Medicine
Showing 21-40 of 49 Results
-
Tina Hernandez-Boussard
Professor of Medicine (Computational Medicine), of Biomedical Data Science, of Surgery and, by courtesy, of Epidemiology and Population Health
Current Research and Scholarly InterestsMy background and expertise is in the field of computational biology, with concentration in health services research. A key focus of my research is to apply novel methods and tools to large clinical datasets for hypothesis generation, comparative effectiveness research, and the evaluation of quality healthcare delivery. My research involves managing and manipulating big data, which range from administrative claims data to electronic health records, and applying novel biostatistical techniques to innovatively assess clinical and policy related research questions at the population level. This research enables us to create formal, statistically rigid, evaluations of healthcare data using unique combinations of large datasets.
-
Daniel Katz
Assistant Professor of Medicine (Computational Medicine)
BioDaniel Katz is an Assistant Professor of Medicine in the Stanford Center for Biomedical Informatics Research (BMIR) and the Cardiovascular Medicine Divisions. He practices as an Advanced Heart Failure and Transplant Cardiologist. He completed internal medicine residency at Massachusetts General Hospital, general cardiology training at Beth Israel Deaconess Medical Center, and then joined Stanford in 2021 for his advanced heart failure training. His research focuses on identifying the various pathophysiologic patterns and mechanisms that lead to the heterogeneous syndrome of heart failure. His efforts leverage high dimensional data in many forms including clinical phenotypes, plasma proteomics, metabolomics, and genetics. He is presently engaged in analysis of multi-omic data from the Molecular Transducers of Physical Activity Consortium (MoTrPAC) and the NHLBI Trans-Omics for Precision Medicine (TOPMed) Program. His clinical interests include advanced heart failure, transplant cardiology, and mechanical circulatory support.
-
Christian Kindermann
Research Engineer, Computational Medicine
Current Role at StanfordI am a research engineer specializing in semantic technologies (ontologies and knowledge graphs). My work focuses on helping life-science practitioners and researchers manage their data.
-
Teri Klein
Professor (Research) of Biomedical Data Science, of Medicine (Computational Medicine) and, by courtesy, of Genetics
On Partial Leave from 01/16/2026 To 12/18/2026Current Research and Scholarly InterestsCo-founder, Pacific Symposium on Biocomputing
NIEHS, Site Visit Reviewer
NIH, Study Section Reviewer -
Curtis Langlotz
Senior Associate Vice Provost for Research, Professor of Radiology (Integrative Biomedical Imaging Informatics), of Medicine, of Biomedical Data Science and Senior Fellow at the Stanford Institute for Human-Centered AI
Current Research and Scholarly InterestsMy laboratory develops machine learning methods to help physicians detect disease and eliminate diagnostic errors. My laboratory is developing neural network systems that detect and classify disease on medical images. We also develop natural language processing methods that use the narrative radiology report for contrastive learning and other multi-modal methods that improve the accuracy and capability of machine learning systems.
-
Maya Mathur
Associate Professor (Research) of Pediatrics, of Medicine (Computational Medicine) and, by courtesy, of Epidemiology and Population Health
On Partial Leave from 05/01/2026 To 06/30/2026Current Research and Scholarly InterestsSynthesizing evidence across studies while accounting for biases
-
Mark Musen
Stanford Medicine Professor of Biomedical Informatics Research, Professor of Medicine (Computational Medicine) and of Biomedical Data Science
Current Research and Scholarly InterestsModern science requires that experimental data—and descriptions of the methods used to generate and analyze the data—are available online. Our laboratory studies methods for creating comprehensive, machine-actionable descriptions both of data and of experiments that can be processed by other scientists and by computers. We are also working to "clean up" legacy data and metadata to improve adherence to standards and to facilitate open science broadly.
-
Behzad Naderalvojoud
Biostatistician 2, Computational Medicine
BioBehzad Naderalvojoud is a biomedical informatics scientist at the Stanford Center for Biomedical Informatics Research. He received his Ph.D. degree in computer science at Hacettepe University, Turkey, in 2020. He is immersed in the fields of machine learning, deep learning, natural language understanding, and Big data analytics and works on health knowledge discovery platforms that transfer Big health data from volume-based to value-based by generating relational knowledge leading to innovative treatments, predictive therapeutic outcomes, and early diagnosis. He was the leader of many industrial AI projects in the fields of healthcare intelligence and information management in the Eureka cluster programs.
Dr. Naderalvojoud has published several papers in the field of natural language understanding by working on word sense disambiguation, sentiment analysis, neural word embeddings, and deep learning models through national and international projects.
He is currently working on the funded NLM grant project "Advancing Knowledge Discovery for Postoperative Pain Management" under the supervision of Dr. Tina Hernandez-Boussard. He develops descriptive, predictive, and analytical tools using OMOP CDM for postoperative pain research to facilitate timely generation of evidence across multiple populations and settings. -
Martin O'Connor
Software Dvlpr 3, Computational Medicine
Current Role at StanfordResearch software developer at Stanford Center for Biomedical Informatics Research (BMIR)
-
Natalie Pageler
Clinical Professor, Clinical Informatics
Clinical Professor, Computational MedicineCurrent Research and Scholarly InterestsIn my administrative role, I oversee the development and maintenance of clinical decision support tools within the electronic medical record. These clinical decision support tools are designed to enhance patient safety, efficiency, and quality of care. My research focuses on rigorously evaluating--1) how these tools affect clinician knowledge, attitudes, and behaviors; and 2) how these tools affect clinical outcomes and efficiency of health care delivery.
-
Shriti Raj
Assistant Professor of Medicine (Computational Medicine)
BioShriti is an Assistant Research Professor in Stanford’s Center for Biomedical Informatics Research and a Junior Faculty Fellow at the Institute for Human-Centered AI. Her research focuses on developing and evaluating human-centered decision-support techniques to help patients and clinicians make health data and algorithms actionable. She is particularly interested in creating tools to support the use of wearable health data and studying their impact on chronic condition management.
