School of Medicine
Showing 1-50 of 127 Results
-
Shaimaa Bakr
Masters Student in Biomedical Data Science, admitted Autumn 2020
BioShaimaa is a graduate of the Ph.D. program, the Department of Electrical Engineering at Stanford and currently a postdoctoral researcher at the Gevaert lab at the Stanford Center for Biomedical Informatics Research (BMIR). Shaimaa is interested in developing multi-modal deep learning models using biomedical data with focus on genomic, radiology and histopathology data and applying these models to solve problems in cancer and other diseases. Prior to Stanford, she received her B.Sc. (Summa Cum Laude) from the American University in Cairo, where she studied Electronics Engineering and Computer Science. She obtained her MS degree in Electrical Engineering from Rensselaer Polytechnic Institute, working in the Cognitive and Immersive Systems lab, and advised by Professor Richard Radke.
-
Corinne Beck
Program Manager, Center for Cancer Systems Biology (CCSB), Biomedical Data Science
Current Role at StanfordProgram Manager
Stanford Center for Cancer Systems Biology (CCSB)
Plevritis Lab
Department of Biomedical Data Science (DBDS)
School of Medicine | Stanford University -
Daniel Bloch
Professor (Research) of Biomedical Data Science (BDS), Emeritus
BioI received my PhD. in Mathematical Statistics in 1967. I joined the research community at the Stanford University School of Medicine, Division of Immunology & Rheumatology, in 1984 as head statistician directing the biostatistics consulting and analytic support of the Arthritis Rheumatism Aging Medical Information System (ARAMIS) and Multipurpose Arthritis Center (MAC) grant-related research programs. In 1993 I was appointed Associate Professor with a joint appointment in the Departments of Medicine and of Health Research & Policy, and am currently Professor of Biostatistics at Stanford University, emeritus since 2007. My contributions to the statistics literature span numerous fields, including methods of sample size estimation, efficiency and bias of estimators, research methods for kappa statistics, non-parametric classification methods and methods of assessing multi-parameter endpoints. I have over 200 peer-reviewed publications. I have been directly involved with the development of numerous criteria rules for classification of diseases and with establishing guidelines for clinical trial research and in proposing responder criteria for osteoarthritis drugs. Since 1987, I have been a consultant on an ad hoc basis to pharmaceutical and biotechnical firms, including both start-up and established companies. I have extensive experience with devices, drugs and biologics and have participated in all aspects of applying statistics to implement investigational plans; e.g.: for protocol development, design of trials, database design. I’ve been a member of the FDA Statistical Advisors Panel, the statistical member on numerous data safety monitoring boards, and frequently represent companies at meetings with the FDA
-
Jiachen Cai
Postdoc, Biomedical Data Science
BioI am currently a postdoc in Prof. Barbara Engelhardt's lab at Stanford University and Gladstone Institutes, developing and applying statistical and computational tools for analyzing biomedical data. Prior to this position, I obtained a Ph.D. in Biostatistics from University of Cambridge in 2024 and a M.S. in Biostatistics from Yale University in 2021.
More information about my experience can be found via my LinkedIn profile: https://www.linkedin.com/in/jiachen-cai-872ab9191/. -
Michelle Whirl-Carrillo
Principal Investigator and Director, PharmGKB, Biomedical Data Science
Current Role at StanfordPrincipal Investigator and Director, PharmGKB
-
Francisco M. De La Vega
Adjunct Professor, Biomedical Data Science
BioFrancisco De La Vega is a distinguished geneticist and computational biologist, and an experienced technical executive, widely recognized for his expertise in clinical and population genomics, and bioinformatics. Currently serving as the Vice President of Hereditary Disease at Tempus Labs, Francisco is spearheading the development of comprehensive germline genetic tests and conducting innovative research into racial disparities in cancer leveraging Tempus’ multimodal Real-World Data. His work focuses on uncovering the connections between genetic ancestry and cancer genome mutational profiles that may help explain the differences in cancer incidence and outcomes across races and ethnicities. In addition to his role at Tempus Labs, Francisco is an Adjunct Professor in the Department of Biomedical Data Science at Stanford University School of Medicine and is a member of the Board of Directors of the International Society of Computational Biology, serving from 2022 to 2025.
