Faculty
BMIR is made up of world class leaders and researchers in biomedical informatics, translational science, and quantitative sciences.
Jonathan H. Chen, MD, PhD
Assistant Professor of Medicine, Biomedical Informatics Research
Dr. Chen is a physician-scientist with professional software development experience as an entrepreneur and graduate training in computer science. He practices Internal Medicine for the reward of caring for patients and to inspire research, mining clinical data sources to inform recommendations for medical decision-making.
Dr. Chen is an expert in Electronic Health Records, Data-Mining, Crowd-sourcing, Recommender Systems, Collaborative Filtering, Observational Research, Medical Decision Making, Machine Learning, Secondary Analysis, Clinical Decision Support. Dr. Chen joined Stanford BMIR in 2017 as an Assistant Professor.
Education:
PhD, University of California, Irvine
MD, University of California, Irvine
Residency: Internal Medicine, Stanford University
Fellowship: Palo Alto VA Healthcare System
Manisha Desai, PhD
Professor of Medicine, Biomedical Informatics Research
Section Chief, Biostatistics
Dr. Desai is the Director of the Quantitative Sciences Unit and is an expert in the handling of missing data, the translation of randomized clinical trial findings to real-world target populations, the incorporation of digital health data to clinical trials, and the design of clinical trials. As Director of the Quantitative Sciences Unit (QSU), she manages a group of faculty and PhD and Master’s level staff who collaborate with clinical and translational investigators throughout the School of Medicine. Dr. Desai joined the Department of Medicine at Stanford University in 2009.
Education:
PhD, University of Washington, Seattle, WA, Biostatistics
Administrative Contact:
Ni Deng: nideng@stanford.edu
Deendayal Dinakarpandian, MD, PhD
Clinical Associate Professor of Medicine, Biomedical Informatics Research
Dr. Deendayal Dinakarpandian (“Dinakar”) joined BMIR in 2018 as a Clinical Associate Professor. Prior to that, he was an Associate Professor at the University of Missouri-Kansas City and came to Stanford as a Visiting Associate Professor in the Department of Medicine in 2017. Dinakar is interested in methods development and insightful informatics based on his training as a physician, biochemist, and computer scientist. He is now focused on informatics research to help transform healthcare from where it is now to what it ought to be. He is interested in capturing and integrating emerging or expert biomedical knowledge to improve computational predictions of biological and clinical relevance. Methods for adapting and evaluating machine learning. Interventional and causal predictions. Informatics research on problems in oncology, and the essential role of equity for the survival of humanity.
Education:
PhD, Case Western Reserve University, Biochemistry
MD, Jawaharlal Institute of Medical Education and Research
N. Lance Downing, MD
Clinical Assistant Professor of Medicine, Biomedical Informatics Research
Dr. Downing is a physician (Internal Medicine) and an expert in clinical decision support, electronic health records, clinician burnout, and applications of artificial intelligence in healthcare. Dr. Downing joined BMIR in 2016 as a Clinical Assistant Professor of Medicine.
Education:
MD, Case Western Reserve School of Medicine
Residency: Internal Medicine, Stanford University
Fellowship: Medical Informatics, Stanford University
Andrew Gentles, PhD
Assistant Professor of Medicine, Biomedical Informatics Research
Dr. Gentles is an expert in computational systems biology of human disease, with a focus on integration of high-throughput datasets with each other, and phenotypic information and clinical outcomes. He leads a team that uses a variety of statistical/machine learning approaches to analyze and integrate genomic and proteomic datasets. Dr. Gentles joined BMIR in 2016 as an Assistant Professor and as a member of the Quantitative Sciences Unit.
Education:
PhD, University of Southampton, UK, Theoretical particle physics
Olivier Gevaert, PhD
Assistant Professor of Medicine, Biomedical Informatics Research
Dr. Gevaert is an expert in machine learning for biomedical data fusion. His research includes work in bioinformatics, computational biology, imaging genomics, radiogenomics, quantitative imaging, machine learning and biomedical decisions support. Dr. Gevaert joined Stanford BMIR in 2015, as an Assistant Professor. Prior to that he was a research associate and post-doc at the Stanford Department of Radiology.
Education:
PhD, University of Leuven, Belgium, Bioinformatics
Tina Hernandez-Boussard, PhD
Associate Professor of Medicine, Biomedical Informatics Research
Dr. Hernandez-Boussard's background and expertise is in computational biology as well as in health-services research. Her research concentrates on accountability measures, population health, and health policy. A key focus of her research is the application of novel methods and tools to large clinical datasets for hypothesis generation, comparative effectiveness research, and the evaluation of quality healthcare delivery.
