School of Medicine
Showing 1-20 of 85 Results
-
Minhaj Nur Alam
Postdoctoral Research Fellow, Biomedical Data Sciences
BioI am a Postdoctoral Scientist at the Stanford Department of Biomedical Data Sciences, with a research focus on Medical AI/ML applications and quantitative image processing (Ophthalmology and Radiology). I have extensive experience in quantitative image biomarker development and incorporating machine learning algorithms for computer aided diagnosis/classification in Ophthalmology and Radiology. I hold a PhD in Bioengineering (CV/AI applications in Ophthalmology) from University of Illinois at Chicago.
-
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
On Partial Leave from 01/01/2021 To 06/30/2021Current 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.
-
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
-
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.
-
Michelle Whirl-Carrillo
Senior Research Scientist, Biomedical Data Science
Current Role at StanfordPharmGKB Director
www.pharmgkb.org -
Helio Costa
Instructor, Biomedical Data Science
BioHelio Costa, PhD, is a medical geneticist with expertise in oncology, medical genetics and genomics, computational biology, data science, software engineering, and product development. He is passionate about leveraging his interdisciplinary skillset to build and develop commercial-grade healthcare tools that aid in patient care and clinical decision support.
Dr. Costa's research focuses on developing, clinically validating, and implementing new medical diagnostic genetic tests and software for use at Stanford Health Care. His research group is also developing clinical algorithms using large-scale clinical laboratory datasets and patient electronic medical records to predict patient outcomes and aid in therapeutic clinical decision support.
He is a co-Investigator on the NIH-funded Clinical Genome Resource (ClinGen) Consortium, and leads the engineering and product management teams developing FDA-recognized medical software applications used by healthcare providers, researchers, and biotechnology companies to define the clinical relevance of genes and mutations identified in patients.
Dr. Costa 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 Medical Geneticist, and Assistant Lab Director for the Molecular Genetic Pathology Laboratory at Stanford Health Care.
Dr. Costa received his BS in Genetics from University of California at 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. -
Roxana Daneshjou
Clinical Scholar, Dermatology
Postdoctoral Research Fellow, Biomedical Data SciencesBioI 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 M. De La Vega
Adjunct Professor, Biomedical Data Science
BioProf. Francisco De La Vega is a geneticist, computational biologist and experienced technical executive of the life sciences industry, having spent over a decade at Applied Biosystems/Life Technologies developing several successful genetic analysis products, and more recently contributing to technology start-up companies focused on bringing genome sequencing into the clinic. He has participated in several breakthrough international projects such as the 1000 Genomes Project, the Genome-in-a-Bottle Consortium, and the International Cancer Genome Consortium. Francisco has co-authored more than 100 scientific publications, including papers in top journals such as Nature, Nature Genetics, Science, Genome Research and others, which have received over 20,000 citations. Currently he is Chief Scientific Officer and Senior Vice President of Research and Development at Fabric Genomics, an Oakland-based privately held company that develops an Artificial Intelligence-driven software-as- a-service platform for genomic interpretation and clinical reporting from genomes, exomes, and gene panels.
-
Manisha Desai (She/Her/Hers)
Professor (Research) of Medicine (Biomedical Informatics), of Biomedical Data Science and, by courtesy, of Epidemiology and Population Health
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.
