FACULTY
Reza Abbasi-Asl, PhD
Assistant Professor of Neurology
Reza Abbasi-Asl, PhD
Dr. Abbasi-Asl is an Assistant Professor in the Department of Neurology and Director of Data Analytics and Visualization at Weill Institute for Neuroscience at UCSF. He completed his PhD and MSc in Electrical Engineering & Computer Sciences at UC Berkeley in 2018. His lab focuses on understanding the brain functions and related disorders using interpretable machine learning and statistical tools.
Computational health science interests:
Biological Modeling, Computational Neuroscience, Deep Machine Learning and Data Visualization
Nancy Adler, PhD
Professor and Vice-Chair of Psychiatry
Nancy Adler, PhD
Dr. Adler is a Professor and Vice-Chair of the Department of Psychiatry at UCSF and Director of the UCSF Center for Health & Community. As Chair of the MacArthur Foundation Network on socioeconomic status (SES) and Health, she coordinates research spanning social, psychological and biological mechanisms by which SES influences health. Another research focus is on health behaviors, investigating why individuals engage in health-damaging behaviors and how their understanding of risk affects their choices (primarily related to reproductive health).
Julia Adler-Milstein, PhD
Professor of Medicine
Julia Adler-Milstein, PhD
Dr. Adler-Milstein is an internationally-recognized expert on policy and management issues related to the use of IT in healthcare delivery. She obtained her bachelor’s degree in Human Biology from Stanford, and PhD in Health Policy from Harvard University. Her private-sector experience includes the Center for IT Leadership at Partners Healthcare in Boston and in the Health and Life Sciences Division of Accenture.
Ahmed Alaa, PhD
Assistant Professor of Computational Precision Health
Ahmed Alaa, PhD
Ahmed Alaa is an Assistant Professor of Computational Precision Health at UC Berkeley and UCSF, with affiliations in the EECS and Statistics departments at UC Berkeley. Previously, he was a postdoctoral associate at Massachusetts Institute of Technology and the Broad Institute of MIT and Harvard University. He obtained his Ph.D. in Electrical and Computer Engineering from UCLA, where he received the 2021 Edward K. Rice Outstanding Doctoral Student Award from the UCLA Samueli School of Engineering. His research interests include machine learning for healthcare, computer vision for medical imaging, clinical informatics, statistics, and causal inference.
Computational health science interests:
Clinical Research Informatics, Deep Machine Learning and Data Visualization
Steven Altschuler, PhD
Professor of Pharmaceutical Chemistry
Steven Altschuler, PhD
Dr. Altschuler has come to biology by way of pure mathematics, computer science and electrical engineering. In his joint lab with Dr. Lani Wu, they investigate fundamental questions about the origins and impact of cellular heterogeneity in cellular decision making, tissue development and homeostasis. Results from these studies are applied to investigate mechanisms of drug resistance, cancer evolution and new therapeutic strategies.
Computational health science interests:
Biological Modeling, Deep Machine Learning and Data Visualization
Rima Arnaout, MD
Associate Professor of Cardiology, Bakar Institute's Cardiology Clinical Lead
Rima Arnaout, MD
Dr. Arnaout is a physician-scientist with a background in genetics, clinical research and programming, and a practicing cardiologist board-certified in multi-modality cardiovascular imaging. She studied Biology and Bioengineering at MIT, and got her MD at Harvard. She did her Residency in Internal Medicine at MGH, and trained as a Cardiology Fellow at UCSF. Her research aims to improve the resolution and accuracy of cardiovascular phenotypes, thus leading to novel insights and therapies.
