School of Medicine
Showing 1-64 of 64 Results
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Russ B. Altman
Kenneth Fong Professor and Professor of Bioengineering, of Genetics, of Medicine (General Medical Discipline), of Biomedical Data Science and, by courtesy, of Computer Science
Current Research and Scholarly InterestsI refer you to my web page for detailed list of interests, projects and publications. In addition to pressing the link here, you can search "Russ Altman" on http://www.google.com/
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Euan A. Ashley
Associate Dean, School of Medicine, Professor of Medicine (Cardiovascular), of Genetics, of Biomedical Data Science and, by courtesy, of Pathology at the Stanford University Medical Center
Current Research and Scholarly InterestsThe Ashley lab is focused on precision medicine. We develop methods for the interpretation of whole genome sequencing data to improve the diagnosis of genetic disease and to personalize the practice of medicine. At the wet bench, we take advantage of cell systems, transgenic models and microsurgical models of disease to prove causality in biological pathways and find targets for therapeutic development.
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Carlos Bustamante
Professor of Biomedical Data Science, of Genetics and, by courtesy, of Biology
Current Research and Scholarly InterestsMy genetics research focuses on analyzing genome wide patterns of variation within and between species to address fundamental questions in biology, anthropology, and medicine. We focus on novel methods development for complex disease genetics and risk prediction in multi-ethnic settings. I am also interested in clinical data science and development of new diagnostics.I am also interested in disruptive innovation for healthcare including modeling long-term risk shifts and novel payment models.
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Michelle Whirl-Carrillo
Senior Research Scientist, Biomedical Data Science
Current Role at StanfordPharmGKB Director
www.pharmgkb.org -
Helio Costa
Instructor, Pathology
Instructor, Biomedical Data ScienceBioHelio Costa, PhD, is a geneticist with expertise in genomics, molecular biology, molecular oncology, and bioinformatics. He is currently an Instructor within the Departments of Pathology and Biomedical Data Science at Stanford Medical School. Dr. Costa's research utilizes next-generation sequencing to develop new clinical genome and transcriptome profiling methods with the end goal of translating these tools to clinical diagnostic tests for implementation at Stanford Health Care. His research group is also developing data science and machine learning methods to model and predict clinical outcomes and aid in clinical decision support. He is a co-Investigator on the NIH-funded Clinical Genome Resource (ClinGen) Consortium, and leads the engineering and biocuration teams building the Gene and Variant Curation Interfaces which are used by health care providers, researchers and the clinical genetics community to interpret the clinical significance of genetic alterations identified in patients during routine DNA sequencing. He is the founding director of the Stanford Clinical Data Science Fellowship where post-doctoral fellows engage in interdisciplinary clinical research and embed in health care workflows learning, building and deploying real-world health data solutions in the Stanford Health Care system. Additionally, he is an Attending Geneticist, and Assistant Lab Director of the Molecular Genetic Pathology Laboratory for Stanford Health Care. Dr. Costa received his BS in Genetics from University of California, Davis, his PhD in Genetics from Stanford University School of Medicine, and his ABMGG Clinical Molecular Genetics and Genomics fellowship training from Stanford University School of Medicine.
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Mark R. Cullen, MD
Director, Center for Population Health Sciences, Professor of Medicine, of Biomedical Data Science, of Health Research & Policy & Senior Fellow at the Stanford Institute for Economic Policy Research
Current Research and Scholarly InterestsSocial and environmental determinants of health; role of workplace physical environment and work organization as causes of chronic disease and disability
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Francisco De La Vega
Adjunct Professor, Biomedical Data Science
BioProf. Francisco M. De La Vega is a geneticist and computational biologist with interests in cancer, population, and clinical genomics, and with extensive experience in the life sciences industry. He is a Distinguished Scientific Fellow and Vice President of Bioinformatics and at TOMA Biosciences, a privately held start-up company commercializing a technology for precision oncology derived from inventions at Stanford. Francisco is also Adjunct Professor in the Department of Biomedical Data science of the Stanford School of Medicine, a Director of the International Society of Computational Biology, and is or has been a member of the Steering Committee of the NIST-led Genome-in-a-Bottle consortium, the PanCancer Analysis of Whole Genomes project of the ICGC, and the Steering Committee of the 1000 Genomes Project. He has more recently contributed to start-up companies in the life sciences area in positions such as CSO (Annai Systems) and VP of Genomics (Real Time Genetics, Omicia). Previously, he spent over 13 yeas at Applied Biosystems (later Life Technologies and currently Thermo-Fisher), where he played a pivotal role in the development of several successful genetic analysis technologies. For this, he was inducted in 2009 to the Innovation & Invention Society of Life Technologies, a program that recognized the company’s most elite inventors, and in 2008 was a co-recipient of the Bio-IT World Best Practices Award in Basic Research.
