Apple

Nick Foti is a research scientist at Apple where he works on various aspects of machine learning and how machine learning can be used to improve peoples’ health. His research interests are developing statistical and machine learning methods in order to learn structure underlying data that exhibit complex dependencies.

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Prior to Apple, Nick was a Washington Research Innovation Postdoctoral Fellow in Neuroengineering and Data Science, and then a Research Scientist, both at the University of Washington.

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Brett Kuprel

NDSEG Fellow, Electrical Engineering, Stanford

Brett Kuprel is a PhD student at Stanford advised by Sebastian Thrun. His interests include applying machine learning to healthcare, writing apps, and making a positive impact on the world. He is a humanitarian.

 

Matthew Lungren, MD, MPH

Assistant Professor of Pediatric Radiology, Stanford Univeristy Medical Center

 

 

 

 

Anoop Rao, MD, MS

Instructor, Pediatrics - Neonatal Critical Care, Stanford

Dr. Anoop Rao is an Instructor in Neonatology at Lucile Packard Children's Hospital at Stanford. Anoop completed his early clinical and research training in India before completing his MS in the Biological Engineering Division at MIT. 

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He is board-certified in Pediatrics and Clinical Informatics. Prior to Stanford, he completed his residency in Pediatrics at Columbia and Biomedical Informatics fellowship at Harvard. Additionally, he has over 5 years of medtech industry experience and has independently lent intellectual property expertise in over 100 patent infringement cases. Given his background and expertise, he is exceptionally passionate about maternal and child health innovation. At Stanford Neonatology, he runs the NeoDesign group. This group holds monthly talks by healthtech innovators and physician scientists and helps organize the annual Stanford Health++ Hackathon.

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Geoffrey W. Rutledge, MD, PhD

Chief Medical Officer & Co-founder,
HealthTap

Dr. Rutledge is Cofounder and Chief Medical Officer at HealthTap, where he developed Dr.AI with the help of HealthTap’s network of 100,000+ US-licensed doctors in 147 specialties. 

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He’s enabled hundreds of millions to get the right care at the right time and the right cost, serving free doctor answers to health questions, providing AI-based assessments of symptoms, and offering virtual consultations from the right (and best) doctors.

Dr Rutledge is a double-board certified physician who also earned a PhD in medical computer science from Stanford. He was an NIH-funded researcher who served on faculty at Harvard, Stanford, and UCSD. After Harvard, he created the first consumer health website and PHR at Healtheon/WebMD, was SVP of clinical transformation at First Consulting Group, CMIO at San Mateo Medical Center, and EVP, Product Development and CMO at Epocrates.

Geoff is an avid pilot of hang gliders and experimental aircraft, SCUBA diver, and photographer. He also enjoys bicycling and electric unicycling.

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Ida Sim, MD, PhD

Professor of Medicine, University of California San Francisco

Ida Sim, MD, PhD is a primary care physician, informatics researcher, and entrepreneur. She is a Professor of Medicine at the University of California, San Francisco, where she co-directs Informatics and Research Innovation at UCSF's Clinical and Translational Sciences Institute.

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Her research focuses on computational methods for data sharing and decision making to advance clinical care and research. Dr. Sim is co-founder of Open mHealth, a non-profit organization that is building open standards and open source tools for integrating mobile health data, and co-founderof Vivli, a global data sharing platform for participant-level clinical trials data. Dr. Sim has served on multiple advisory committees on health information infrastructure for clinical care and research, including committees of the National Research Council and National Academy of Medicine. She is a recipient of the United States Presidential Early Career Award for Scientists and Engineers (PECASE), a Fellow of the American College of Medical Informatics, and a member of the American Society for Clinical Investigation.

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Earl Steinberg, MD, MPP

Adjunct Professor of Medicine & Health Policy and Management, Johns Hopkins University

Dr. Steinberg is a nationally known expert in population health management, data analytics, and clinical informatics. He has worked in academia, at a large payer, and at a renowned integrated health care delivery system.

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He also has been a founder and CEO of two venture-backed start-ups and a highly regarded health care consultant. Most recently, Dr. Steinberg spent 5 ½ years as the CEO of xG Health Solutions, a company formed by Geisinger Health System that has helped more than 80 health care delivery systems improve their clinical and financial performance. From 2011 to 2015, Dr. Steinberg was EVP of Innovation and Dissemination and Chief, Healthcare Solutions Enterprise at Geisinger. Prior to joining Geisinger, Dr. Steinberg, was SVP for Clinical Strategy, Quality & Outcomes at WellPoint (now Anthem) and President and CEO of Resolution Health Inc. (RHI), a health care data analytics and intervention company he founded that provided innovative quality improvement and cost reduction services to health plans, employers, PBMs and disease management companies that was acquired by WellPoint. Prior to joining RHI, Dr. Steinberg spent six years as VP of Covance Health Economics and Outcomes Services Inc., Director of its Quality Assessment and Improvement Systems Division, and Co-Director of its Outcomes Studies Group, 12 years on the FT faculty at Johns Hopkins University, where he was Professor of Medicine and of Health Policy and Management and Director of The Johns Hopkins Program for Medical Technology and Practice Assessment, four years on the Federal Physician Payment Review Commission and 20 years as a member of BCBS Association’s National Medical Advisory Panel. While at Covance, Dr. Steinberg led the teams that developed three HEDIS measures and helped develop a set of measures that are used to measure quality of care in all dialysis units in the U.S.