Computational health science interests:
Clinical Research Informatics, Deep Machine Learning and Data Visualization, Population Precision Medicine
Sourav Bandyopadhyay, PhD
Assistant Professor of Bioengineering & Therapeutic Sciences
Sourav Bandyopadhyay, PhD
Sourav did his PhD in Bioinformatics and Systems Biology with Trey Ideker at UC San Diego. In 2010, he obtained a prestigious faculty fellowship at UCSF designed to provide early independence to the world’s best scientists. His research focuses on the generation and network analysis of physical and genetic maps governing pathway deregulation in cancer. Sourav is committed to the development of systems biology techniques to understand pathway structure with a translational focus on the discovery of novel intervention points in cancer, using deep computational health sciences and pharmacogenomics approaches.
Computational health science interests:
Cancer and Precision Oncology, Deep Machine Learning and Data Visualization
Sergio Baranzini, PhD
Professor of Neurology
Sergio Baranzini, PhD
Sergio E. Baranzini studied at the University of Buenos Aires in Argentina, earning his degree in clinical biochemistry and later obtaining a PhD with honors in human molecular genetics. Dr. Baranzini came to UCSF as a postdoctoral scholar, and joined as faculty in the Department of Neurology in 2003. He is a member of the American Association of Immunologists, the American Society for Human Genetics and an elected member of the American Neurological Association. His research focuses on the genetics and molecular mechanisms underlying complex diseases; and work in his lab involves human genetics, immunology, molecular biology, bioinformatics and systems biology approaches.
Computational health science interests:
Biological Modeling, Computational Neuroscience, Very Large Data Molecular Measurements
Michael Blum, MD
Associate Vice Chancellor for Informatics; Clinical Professor of Medicine, Cardiology
Michael Blum, MD
Dr. Blum is the Associate Vice Chancellor for Informatics and a Clinical Professor of Medicine in the Division of Cardiology at UCSF. Dr. Blum applies his expertise in technology as the Chief Digital Transformation Officer and the Director of the Center for Digital Health Innovation at UCSF. He led the enterprise wide implementation of UCSF’s electronic health record system, APeX, and the development of the enterprise wide data warehouse. He has a special research interest in clinical decision support technology, social media and collaborative workspaces and their impact on the quality, effectiveness, and cost of care delivery.
Computational health science interests:
Clinical Research Informatics
Claire Brindis, DrPH
Professor of Pediatrics and OB/Gyn & Reproductive Sciences
Claire Brindis, DrPH
Dr. Brindis is a Professor in the Department of Pediatrics, Division of Adolescent Medicine and the Department of Obstetrics, Gynecology and Reproductive Sciences at UCSF. She is Director of the Philip R. Lee Institute for Health Policy Studies, Dr. Brindis is Executive Director of NAHIC, Associate Director of the Public Policy Analysis & Education Center for Middle Childhood & Adolescent Health, and Director of the Bixby Center for Global Reproductive Health.
William Brown, III, PhD, DrPH
Assistant Professor of Prevention Science;
Bakar Institute's Director of Diversity, Equity, & Inclusion
William Brown, III, PhD, DrPH
Dr. Brown is an Assistant Professor at the UCSF School of Medicine in the Division of Prevention Science. He implements innovative biomedical informatics methods, creates research tools, and follows the principals of community-based participatory research to address health disparities among underserved communities, and to create a Learning Health System that is responsive to vulnerable populations, particularly those at risk for acquiring HIV/AIDS.
Computational health science interests:
Clinical Research Informatics
Atul Butte, MD, PhD
Bakar Institute Director;
Priscilla Chan & Mark Zuckerberg Distinguished Prof; Chief Data Scientist for UC Health
Atul Butte, MD, PhD
Atul Butte is the inaugural Director of BCHSI and is the Priscilla Chan and Mark Zuckerberg Distinguished Professor of Pediatrics, Bioengineering and Therapeutic Sciences, and Epidemiology and Biostatistics. He is also Chief Data Scientist for UC Health, representing all 6 University of California Academic Medical Centers. He has authored over 200 publications, with research repeatedly featured in popular media outlets. He was elected into the National Academy of Medicine, and has been recognized by the Obama Administration as an Open Science Champion of Change for promoting science through publicly available data. Dr. Butte is a principal investigator of several major programs including the California Initiative to Advance Precision Medicine, and ImmPort (NIAID clinical and molecular data repository).