Education:
PhD, University Claude Bernard, Lyon 1, Computational Biology
Purvesh Khatri, PhD
Associate Professor of Medicine, Biomedical Informatics Research
Institute for Immunity, Transplantation and Infection
Dr. Khatri is an expert in the areas of bioinformatics, computational biology, and translational medicine. He actively collaborates with many investigators on the Stanford campus and at other institutions, with a goal to implement and disseminate new diagnostic methods to identify novel biomarkers and therapeutic targets. He and his team develop methods for the integration and analysis of high throughput genomics and proteomics data.
Education:
PhD, Wayne State University, Computer Science
Mark Musen, MD, PhD
Professor of Medicine, Biomedical Informatics Research
Director, Stanford Center for Biomedical Informatics Research
Dr. Musen leads Stanford Center for Biomedical Informatics Research and conducts research related to open science, data stewardship, intelligent systems, and biomedical decision support. His group developed Protégé, the world’s most widely used technology for building and managing terminologies and ontologies. He served as principal investigator of the National Center for Biomedical Ontology, one of the original National Centers for Biomedical Computing created by the U.S. National Institutes of Heath (NIH). He leads the Center for Expanded Data Annotation and Retrieval (CEDAR), founded as a Center of Excellence under the NIH Big Data to Knowledge Initiative, with the goal of developing new technology to ease the authoring and management of biomedical experimental metadata. Dr. Musen chaired the Health Informatics and Modeling Topic Advisory Group for the World Health Organization’s revision of the International Classification of Diseases (ICD-11). He currently directs BMIR's WHO Collaborating Center for Classification, Terminology, and Standards.
Education:
PhD, Stanford University, Medical Information Sciences
MD, Brown University
Residency, Stanford University Hospital, Internal Medicine
Administrative Contact:
Nicholas Nugent: nnugent@stanford.edu
Nigam H. Shah, MBBS, PhD
Professor of Medicine, Biomedical Informatics Research
Associate Director, Stanford Center for Biomedical Informatics Research
Dr. Shah is Associate Director of the Center for Biomedical Informatics Research.
He is a physician-scientist and an expert in approaches that combine machine learning and knowledge of medical ontologies to drive the learning health system. He develops methods to analyze large unstructured data sets for use in data-driven medicine and to enable improvements is decision-making in medicine and health care. Dr. Shah joined the BMIR faculty in 2011. Prior to that he served as a Research Scientist at BMIR and trained as a Postdoctoral Fellow with Dr. Mark Musen between 2005 and 2007.
Education:
PhD, Pennsylvania State University, Molecular Medicine
MBBS, Baroda Medical College, Medicine
Administrative Contact:
Carla Mashack: cmashack@stanford.edu
Russ B. Altman, MD, PhD
The Kenneth Fong Professor of Bioengineering, Genetics, Medicine (BMIR) and Biomedical Data Science (and Computer Science, by courtesy)
Dr. Altman’s primary research interests are in the application of computing (AI, data science andinformatics) to problems relevant to medicine. He is interested in methods for understanding drug action at molecular, cellular, organism and population levels. His lab studies how human genetic variation impacts drug response (PharmGKB).
Research Interests: Biomedical informatics, Pharmacogenomics, Pharmacology, Drug discovery, Structural Informatics, Data science, Artificial Intelligence, Natural Language Processing, Machine Learning, Genomics
Summer Han, PhD
Assistant Professor (Research) of Neurosurgery and Medicine (BMIR)
Dr. Han is an Assistant Professor of Neurosurgery and Medicine in the Stanford School of Medicine and a member of the QSU. She holds a PhD in Statistics (Yale, 2009) with concentration on statistical genetics. Dr. Han's research focuses on developing novel statistical methods for understanding the interplays between genes and the environment and for evaluating efficient screening strategies based on etiological understanding. She is the Principal Investigator of the NIH funded project for conducting GWAS, building risk prediction models, and developing decision analysis for cancer screening for second primary lung cancer (SPLC).
