School of Medicine
Showing 1-19 of 19 Results
-
Michelle Whirl-Carrillo
Senior Research Scientist, Biomedical Data Science
Current Role at StanfordPharmGKB Director
www.pharmgkb.org -
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.
-
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.
-
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. -
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.
