Faculty

BMIR is made up of world class leaders and researchers in biomedical informatics, translational science, and quantitative sciences.

Primary

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:
Cyra June Ente: cyraente@stanford.edu

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

Olivier Gevaert, PhD

Associate Professor of Medicine, Biomedical Informatics Research

Dr. Olivier Gevaert is an associate professor at Stanford University focusing on developing machine-learning methods for biomedical decision support from multi-scale data. He is an electrical engineer by training with additional training in artificial intelligence, and a PhD in bioinformatics at the University of Leuven, Belgium. He continued his work as a postdoc in radiology at Stanford and then established his lab in the department of medicine in biomedical informatics. The Gevaert lab focuses on multi-scale biomedical data fusion primarily in oncology and neuroscience. The lab develops machine learning methods including Bayesian, kernel methods, regularized regression and deep learning to integrate molecular data or omics. The lab also investigates linking omics data with cellular and tissue data in the context of computational pathology, imaging genomics & radiogenomics. Dr. Gevaert joined BMIR in 2015 as an Assistant Professor of Medicine.

Education:
PhD, University of Leuven, Belgium, Bioinformatics

Tina Hernandez-Boussard, PhD

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 a faculty member in Institute for Immunity, Transplantation and Infection (ITI) and Center for Biomedical Informatics Research (BMIR) in Department of Medicine at Stanford University. His research focuses on the intersection of machine learning, computational immunology, and translational medicine with the overarching goal of accelerating translation of immune response-based diagnostics and therapies to clinical practice across a broad spectrum of inflammatory diseases, including infections, autoimmune diseases, organ transplant, cancers, and vaccines. His lab develops machine learning-based methods and computational frameworks to leverage biological, clinical, and technical heterogeneity across multiple datasets to identify robust disease signatures and identify novel therapies for inflammatory conditions.

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

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

Secondary

QSU Faculty

Vivek Charu, MD, PhD

Assistant Professor of Pathology and of Medicine (Quantitative Sciences)

Dr. Charu is a physician and a biostatistician. His clinical expertise is in the diagnosis of non-neoplastic kidney and liver disease (including transplantation). His research interests center on the design of observational studies and clinical trials, the analysis of observational data, and causal inference.

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

Maya Mathur, PhD

Assistant Professor (Research) of Pediatrics and Medicine (BMIR)

Dr. Mathur is an Assistant Professor in the Quantitative Sciences Unit and the Department of Pediatrics. She is the Associate Director of the Stanford Data Science’s Center for Open and Reproducible Science (CORES). She is a statistician whose methodological research focuses on meta-analysis and other forms of evidence synthesis, as well as causal inference. She has received early-career and young investigator awards from the Society for Epidemiologic Research (2022), the Society for Research Synthesis Methods (2022), and the American Statistical Association (2018).

BMIR Secondary Faculty

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

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

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

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:

Affiliated Faculty

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.

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

Justin Norden, MD

Adjunct Professor
Partner at GSR Ventures

Dr. Norden is a Partner at GSR Ventures investing in early-stage health technology startups. Prior to GSR Ventures, he was founder and CEO of Trustworthy AI which was acquired by Waymo (Google Self-Driving), worked on the healthcare team at Apple, co-founded Indicator (a data platform for biopharma), and helped launch the Stanford Center for Digital Health. Dr. Norden received an MD from the Stanford School of Medicine, an MBA from the Stanford Graduate School of Business, an M.Phil. in Computational Biology from the University of Cambridge, and a BA in Computer Science from Carleton College.

Research Interests: digital health, AI in healthcare, care model transformation, clinical outcomes with new technologies, evaluation of AI systems.

Matthew A. Eisenberg, MD

SHC Site Director - Stanford Clinical Informatics Fellowship Program
Clinical Assistant Professor

Dr. Matthew A. Eisenberg joined Stanford Health Care in early 2013 and is the Medical Informatics Director for Analytics & Innovation with a focus on interoperability and health information exchange, regulatory reporting, health care analytics, patient reported outcomes and other uses of technology to meet our strategic initiatives.

Dr. Eisenberg is board certified in Pediatrics and Clinical Informatics. He is a Clinical Assistant Professor (Affiliated) in the Stanford Center for Biomedical Informatics Research at the Stanford University School of Medicine and he serves as the Stanford Health Care site director for the Stanford Clinical Informatics Fellowship Program. He previously held the position of Clinical Assistant Professor in Pediatrics at the University of Washington School of Medicine. He is a current member of the eHealth Exchange Coordinating Committee, a Sequoia Project Board member and serves as the current chair of the Epic Care Everywhere Network Governing Council. He is a member of the Carequality Advisory Council (past co-chair) and a member of IHE USA Implementation Committee. He is a Fellow of the American Academy of Pediatrics and a member of the American Medical Informatics Association and their Clinical Informatics Community.

Find a doctor

Clinics & Services

Research Resources

Professional Training

Education Resources