Dr. Steinberg currently is an independent consultant, advising Johns Hopkins University regarding its Precision Medicine Initiative. He also serves as Acting Chief Strategy Officer at GNS Healthcare, which leverages proprietary artificial intelligence techniques on behalf of pharma and biotech firms, as well health plans. He also is on the Scientific Advisory Board of Embold Health and is an Adjunct Professor of Medicine and of Health Policy and Management at Johns Hopkins University. During April and part of May 2019 he was a Visiting Scholar at Stanford’s Clinical Excellence Research Center.

Dr. Steinberg received his A.B. degree from Harvard College (Summa Cum Laude), his M.D. from Harvard Medical School and a Master of Public Policy degree from the Kennedy School of Government. His residency training in internal medicine was performed at the Mass. General Hospital.

Dr. Steinberg has received numerous awards, including the Henry J. Kaiser Family Foundation Faculty Scholar Award in General Internal Medicine (1984), the “Outstanding Young Investigator” Award from the Association for Health Services Research (1988), and a Special Presidential Visionary Award from the National Kidney Foundation (2004) for his work as the scientific director of NKF’s landmark Kidney Disease Outcomes and Quality Initiative, which produced over 250 clinical practice guidelines for

management of patients with end stage renal disease. He also is a Fellow of both the American College of Physicians and AcademyHealth and has published more than 135 articles in peer reviewed journals.

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Daniel Tse, MD

Product Manager, Google Brain

Daniel’s work as a Product Manager focuses on Medical Imaging as well as external partnership development across a number of clinical domains.

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Before coming to Google, he was an early member of Watsi.org (Y-Combinator’s first non-profit) building their medical program and infrastructure in over 20 countries as well as at Palantir Technologies where he helped scale their commercial health care team and establish their Philanthropy team. Daniel received his MD at Dartmouth Medical School and studied Molecular Genetics at The Ohio State University.

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James Zou, PhD

Assistant Professor, Biomedical Data Science, Stanford

 

Mohsen Bayati, PhD

Associate Professor, Graduate School of Business, Stanford

Mohsen received a BS in Mathematics from Sharif University of Technology and a PhD in Electrical Engineering from Stanford University in 2007. His dissertation was on algorithms and models for large-scale networks.

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During the summers of 2005 and 2006 he interned at IBM Research and Microsoft Research respectively. He was a Postdoctoral Researcher with Microsoft Research from 2007 to 2009 working mainly on applications of machine learning and optimization methods in healthcare and online advertising. In particular, he helped develop a system for predicting hospital patient readmissions and obtained a decision support mechanism for allocating scarce hospital resources to post-discharge care. Their system is currently used in several hospitals across US and Europe. He was a Postdoctoral Scholar at Stanford University from 2009 to 2011 with a research focus in high-dimensional statistical learning. In 2011 he joined Stanford University as a faculty, and since 2015 he is an associate professor of Operations, Information, and Technology at Stanford University Graduate School of Business. He was awarded the INFORMS Healthcare Applications Society best paper (Pierskalla) award in 2014 and in 2016, INFORMS Applied Probability Society best paper award in 2015, and National Science Foundation CAREER award.

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Javier Carmona, PhD

Senior Editor, Nature Medicine

Javier started his studies at the University of Navarra in Spain and received a degree in Biology from the Autonomous University of Madrid. In 2013, he obtained his Ph.D. after working in Manel Esteller's Cancer Epigenetics and Biology Program in Barcelona.

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Javier continued his research as a postdoctoral fellow in the group of José Baselga at the Memorial Sloan Kettering Cancer Center in New York, where he studied the mechanisms of resistance to therapy in patients with breast cancer. In 2016 he joined Nature Medicine.

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Lance Downing, MD

Clinical Assistant Professor, Biomedical Informatics Research, Stanford

Dr. Lance Downing is faculty in Biomedical Informatics Research at Stanford and board-certified internal medicine and clinical informatics. He splits his time between clinical practice, hospital medical informatics and applications of AI in healthcare. 

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He works with the Clinical Excellence Research Center – a research group dedicated to reducing the cost of high-quality care – directing the Partnership in AI collaboration with the Stanford Artificial Intelligence Lab. Recognizing that the complexity of medicine has grown beyond the abilities of even the most expert clinician, the team focuses applications of computer vision to address some of the greatest challenges in healthcare: perfecting intended care for frail patients in settings ranging from the intensive care unit to the home. His work has been featured in the New England Journal of Medicine, Health Affairs, Annals of Internal Medicine, and the Journal of the American Medical Informatics Association on applications of artificial intelligence and health IT to lower the cost of high-quality care.

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Atilla P. Kiraly, PhD

Software Engineer, Google Health

Atilla’s work focuses on R&D of robust prediction models and applications in Medical Imaging at Google Health. Previously, he was a principal scientist at Siemens Healthineers Medical Imaging Technologies working mainly on CT and MRI post-processing for medical applications used worldwide with one winning an R&D 100 award.