Research Interests: statistical genetics, molecular epidemiology, cancer screening, health policy modeling, and risk prediction modeling
Zihuai He, PhD
Assistant Professor (Research) of Neurology and of Medicine (BMIR)
Dr. He received his PhD from the University of Michigan in 2016. Following a postdoctoral training in biostatistics at Columbia University, he joined Stanford University as an assistant professor of neurology and of medicine in 2018. His research is concentrated in the area of statistical genetics and integrative analysis of omics data.
Research Interests: Statistical Genetics, Integrative Analysis of Omics Data, Neurological Disorders, High-dimensional Data Analysis, Correlated (longitudinal, familial) Data Analysis, Machine Learning
Teri Klein, PhD
Professor of Biomedical Data Science, and Medicine (BMIR)
Dr. Klein is Professor of Biomedical Data Science and Medicine. She holds a PhD in Medical Informacitcs Sciences from UCSF. Dr. Klein's area of professional expertise extends over clinical and research pharmacogenomics, the study of how variation in human genetics impacts drug response phenotypes. The PharmGKB resource is the premier repository of curated information about how human genetic variation impacts drug-response phenotypes. Her research team uses the contents of PharmGKB to create drug dosing guidelines (CPIC) and new applications in data mining, drug discovery and personal genomics.
Research Interests: Pharmacogenomics, Computational Biology, Pharmcogenomics Knowledge Base
Curtis Langlotz, MD
Professor of Radiology
Associate Chair of Information Systems
Medical Informatics Director for Stanford Health Care
Dr. Langlotz is the Director of the Center for AI in Medicine & Imaging, which develops methods to optimize how clinical data are used to promote health. As Medical Informatics Director for Stanford Health Care, he is responsible for systems that support Stanford's radiology practice.
Research Interests: Machine Learning for Imaging Decision Support, Natural Language Processing, Technology Assessment
Ron Li, MD
Clinical Assistant Professor of Medicine
Ron's work is centered around the design, implementation, and evaluation of novel systems of care delivery that can be enabled by artificial intelligence. His work spans across multiple disciplines, including clinical medicine, data science, digital health, information technology, design thinking, process improvement, and implementation science.
Research Interests: Clinical Informatics, Artificial Intelligence, Systems Thinking, Improvement Science
Natalie Pageler, MD, MEd
Clinical Professor of Pediatric Critical Care Medicine and Medicine (BMIR)
Chief Medical Information Officer, Stanford Children's Health
Program Director, Stanford Clinical Informatics Fellowship
Dr. Natalie Pageler is the CMIO at Stanford Children’s Health and is a passionate advocate for the unique needs of pediatric and obstetric patients. Dr. Pageler has been leading Stanford Children’s Digital Health program, which seeks to transform the model of pediatric and obstetric care delivery.
Research Interests: Digital Health, Adolescent Informatics and privacy issues, Patient Engagement and Data Sharing, Digital Identity, Clinical Decision Support
Jonathan Palma, MD
Clinical Associate Professor, Pediatrics (Neontal and Developmental Medicine), Medicine (BMIR)
Dr. Palma is a Clinical Professor of Pediatrics in the Division of Neonatal and Developmental Medicine at Stanford University. In addition to his clinical role he paractices in newborn intensive care. Dr. Palma holds an administrative appointment as Medical Director of Clinical Informatics at Stanford Children's Health. Dr. Palma completed a Master's in Biomedical Informatics at Stanford, became board certified in Clinical Informatics with the inaugural class in 2013, and serve as Associate Program Director for the Stanford Clinical Informatics Fellowship program.
Research Interests: clinical informatics efforts focus on optimizing electronic workflows for neonatology providers, interventional informatics, predictive analytics to hospital data
Michael A. Pfeffer, MD
Chief Information Officer and Associate Dean for Stanford Health Care), Clinical Professor in Department of Hospital Medicine and Biomedical Research (BMIR)
Michael A. Pfeffer, MD, FACP serves as Chief Information Officer and Associate Dean for Stanford Health Care and Stanford University School of Medicine. Michael oversees Technology and Digital Solutions (TDS), responsible for providing world class technology solutions to Stanford Health Care and School of Medicine, enabling new opportunities for groundbreaking research, teaching, and compassionate care across two hospitals and over 150 clinics. TDS supports Stanford Medicine’s mission to improve human health through discovery and care and strategic priorities to be value focused, digitally driven, and uniquely Stanford.