Computational health science interests:
Cancer and Precision Oncology, Clinical Research Informatics, Computational Pharmacology, Very Large Data Molecular Measurements
Tony Capra, PhD
Associate Professor of Epidemiology & Biostatistics
Tony Capra, PhD
Dr. Capra received a PhD in computer science from Princeton University under the supervision of Mona Singh. He was a postdoc in the group of Katherine Pollard at the Gladstone Institutes and UCSF. As a postdoc, he developed comparative genomics algorithms that integrated genome-scale data to develop testable hypotheses about the function of non-coding regulatory elements and to study recent human evolution.
Computational health science interests:
Population Precision Medicine, Very Large Data Molecular Measurements
Shawn Douglas, PhD
Assistant Professor of Cellular & Molecular Pharmacology
Shawn Douglas, PhD
Shawn Douglas earned a B.S. in Computer Science at Yale in 2003, and then a Ph.D. in Biophysics at Harvard in 2009, working in the laboratories of William Shih and George Church. He stayed at Harvard as a Postdoctoral Fellow at the Wyss Institute for Biologically Inspired Engineering. He was named as one of Popular Science magazine’s “Brilliant 10”, and is supported by Burroughs Wellcome Foundation and Pew-Stewart Scholars Program for Cancer Research.
Computational health science interests:
Biological Modeling, Computational Pharmacology, Very Large Data Molecular Measurements
Jean Feng, PhD
Assistant Professor of Epidemiology and Biostatistics
Jean Feng, PhD
Dr. Feng is an Assistant Professor in the Department of Epidemiology and Biostatistics. She obtained a BS in Computer Science from Stanford University and a PhD in Biostatistics from the University of Washington under Noah Simon and Erick Matsen. Her current research interests are in developing reliable and interpretable machine-learning algorithms that aid clinical decision-making.
Computational health science interests:
Clinical Research Informatics, Deep Machine Learning and Data Visualization, Population Precision Medicine
Valy Fontil, MD, MAS
Assistant Professor of Medicine
Valy Fontil, MD, MAS
Dr. Fontil is an implementation scientist and primary care physician at UCSF in the Division of General Internal Medicine at Zuckerberg San Francisco General Hospital. He is an expert in developing and adopting digital health technology for chronic disease management across multiple clinical settings, including safety-net healthcare institutions. His work has focused on developing and scaling technology-enabled healthcare interventions and innovations, such as clinical decision support technology platforms, in real-world settings targeted to reduce cardiovascular risk in high-risk populations vulnerable to health disparities.
Computational health science interests:
Clinical Research Informatics, Population Precision Medicine
Gabriela K. Fragiadakis, PhD
Assistant Professor of Medicine
Gabriela K. Fragiadakis, PhD
Dr. Fragiadakis is an Assistant Professor in the Division of Rheumatology and Director of the Data Science CoLab. She obtained her PhD in Microbiology and Immunology and postdoctoral studies at Stanford University. Her lab focuses on systems-level immune organization using single-cell methods, including CyTOF and single-cell sequencing. She also leads the UCSF Data Library project, a web-based data sharing platform for projects with multimodal biological and clinical data.
Computational health science interests:
Biological Modeling, Deep Machine Learning and Data Visualization, Population Precision Medicine, Very Large Data Molecular Measurements
Stuart Gansky, MS, DrPH
Professor and Lee Hysan Chair of Oral Epidemiology
Stuart Gansky, MS, DrPH
Dr. Gansky is Professor and Lee Hysan Chair of Oral Epidemiology in the UCSF School of Dentistry. As a biostatistician, his research concentrates on oral health, health disparities research, applied statistical analyses and related methodological issues. He is currently Director (PI) of the UCSF Center to Address Disparities in Children’s Oral Health (CAN-DO), serves as Co-Director of the NIH-funded Coordinating Center to Help Reduce/Eliminate Oral Health Inequalities in Children, and is an Assistant Director of the UCSF CTSI Comprehensive Mentoring Program.