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Manisha Desai
Professor (Research) of Medicine (Biomedical Informatics), of Biomedical Data Science and, by courtesy, of Health Research and Policy
Current Research and Scholarly InterestsDr. Desai is the Director of the Quantitative Sciences Unit. She is interested in the application of biostatistical methods to all areas of medicine including oncology, nephrology, and endocrinology. She works on methods for the analysis of epidemiologic studies, clinical trials, and studies with missing observations.
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Bradley Efron
Max H. Stein Professor and Professor of Statistics and of Biomedical Data Science
Current Research and Scholarly InterestsResearch Interests:
BOOTSTRAP
BIOSTATISTICS
BAYESIAN STATISTICS -
Andrew Gentles
Assistant Professor (Research) of Medicine (Biomedical Informatics) and, by courtesy, of Biomedical Data Science
Current Research and Scholarly InterestsComputational systems biology of human disease. Particular focus on integration of high-throughput datasets with each other, and with phenotypic information and clinical outcomes.
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Olivier Gevaert
Assistant Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
Current Research and Scholarly InterestsMy lab focuses on biomedical data fusion: the development of machine learning methods for biomedical decision support using multi-scale biomedical data. We primarily use methods based on regularized linear regression to accomplish this. We primarily focus on applications in oncology and neuroscience.
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Trevor Hastie
John A. Overdeck Professor, Professor of Statistics and of Biomedical Data Sciences
Current Research and Scholarly InterestsFlexible statistical modeling for prediction and representation of data arising in biology, medicine, science or industry. Statistical and machine learning tools have gained importance over the years. Part of Hastie's work has been to bridge the gap between traditional statistical methodology and the achievements made in machine learning.
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Tina Hernandez-Boussard
Associate Professor (Research) of Medicine (Biomedical Informatics), of Biomedical Data Science and of Surgery
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.
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Alexander Ioannidis
Postdoctoral Research Fellow, Biomedical Data Sciences
BioAlexander graduated from Harvard in Chemistry and Physics and earned an M.Phil in Computational Biology and Diploma in Greek from the University of Cambridge. He has a Ph.D. in Computational and Mathematical Engineering from Stanford, where he teaches machine learning and data science. Prior to Stanford, he worked in superconducting computing research at Northrop Grumman. As a current research fellow in the Stanford School of Medicine (Department of Biomedical Data Science), his work focuses on applying computational methods to problems in human genetics and population history.
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I work on methods for creating synthetic genomic data for DNA privacy, as well as on novel algorithm design (particularly ancestry related) for several large-scale genomic studies that aim at understanding genetic causes of disease.
I also focus on projects at the intersection of computational history and population genetics, including work with native communities. As the grandson of Cappadocians expelled from their homeland, I try to engage with the complex sentiments of displaced native peoples in these projects. Pain over the disruption of community heritage and over dispossession from traditional sites often remains raw. If engagement with descendant communities is lacking, research into our past can often feel like a continuation, even a legitimation, of our dispossession. Combined alongside a dialogue with indigenous peoples, however, genetics can play a small role in helping us to reclaim ancestral stories and dispersed community connections. I hope my work in this area plays a constructive role in that process.
As written by the poet Rumi in the language of the Cappadocians (Rum),
پیمی تیِ پَاثیِسْ پیمی تی خاسِس
“Tell me what happened to you, tell me what you have lost.”
[Rumi; Konya ms 67; translit. πε με τι έπαθες, πε με τι έχασες] -
John P.A. Ioannidis
C. F. Rehnborg Professor in Disease Prevention in the School of Medicine, Professor of Medicine, of Health Research and Policy (Epidemiology) and by courtesy, of Statistics and of Biomedical Data Science
Current Research and Scholarly InterestsMeta-research
Evidence-based medicine
Clinical and molecular epidemiology
Human genome epidemiology
Research design
Reporting of research
Empirical evaluation of bias in research
Randomized trials
Statistical methods and modeling
Meta-analysis and large-scale evidence
Prognosis, predictive, personalized, precision medicine and health
Sociology of science -
Iain Johnstone
Marjorie Mhoon Fair Professor in Quantitative Science and Professor of Statistics and of Biomedical Data Sciences
Current Research and Scholarly InterestsEmpirical bias/shrinkage estimation; non-parametric, smoothing; statistical inverse problems.
