School of Medicine
Showing 1-50 of 66 Results
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/
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.
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.
Senior Research Scientist, Biomedical Data Science
Current Role at StanfordPharmGKB Director
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
Postdoctoral Research Fellow, Biomedical Data Sciences
Resident in Dermatology
BioI am interested in bridging new technologies such as genomics and machine learning with clinical medicine. I am also interested in the use of Twitter for scientific communication and medical education. I am on Twitter: @RoxanaDaneshjou.
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.
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.
Max H. Stein Professor and Professor of Statistics and of Biomedical Data Science
Current Research and Scholarly InterestsResearch Interests:
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.
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.
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.
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.
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 and quantum computing 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 genomics and population genetics.
I work 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 history and population genetics, including work with native communities. As the grandson of Cappadocians expelled from their native land, I try to engage with the complex sentiments of displaced indigenous 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 dispossession. Combined alongside a dialogue with native communities, however, genetics can play a small role in helping to reclaim ancestral stories and dispersed ancestral connections. I hope our work in this area plays a constructive role in that process.
As written by the poet Rumi in the language of the Cappadocians (Rûm),
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
Clinical and molecular epidemiology
Human genome epidemiology
Reporting of research
Empirical evaluation of bias in research
Statistical methods and modeling
Meta-analysis and large-scale evidence
Prognosis, predictive, personalized, precision medicine and health
Sociology of science
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.
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.
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.
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.
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
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.
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.
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.
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.
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.
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.
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.
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.
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.
Assistant Professor of Biochemistry and of Biomedical Data Science
Current Research and Scholarly InterestsCircular RNA regulation and function; computational and experimental approaches