Computational health science interests:
Clinical Research Informatics, Population Precision Medicine
Jin Ge, MD, MBA
Assistant Professor of Medicine
Jin Ge, MD, MBA
Dr. Ge is a gastroenterologist and transplant hepatologist who cares for patients with liver diseases. He received his MD/MBA at the University of Pennsylvania before completing his internal medicine residency, and gastroenterology and advanced/transplant hepatology fellowships at UCSF. While at UCSF, he also completed a certificate program in advanced clinical research training, with a focus on data science. His research focuses on using clinical informatics, data science and artificial intelligence to improve the quality of care for patients with advanced liver diseases and awaiting transplant. He also currently serves as the GI/Liver Domain Team lead for the NIH sponsored National COVID Cohort Collaborative (N3C).
Computational health science interests:
Clinical Research Informatics, Deep Machine Learning and Data Visualization, Population Precision Medicine
Efstathios D. Gennatas, MBBS, PhD
Assistant Professor of Epidemiology & Biostatistics
Efstathios D. Gennatas, MBBS, PhD
Efstathios (Stathis) D. Gennatas, MBBS AICSM PhD, is an Assistant Professor in the Department of Epidemiology and Biostatistics, and a member of the Center for Intelligent Imaging at the University of California, San Francisco. He completed medical school at Imperial College London and doctoral training in Neuroscience at the University of Pennsylvania. His work includes applied data science in basic research, clinical predictive modeling, and the development of machine learning methods and software for biomedical data analysis. His overarching goal is to help make precision medicine a reality in a safe, fair, and efficient way through interdisciplinary collaboration and team science.
Computational health science interests:
Cancer and Precision Oncology, Clinical Research Informatics, Deep Machine Learning and Data Visualization, Population Precision Medicine
Maria Glymour, ScD, MS
Professor, Epidemiology & Biostatistics
Maria Glymour, ScD, MS
Dr. Glymour serves as the Director for the UCSF PhD program in Epidemiology and Translational Science. She co-leads the UCSF T32 training grant on Aging and Chronic Disease, which offers financial support for pre- and post-doctoral researchers.
Computational health science interests:
Clinical Research Informatics, Deep Machine Learning and Data Visualization
Hani Goodarzi, PhD
Assistant Professor of Biochemistry and Biophysics
Hani Goodarzi, PhD
Dr. Goodarzi obtained his PhD in quantitaive and computational biology from Princeton University. He later did his postdoctoral training in Cancer Systems Biology at Rockefeller University in New York. He came to UCSF in 2016 as an Assistant Professor in the Departments of Biochemistry and Biophysics, and Urology. He is a member of the New York Academy of Sciences and the American Association of Cancer Research. His research combines modern computational and experimental technologies to understand cancer progression at a molecular level, with the goal of developing novel strategies for studying, diagnosing, and ultimately treating cancer.
Computational health science interests:
Cancer and Precision Oncology, Very Large Data Molecular Measurements
Lea Grinberg, MD, PhD
Associate Professor at Memory and Aging Center
Lea Grinberg, MD, PhD
Dr. Grinberg is a neuropathologist specializing in brain aging and associated neurodegenerative disorders. She received her medical and doctorate degrees in São Paulo, Brazil. Currently, Dr. Grinberg is an Associate Professor at the UCSF Memory and Aging Center and leads an international initiative to develop a pipeline, using high-resolution histology, to improve and validate multimodal neuroimaging tools. She is has served as Chair of the HUPO Brain Proteome Project, and was the recipient of the UNESCO-L’Oréal Award For Women in Science as well as the John Douglas French Alzheimer Foundation Distinguished Research Scholar Award.