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Teri Klein
Professor (Research) of Biomedical Data Science and of Medicine (BMIR)
Current Research and Scholarly InterestsCo-founder, Pacific Symposium on Biocomputing
NIEHS, Site Visit Reviewer
NIH, Study Section Reviewer -
Tze Leung Lai
Ray Lyman Wilbur Professor and Professor, by courtesy, of Biomedical Data Science
Current Research and Scholarly InterestsResearch interests include clinical trial design, cancer biostatistics, survival analysis, adaptation and sequential experimentation, change-point detection and segmentation, stochastic optimization, time series and inference on stochastic processes, hidden Markov models and genomic applications.
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Philip W. Lavori
Professor of Biomedical Data Science, Emeritus
Current Research and Scholarly InterestsBiostatistics, clinical trials, longitudinal studies, casual inference from observational studies, genetic tissue banking, informed consent. Trial designs for dynamic (adaptive) treatment regimes, psychiatric research, cancer.
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Laura C. Lazzeroni, Ph.D.
Professor (Research) of Psychiatry and Behavioral Sciences and of Biomedical Data Science
Current Research and Scholarly InterestsStatistics/Data Science. I develop & apply models, methods & algorithms for complex data in medical science & biology. I am also interested in the interplay between fundamental statistical properties (e.g. variability, bias, p-values) & how scientists actually use & interpret data. My work in statistical genetics includes: the invention of Plaid bi-clustering for gene expression data; methods for twin, association, & family studies; multiple testing & estimation for high dimensional arrays.
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Ying Lu
Professor of Biomedical Data Science and, by courtesy, of Radiology (Molecular Imaging) and of Health Research and Policy (Epidemiology)
Current Research and Scholarly InterestsBiostatistics, clinical trials, statistical evaluation of medical diagnostic tests, radiology, osteoporosis, meta-analysis, medical decisoin making
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Mark Musen
Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
Current Research and Scholarly InterestsThere are great opportunities for new discoveries and for ensuring the reproducibility of scientific results when experimental data—and descriptions of the methods used to generate and analyze those data—are available in public repositories. Our laboratory is studying the development of new methods to aid investigators in creating more comprehensive online descriptions both of their data and of their experiments that can be processed both by other scientists and by computers.
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Richard A. Olshen
Professor of Biomedical Data Science, Emeritus
Current Research and Scholarly InterestsMy research is in statistics and their applications to medicine and biology. Many efforts have concerned tree-structured algorithms for classification, regression, survival analysis, and clustering.
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Julia Palacios
Assistant Professor of Statistics and of Biomedical Data Science
BioDr. Palacios seek to provide statistically rigorous answers to concrete, data driven questions in evolutionary genetics and public health . My research involves probabilistic modeling of evolutionary forces and the development of computationally tractable methods that are applicable to big data problems. Past and current research relies heavily on the theory of stochastic processes, Bayesian nonparametrics and recent developments in machine learning and statistical theory for big data.
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Maximilian Pfau
Visiting Postdoctoral Scholar, Biomedical Data Science
BioPhysician-scientist who studies retinal diseases such as age-related macular degeneration with a focus on multimodal imaging and psychophysics.
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Sylvia K. Plevritis, PhD
Professor of Biomedical Data Science and of Radiology (Integrative Biomedical Imaging Informatics at Stanford)
Current Research and Scholarly InterestsMy research program focuses on computational modeling of cancer biology and cancer outcomes. My laboratory develops stochastic models of the natural history of cancer based on clinical research data. We estimate population-level outcomes under differing screening and treatment interventions. We also analyze genomic and proteomic cancer data in order to identify molecular networks that are perturbed in cancer initiation and progression and relate these perturbations to patient outcomes.
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Johannes Reiter
Assistant Professor of Radiology (Canary Center) and, by courtesy, of Biomedical Data Science
Current Research and Scholarly InterestsMy research focuses on the stochastic biological processes underlying cancer evolution with the goal to improve diagnosis, prognosis, and treatment of tumors. I develop computational methods and design mathematical models to generate novel hypotheses and explain observations on a mechanistic level.
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David Rogosa
Associate Professor of Education and, by courtesy, of Biomedical Data Science and of Statistics
Current Research and Scholarly InterestsStatistical issues in educational assessment; analysis of longitudinal data.
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Daniel Rubin
Professor of Biomedical Data Science and of Radiology (Integrative Biomedical Imaging Informatics at Stanford), of Medicine (Biomedical Informatics Research) and, by courtesy, of Ophthalmology and of Computer Science
Current Research and Scholarly InterestsMy research interest is imaging informatics--ways computers can work with images to leverage their rich information content and to help physicians use images to guide personalized care. Work in our lab thus lies at the intersection of biomedical informatics and imaging science.