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Atilla received his PhD and MS degrees in Computer Science and Electrical Engineering focused on medical imaging at The Pennsylvania State University and BS degrees in Mathematics and Physics at Hobart College.

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Curtis Langlotz, MD, PhD

Professor of Radiology, Stanford

Curtis P. Langlotz, MD, PhD is Professor of Radiology and Biomedical Informatics and Director of the Center for Artificial Intelligence in Medicine and Imaging (AIMI Center) at Stanford University.  

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As Associate Chair for Information Systems and a Medical Informatics Director for Stanford Health Care, he is responsible for the computer technology that supports the Stanford Radiology practice. The AIMI Center develops artificial intelligence methods that enable computer systems to draw inferences directly from image information and associated clinical data, augmenting the skills of human imaging professionals.  Dr. Langlotz has authored over 100 scholarly publications and the book, “The Radiology Report: A Guide to Thoughtful Communication for Radiologists and Other Medical Professionals”.  He led the development of the RadLex standard terminology for radiology report information, a national standard for imaging exam codes, and a library of radiology report templates that have been downloaded over 5 million times. Dr. Langlotz is a past president of the Radiology Alliance for Health Services Research (RAHSR) and the Society for Imaging Informatics in Medicine (SIIM), and a former board member of the Association of University Radiologists (AUR), the American Medical Informatics Association (AMIA) and the Society for Medical Decision Making (SMDM).  He currently serves on the Board of Directors of the Radiological Society of North America (RSNA) and as president of the College of SIIM Fellows. Dr. Langlotz has founded 3 health care information technology companies, the most recent of which was acquired by Nuance Communications in 2016.

 

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David Paik, PhD

Chief Scientific Officer, Sirona Medical Inc
Adjunct Lecturer, Department of Radiology, Stanford

David Paik is leading an outstanding team of research scientists working on AI algorithms in healthcare. He also co-directs a graduate course on biomedical image analysis and interpretation at Stanford.

 

Sherri Rose, PhD

Associate Professor, Health Care Policy, Harvard Medical School

Sherri Rose, PhD is an Associate Professor of Health Care Policy at Harvard Medical School and Co-Director of the Health Policy Data Science Lab. Her research in health policy focuses on risk adjustment, comparative effectiveness, and health program evaluation. 

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Dr. Rose coauthored the first book on machine learning for causal inference and has published work across fields, including in Biometrics, PMLR, Journal of Health Economics, and NEJM. She currently serves as co-editor of the journal Biostatistics and is Chair-Elect of the American Statistical Association’s Biometrics Section. Her recent honors include the ISPOR Bernie J. O’Brien New Investigator Award for exceptional early career work in health economics and outcomes research and an NIH Director’s New Innovator Award to develop machine learning estimators for generalizability in health policy. 

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Nigam Shah, PhD

Associate Professor, Medicine and Biomedical Data Science, Stanford

Nigam is an Associate Professor of Medicine (Biomedical Informatics) at Stanford University, and is an executive member of the Biomedical Informatics Graduate Program.

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Nigam’s research focuses on combining machine learning and prior knowledge in medical ontologies to enable the learning health system.

He was elected into the American College of Medical Informatics (ACMI) in 2015 and is inducted into the American Society for Clinical Investigation (ASCI) in 2016. He holds an MBBS from Baroda Medical College, India, a PhD from Penn State University and completed postdoctoral training at Stanford University.

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Marina Sirota, PhD

Assistant Professor, Pediatrics, University of California San Francisco

Marina is currently an Assistant Professor at the Bakar Computational Health Sciences Institute at UCSF. Prior to that she has worked as a Senior Research Scientist at Pfizer where she focused on developing Precision Medicine strategies in drug discovery. 

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She completed her PhD in Biomedical Informatics at Stanford University. Dr. Sirota’s research experience in translational bioinformatics spans over 10 years during which she has co-authored over 50 scientific publications. Her research interests lie in developing computational integrative methods and applying these approaches in the context of disease diagnostics and therapeutics with a special focus on studying the role of the immune system in disease. The Sirota laboratory is funded by NIA, NLM, NIAMS, Pfizer, March of Dimes and the Burroughs Wellcome Fund. As a young leader in the field, she has been awarded the AMIA Young Investigator Award in 2017.

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Walter Sujansky, MD, PhD

President, Sujansky & Associates, LLC

 

 

 

 

 

Serena Yeung, PhD

Postdoctoral Fellow, Harvard University

Currently, Serena is visiting Harvard University as a TEAM (Technology for Equitable and Accessible Medicine) postdoctoral fellow focusing on the intersection of AI and healthcare.

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In Fall 2019, she will be Assistant Professor of Biomedical Data Science and, by courtesy, of Electrical Engineering at Stanford University. Serena received her PhD from Stanford University where she was advised by Fei-Fei Li and Arnold Milstein. Her research was broadly in the areas of computer vision, machine learning, and deep learning, with particular focus on video understanding and applications to healthcare.

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