Computational health science interests:
Clinical Research Informatics, Computational Neuroscience, Deep Machine Learning and Data Visualization
Ryan Hernandez, PhD
Associate Professor of BioEngineering
Ryan Hernandez, PhD
Ryan studies patterns of genetic variation in modern day populations to gain insight into their evolutionary history. His focus is on the development of population genetic models that can best explain observed data. Most recently, he has been evaluating models of background selection under parameters that are realistic for humans. Ryan’s scientific approach tends to be highly computational, often involving a thorough analysis of detailed simulations.
Computational health science interests:
Very Large Data Molecular Measurements
Christopher Hess, MD, PhD
Alexander R. Margulis Distinguished Professor and Chair of Radiology
Christopher Hess, MD, PhD
Dr. Hess completed his PhD in Electrical Engineering and later his MD at the University of Illinois. He joined UCSF as a resident in Radiology, and during his training was one of the first class of NIH T-32 Radiology research fellows, chief resident and recipient of the department’s Elmer Ng Award for outstanding resident. He completed his Radiology residency in 2007 and went on to complete a Neuroradiology fellowship at UCSF in 2008. He joined the Neuroradiology Section faculty that same year. He became chief of Neuroradiology in 2015, until 2018 when he became Chair of the Department of Radiology and Biomedical Imaging.
Computational health science interests:
Computational Neuroscience, Deep Machine Learning and Data Visualization
A Jay Holmgren, PhD
Assistant Professor of Medicine
A Jay Holmgren, PhD
Dr. Holmgren is an Assistant Professor in the Department of Medicine and the Center for Clinical Informatics and Improvement Research (CLIIR). He earned his BA in History and Masters of Health Informatics from the University of Michigan and his PhD in Health Policy from Harvard University. Dr. Holmgren is an expert on the use of digital tools in health care delivery, and his research focuses on the impact of information technology on patients, clinicians, and health care organizations.
Computational health science interests:
Clinical Research Informatics
Julian Hong, MD, MS
Assistant Professor of Radiation Oncology
Julian Hong, MD, MS
Dr. Hong is a radiation oncologist and informatician. He serves as Director of Clinical Informatics in Radiation Oncology. His lab focuses on combining clinical domain knowledge with data science to analyze real world multi-modal data, develop actionable computational tools, and evaluate these advances in the clinic for personalized cancer care.
Computational health science interests:
Cancer and Precision Oncology, Clinical Research Informatics, Deep Machine Learning and Data Visualization, Population Precision Medicine
Yulin Hswen, ScD
Assistant Professor of Epidemiology and Biostatistics
Yulin Hswen, ScD
Dr. Hswen is an Assistant Professor in the Department of Epidemiology and Biostatistics and the Bakar Computational Health Institute at UCSF. Dr. Hswen graduated with a Doctoral Degree in social and computational epidemiology at Harvard University. Through the collection of unconventional and underground data from online social networks, Dr. Hswen seeks to captures unfiltered conversations to uncover the connections between social experiences and health. Dr. Hswen is the founder and Principal Investigator of Covidseeker.com a platform that captures geospatial temporal data from Smartphones to better study the risks between human mobility and infectious disease.
Computational health science interests:
Clinical Research Informatics, Deep Machine Learning and Data Visualization, Population Precision Medicine
Franklin Huang, MD, PhD
Assistant Professor of Medicine
Franklin Huang, MD, PhD
Dr. Huang has a background in molecular biology, genetics, and global health, with specific training and expertise in cancer in resource-limited settings. Dr. Franklin Huang is a physician-scientist and a member of the Genitourinary Oncology division at UCSF Health Sciences. He serve as a mentor to students and trainees who are interested in cancer disparities, genetics, and global oncology. He is also the co-founder of Global Oncology.