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Chiara Sabatti
Professor of Biomedical Data Science and of Statistics
Current Research and Scholarly InterestsStatistical models and reasoning are key to our understanding of the genetic basis of human traits. Modern high-throughput technology presents us with new opportunities and challenges. We develop statistical approaches for high dimensional data in the attempt of improving our understanding of the molecular basis of health related traits.
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Julia Salzman
Assistant Professor of Biochemistry and of Biomedical Data Science
Current Research and Scholarly InterestsCircular RNA regulation and function; computational and experimental approaches
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Nigam H. Shah, MBBS, PhD
Associate Professor of Medicine (Biomedical Informatics) and of Biomedical Data Science
Current Research and Scholarly InterestsMy research group studies ontology-based approaches to annotate, index, integrate and analyze unstructured information available in biomedicine for the purpose of enabling data-driven analytics in medicine and health care.
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Laurel Stell
Research Engineer, Biomedical Data Science
Current Role at StanfordPrimarily collaborating with VA researchers on GWAS using MVP data. Also providing statistical support to some Stanford clinicians conducting investigational research.
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Jaap Suermondt, PhD
Executive Director, Biomedical Informatics Training Program, Biomedical Data Science
BioI’m the Executive Director of Stanford’s Biomedical Informatics Program, working with MS and PhD students who are training to be the next generation of researchers and leaders in Biomedical Data Science. I hold a BS, MS, and PhD from Stanford University, and am an elected Fellow of the American College of Medical Informatics
Before coming back to Stanford, I spent most of my career in industry, as a researcher, manager, and executive. Outside of Stanford, I’m active in the Silicon Valley ecosystem as a mentor to startup founders and strategic advisor -- all this obviously while being compliant with Stanford's policies and conflict of interest and commitment constraints. -
Suzanne Tamang
Instructor, Biomedical Data Science
BioSuzanne Tamang is based at the Center for Population Health Sciences She received her Ph.D. in Computer Science from the City University of New York and completed her postdoctoral training at the Stanford's Center for Biomedical Bioinformatics.
At Stanford, Suzanne's collaborations span the Alcoa Research Consortium, the Clinical Excellence Research Center and the Stanford Cancer Institute. She is also affiliated with the Department of Rheumatology at UCSF. -
John S. Tamaresis, PhD, MS
Biostatistician, Biomedical Data Science
BioDr. Tamaresis joined the Stanford University School of Medicine in Summer 2012. He earned the Ph.D. in Applied Mathematics from the University of California, Davis and received the M.S. in Statistics from the California State University, East Bay. He has conducted research in computational biology as a postdoctoral scholar at the University of California, Merced and as a biostatistician at the University of California, San Francisco.
As a statistician, Dr. Tamaresis has developed and validated a highly accurate statistical biomarker classifier for gynecologic disease by applying multivariate techniques to a large genomic data set. His statistical consultations have produced data analyses for published research studies and analysis plans for novel research proposals in grant applications. As an applied mathematician, Dr. Tamaresis has created computational biology models and devised numerical methods for their solution. He devised a probabilistic model to study how the number of binding sites on a novel therapeutic molecule affected contact time with cancer cells to advise medical researchers about its design. For his doctoral dissertation, he created and analyzed the first mathematical system model for a mechanosensory network in vascular endothelial cells to investigate the initial stage of atherosclerotic disease. -
Lu Tian
Professor of Biomedical Data Science and, by courtesy, of Statistics
Current Research and Scholarly InterestsMy research interest includes
(1) Survival Analysis and Semiparametric Modeling;
(2) Resampling Method ;
(3) Meta Analysis ;
(4) High Dimensional Data Analysis;
(5) Precision Medicine for Disease Diagnosis, Prognosis and Treatment. -
Robert Tibshirani
Professor of Biomedical Data Science and of Statistics
Current Research and Scholarly InterestsMy research is in applied statistics and biostatistics. I specialize in computer-intensive methods for regression and classification, bootstrap, cross-validation and statistical inference, and signal and image analysis for medical diagnosis.
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Dennis Wall
Associate Professor of Pediatrics (Systems Medicine), of Biomedical Data Science and, by courtesy, of Psychiatry and Behavioral Sciences
Current Research and Scholarly InterestsSystems biology for design of clinical solutions that detect and treat disease
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Wing Hung Wong
Stephen R. Pierce Family Goldman Sachs Professor in Science and Human Health and Professor of Biomedical Data Science
Current Research and Scholarly InterestsCurrent interest centers on the application of statistics to biology and medicine. We are particularly interested in questions concerning gene regulation, genome interpretation and their applications to precision medicine.