Research Interests:
Elsie G. Ross, MD, MSc
Assistant Professor of Surgery (Vascular Surgery), Assistant Professor of Medicine (BMIR)
Dr. Ross is a vascular surgeon and scientist with a keen interest in improving health care delivery through use of cutting edge technology and data science. Her lab focuses on using data science and machine learning to enable earlier detection of cardiovascular diseases, predict disease progression and outcomes.
Research Interests: Machine Learning, Precision Health, EHR, Genomics, Cardiovascular Diseases
Daniel L. Rubin, MD, MS
Professor of Biomedical Data Science, Radiology, and Medicine (BMIR)
Dr. Daniel Rubin’s laboratory develops foundational data science methods for extracting and mining meaning in unstructured biomedical data (text and images) and creates artificial intelligence applications to tackle challenging problems in radiology, pathology, and ophthalmology. He has published over 300 peer-reviewed scientific papers.
Research Interests: Artificial Intelligence, Imaging, Image Analysis, Natural Language Processing, Clinical Prediction, Clinical Decision Support
Carol Cain, PhD
Adjunct Professor
Executive Director at The Permanente Federation, KP Care Management Institute
Research Interests: Care Delivery, Clinical Decision Support, Health IT Innovation
Albert Chan, MD
Adjunct Professor
Chief of Digital Patient Experience, Sutter Health
Dr. Chan holds an MD from UC San DIego and completed his residency and chief residency in family medicine at the Stanford O'Connor Family Medicine Program. He concurrently completed his MS in Biomedical Informatics at Stanford and a research fellowship at the family medicine research at UCSF in 2004. While a MS Student at Stanford, Dr. Chan was an early member of the team that implemented the first Epic MyChart patient portal instance in the world.
Dr. Chan is an expert in change management, navigation of complex health systems, implementation of health IT at scale, mentorship of healthcare leaders and digital health innovators. His work has been recognized as a Fulbright Specialist and a 2017 Eisenhower Fellow, one of 20 U.S citizens selected annually to join a global network of leaders for change and named Becker's 105 Physician Leaders to Know in 2019.
Research Interests: health services research, digital health.
Mary Goldstein, MD
Adjunct Professor
Professor of Medicine, Center for Primary Care and Outcomes Research
Dr. Goldstein is Professor of Medicine in the Center for Health Policy/Center for Primary Care and Outcomes Research (CHP/PCOR) at Stanford University; and National Director of Data Analytics, Quality Improvement, and Research in the Office of Geriatrics and Extended Care (GEC), Veterans Health Administration (VHA). Prior to the role in GEC, Dr. Goldstein was Chief, Medical Service, at the VA Palo Alto Health Care System.
Research Interests: clinical care for patients with multiple comorbidities (mulitmorbidity) and services for frail older adults.
Michael Higgins, PhD
Adjunct Professor
Senior Direcor, Enterprise Analysis Corp.
Dr. Michael Higgins earned a BS in Mathematics and a BS Electrical Engineering at the University of Washington. He has an MS in Operations Research and a Ph.D. in Engineering-Economics from Stanford. He spent his career in industry developing healthcare information systems and medical devices. Dr Higgins returned to Stanford after retirement as an adjunct professor in 2010.
Research Interests: Utility models for time-varying outcomes, dynamic stochastic systems, cost-constrained clinical policies
Daniel Riskin, MD
Adjunct Professor
Chief Executive Officer, Verantos
Dr. Riskin is Adjunct Professor of Surgery and Adjunct Professor of Biomedical Informatics Research with a MD from Boston University, residency in surgery at UCLA, and fellowship in critical care and acute care surgery at Stanford University. He is board-certified in four specialties, including surgery, critical care, palliative care, and clinical informatics. His business training includes an MBA with a focus in bioinformatics from the Massachusetts Institute of Technology and the Stanford Biodesign Innovation Fellowship.
Research Interests: healthcare quality, technology, and policy, with a focus on translational research
Walter Sujansky, MD, PhD
Adjunct Professor
President at Sujansky & Associates, LLC
Dr. Sujansky received his M.D. and Ph.D. in medical informatics at Stanford University and his undergraduate degree in economics at Harvard College. Dr. Sujansky is the President of Sujansky & Associates, a consulting firm that has specialized in the representation, analysis, and exchange of clinical data in information systems since 2003.
Research Interests: Clinical data modeling, clinical data standards, interoperability and health information exchange, clinical data integration and normalization, disease registries, clinical data warehouses, clinical decision support systems, statistics and machine learning, health data security and privacy, software development lifecycle processes, health I.T. policy, software intellectual property law