Computational health science interests:
Cancer and Precision Oncology
Ajay Jain, PhD
Professor Emeritus
Ajay Jain, PhD
Following a long period of applied research in defense applications and in speech understanding, Prof. Jain began a research career exclusively focused on issues in computational chemistry and computational biology. He has done foundational work in computer-aided drug design, and currently develops models for multitudes of human targets in order to help guide the design and selection of compounds during preclinical research. The Jain lab has active collaborations with both academic and industry partners; and are particularly interested in applications involving cancer.
Computational health science interests:
Biological Modeling, Computational Pharmacology
Fei Jiang, PhD
Assistant Professor of Biostatistics
Fei Jiang, PhD
Dr. Jiang is an assistant professor in biostatistics in the University of California, San Francisco. Her research interest lies in machine learning methods, high dimensional models, functional data analysis and their applications in analyzing neurological, image, genetics data, and in designing adaptive randomization clinical trials. Her efforts yield high quality statistical and computational publications, which focus on addressing practical problems in the medical domain.
Computational health science interests:
Computational Neuroscience, Deep Machine Learning and Data Visualization
Elsbeth Kalenderian, DDS, MPH, PhD
Professor and Chair of Preventive & Restorative Dental Sciences, School of Dentistry
Elsbeth Kalenderian, DDS, MPH, PhD
Elisabeth (Elsbeth) Kalenderian received her DDS from Rijks Universiteit Groningen, The Netherlands. She came to Boston University as a Fulbright Scholar and completed an internship and residency in oral and maxillofacial surgery. She spent several years at Harvard University, receiving a Masters degree in Public Health and serving at the Harvard School of Dental Medicine as assistant dean for clinical affairs, associate professor and Chair of the Department of Oral Health Policy and Epidemiology. She obtained her PhD from the University of Amsterdam by leading a project to develop foundational diagnostic terminology for use in electronic dental health records; and she continues to lead efforts to improve these systems both for enhanced patient care and meaningful use.
Computational health science interests:
Clinical Research Informatics
Michael Keiser, PhD
Assistant Professor of Pharm Chem, BioEngineering & Therapeutic Sciences
Michael Keiser, PhD
As an NSF Fellow, Dr. Keiser has a PhD in bioinformatics from UCSF, where he developed techniques, such as the Similarity Ensemble Approach, to relate drugs and proteins based on the statistical similarity of their ligands. Dr. Keiser also holds BSc, BA and MA degrees from Stanford. He cofounded a startup that brings these methods to pharmaceutical companies and to the US FDA. The Keiser lab investigates forward polypharmacology for complex diseases and the prediction of drug off-target activities, combining machine learning and chemical biology methods to investigate how small molecules perturb entire protein networks to achieve their therapeutic effects. In classical pharmacology, each drug strikes a single note (“one drug hits one target to treat one disease”). The Keiser group is tracing out molecular music – new and useful therapeutic chords to treat neurodegenerative diseases.
Computational health science interests:
Computational Pharmacology, Deep Machine Learning and Data Visualization
Kord Kober, PhD
Associate Professor of Physiological Nursing
Kord Kober, PhD
Dr. Kober received his doctoral degree in molecular evolutionary biology from the University of California, Santa Cruz; and worked on the UCSC Cancer Genome Browser. He Co-Directs the WIHS Genomics group as well as the UCSF School of Nursing Genomics Lab, which operates a large biobank supporting biospecimens for research.
Computational health science interests:
Clinical Research Informatics, Very Large Data Molecular Measurements
Aaron Kornblith, MD
Associate Professor of Emergency Medicine & Pediatrics
Aaron Kornblith, MD
Dr. Kornblith is a physician-scientist and Associate Professor of Emergency Medicine and Pediatrics. He completed his training at UCSF and is a practicing general and pediatric emergency physician at Zuckerberg San Francisco General and UCSF Benioff Children’s Hospitals. Dr. Kornblith’s research program is focused on using reliable, reproducible, and trustworthy data science practices to improve the diagnostic evaluation of sick and injured child through advanced data analytics and novel hardware design.