Francisco teaches BIODS-235: "Best practices for developing data science software for clinical and healthcare applications" every Winter quarter. -
Li Gong
Scientific Data Curator 3, Biomedical Data Science
Current Role at StanfordI am a senior scientific curator at PharmGKB, and also serves as the program manager for the Stanford ClinGen team and coordinator for the ClinGen Pharmacogenomics Working Group.
-
Ryunosuke (Ryan) Goto
Ph.D. Student in Biomedical Data Science, admitted Autumn 2024
BioRyunosuke (Ryan) Goto is a PhD student in Biomedical Data Science and a Knight-Hennessy Scholar. Prior to Stanford, Ryan was a Chief Resident in Pediatrics at Nagano Children's Hospital and the University of Tokyo Hospital. He is interested in developing and applying statistical tools to investigate human disease and advance precision medicine. Ryan’s work has been published in The Lancet, JAMA Pediatrics, and Pediatrics, among other journals.
-
Kari Hanson
Lecturer, Biomedical Data Science
BioKari is a former technology executive with a passion for entrepreneurship, innovation, business strategy and making the world a better place. Having worked as a coach, investor, advisor, board member and CFO, she enjoys empowering students and entrepreneurs to thrive in life, the classroom and the marketplace.
-
Dina Hany
Postdoctoral Scholar, Biomedical Data Sciences
BioI am currently a postdoctoral researcher in the laboratory of Prof. Sylvia Plevritis, Department of Biomedical Data Sciences. My current work involves establishing drug testing platforms to evaluate tumor drug responses with respect to the tumor microenvironment and the its spatial organization. I hold a Ph.D. in Life Sciences (Pharmaceutical Sciences) from the University of Geneva, Switzerland, where I conducted research in Prof. Didier Picard's laboratory from 2017 to 2022. Prior to that, I earned a Master’s degree in Pharmacology and Experimental Therapeutics from Alexandria University, Egypt, and a Bachelor’s degree in Pharmacy with honors from Pharos University. My professional experience includes postdoctoral research in molecular pharmacology at UNIGE and a lecturer position in Pharmacotherapeutics and Cancer Biology at Pharos University. I have extensive teaching experience, supervising undergraduate and postgraduate courses, and have successfully guided master's thesis projects. My research has focused on endocrine resistance in breast cancer, utilizing CRISPR/Cas9 screens and exploring drug combinations, resulting in several relevant publications. I have presented my work at numerous conferences and received several awards, including the Ernst et Lucie Schmidheiny Fondation grant and the Ph.D. Booster prize from the faculty of medicine, Geneva, Switzerland. I am an active member of the Life Sciences Switzerland (LS2) and the European Association of Cancer Research (EACR).
-
Alexander Ioannidis
Affiliate, Biomedical Data Science
Adjunct Professor, Institute for Computational and Mathematical Engineering (ICME)BioDr. Alexander Ioannidis is an Adjunct Professor in Computational and Mathematical Engineering, where he teaches machine learning and data science, and is a researcher in the Department of Biomedical Data Science at Stanford Medical School. He earned his Ph.D. from Stanford University in Computational and Mathematical Engineering together with an M.S. in Management Science and Engineering (Optimization). He graduated summa cum laude from Harvard University in Chemistry and Physics and earned an M.Phil at the University of Cambridge from the Department of Applied Math and Theoretical Physics in Computational Biology. His research focuses on the design of algorithms and application of computational methods for problems in genomics, clinical data science, and precision health with a particular focus on underrepresented populations in Oceania and Latin America.
-
Asef Islam
Masters Student in Biomedical Data Science, admitted Winter 2023
Masters Student in Computer Science, admitted Autumn 2022Current Research and Scholarly InterestsAI in medicine and other fields, particularly ML and CV techniques
