Affiliated Faculty
Francisco De La Vega, Adjunct Professor
delavefm@stanford.edu
Dr. De La Vega is a geneticist and computational biologist with interests in cancer, population, and clinical genomics, and extensive experience in the life sciences industry. Besides being an Adjunct Professor of Biomedical Data Science at Stanford, he is also Distinguished Scientific Fellow and Vice President of Bioinformatics and TOMA Biosciences, a privately held start-up company commercializing a technology for precision oncology derived from inventions at Stanford. He is 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 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 years 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.
Andrew Gentles, Courtesy Professor
andrewg@stanford.edu
Dr Gentles is an Assistant Professor in the Department of Medicine (Biomedical Informatics Research Institute). Originally, he trained as a theoretical particle physicist in the UK. His more recent research interests are in computational systems biology, particularly the integration and analysis of different types of data, such as genomic data and clinical outcomes.
Much of his recent work has been concerned with the influence of immune infiltrates on outcome in various cancers, and the impact of sub-populations such as cancer stem cells. He uses statistical and machine learning methods for analyzing genomic data, and extracting insights from large molecular networks by connecting them with phenotypes such as response to treatment and survival outcomes. Dr Gentles confesses to still occasionally perusing the latest news in quantum field theory.
John Ioannidis, Courtesy Professor
jioannid@stanford.edu
John P.A. Ioannidis holds the C.F. Rehnborg Chair in Disease Prevention. He is: Professor of Medicine, of Health Research and Policy, and (by courtesy) of Biomedical Data Science at the School of Medicine; Professor (by courtesy) of Statistics at the School of Humanities and Sciences; co-Director of the Meta-Research Innovation Center at Stanford (METRICS); and Director of the PhD program in Epidemiology and Clinical Research at Stanford. He is interested in meta-research (the evaluation of scientific practices and how to improve them), large-scale evidence, and research methods, and strongly biased in favor of health and wellness rather than disease and medicine. He is more excited about the Methods sections rather than the Results sections of scientific articles.
Mohit Kaushal, Adjunct Professor
mkaushal@stanford.edu
Dr. Kaushal has had an extensive career within investing, clinical medicine/academia and public policy. He is a lead investor and board member to numerous transformational companies, including Humedica (acquired by Optum Health), Rxante (acq. by Millennium), Change Healthcare (acq. by Emdeon), Gravie, Elation Health, CitiusTech, Oak Street Health and Universal American (NYSE: UAM). During his time in the Obama administration, he was a member of the White House Health IT task force; a cross agency team implementing the technology aspects of Health Reform. He also built and led the first dedicated health care team at the Federal Communications Commission. Dr. Kaushal continues to be active within public policy and is a Scholar in Residence at the newly created Duke Margolis Center for Health Policy. He was previously a Visiting Scholar at the Brookings Institution. He has been appointed to the FDASIA Workgroup of the Health IT Policy Committee and to the National Committee on Vital and Health Statistics, advising HHS on Data Access and Use. Kaushal is an ER physician, holds an MBA from Stanford and an MD with distinction from Imperial College of Science, Technology and Medicine, London.
Tze Leung Lai, Courtesy Professor
Tze.Lai@stanford.edu
Tze is Professor of Statistics and, by courtesy, of Health Research and Policy in the School of Medicine and of the Institute for Computational & Mathematical Engineering (ICME) in the School of Engineering. He is Director of the Financial and Risk Modeling Institute, Codirector of the Biostatistics Core of the Stanford Cancer Institute, and Codirector of the Center for Innovative Study Design at the Stanford School of Medicine. He has held regular and visiting faculty appointments at Columbia University, UC Berkeley, and Nankai University, and holds advisory positions with the University of Hong Kong, Peking University, Tsinghua University, the Chinese University of Hong Kong, Fudan University, the National
University of Singapore, and the Institute of Statistical Science at Academia Sinica.
David Rogosa, Courtesy Professor
rag@stanford.edu
David Rogosa is an applied statistician working in education, social science and life sciences research. He teaches in Stanford's School of Education, Department of Statistics, and Medical School. He is an Associate Professor in the School of Education, with courtesy appointments in the Department of Statistics and Department of
Biomedical Data Science. His research and teaching topics include: longitudinal research,
educational measurement, and causal inference from observational studies. Rogosa has served as a statistical consultant to many government agencies and research organizations including California's Department of Education, NIMH, and SRI International, and he is a past fellow in the Center for Advanced Study in the Behavioral Sciences.