Computational health science interests:
Deep Machine Learning and Data Visualization
Peder Larson, PhD
Associate Professor of Radiology and Biomedical Imaging
Peder Larson, PhD
Peder Larson is an Associate Professor in Residence and a Principal Investigator in the Department of Radiology and Biomedical Imaging at UCSF. Dr. Larson’s research program is primarily centered around developing new MRI scanning and reconstruction technology for improved clinical outcomes. Dr. Larson is an active member of International Society for Magnetic Resonance in Medicine, the Institute for Electrical and Electronics Engineering, the UC Berkeley and UCSF Graduate Group in Bioengineering, and the California Institute for Quantitative Biosciences.
Computational health science interests:
Deep Machine Learning and Data Visualization
Ann Lazar, PhD
Associate Professor of Biostatistics
Ann Lazar, PhD
Dr. Lazar received her PhD in Biostatistics from the University of Colorado Denver School of Public Health, Masters of Science in Biostatistics from the University of Michigan School of Public Health and Bachelors of Science from the University of California Berkeley. She was a recipient of the Ruth L. Kirschstein National Research Fellowship Award while she was post-doctoral fellow in Biostatistics and Data Science at the Harvard School of Public Health and Dana Farber Cancer Institute. She received training in oral health disparities via a NIH P30 grant after joining the faculty at UCSF.
Computational health science interests:
Clinical Research Informatics, Population Precision Medicine
Jingjing Li, PhD
Assistant Professor of Neurology
Jingjing Li, PhD
Dr. Li’s predoctoral training was in engineering and machine learning, and later received his PhD in Molecular Genetics from the University of Toronto. He did his postdoc research at Stanford Genetics as a Banting Fellow, and later received training in clinical research at Stanford Pediatrics. As a faculty member at UCSF, his research aims to innovate our analytical frameworks for large-scale disease genome analysis.
Computational health science interests:
Biological Modeling, Cancer and Precision Oncology, Computational Neuroscience, Deep Machine Learning and Data Visualization, Population Precision Medicine, Very Large Data Molecular Measurements
Janine Lupo, PhD
Associate Professor in Radiology and Biomedical Imaging
Janine Lupo, PhD
Dr. Lupo received her Bachelor’s degree in Engineering in 2001 from the University of Pennsylvania, and PhD in Bioengineering from UCSF and UC Berkeley in 2006. She is an Associate Professor in Radiology and Biomedical Imaging, and her research is carried out at the Surbeck Laboratory for Advanced Imaging.
Computational health science interests:
Clinical Research Informatics, Deep Machine Learning and Data Visualization
Courtney Lyles, PhD
Associate Professor of Medicine, Epidemiology, and Biostatistics
Courtney Lyles, PhD
Dr. Lyles is a health services researcher who focuses on digital health interventions conducted in under-resourced healthcare settings. This includes developing new technologies, such as machine learning algorithms and mobile apps, as well as broader efforts to spread and sustain evidence-based innovation solutions at a population level.
Computational health science interests:
Clinical Research Informatics, Population Precision Medicine
Sharmila Majumdar, PhD
Professor and the Vice Chair of Research in Radiology
Sharmila Majumdar, PhD
Dr. Majumdar is a Professor and the Vice Chair of Research in the Department of Radiology and Biomedical Imaging and Professor in the Departments of Bioengineering and Therapeutic Sciences, and Orthopedic Surgery at UCSF and Bioengineering at UC Berkeley. She obtained her PhD degree in Engineering and Applied Science from Yale University in 1987, where she stayed as a post-doctoral researcher and Assistant Professor until 1989, when she joined UCSF. She is a recognized expert in the area of imaging, and fellow of the American Institute of Medical and Biological Engineers and the International Society of Magnetic Resonance in Medicine (ISMRM), and recipient of the Gold Medal from ISMRM.
Computational health science interests:
Clinical Research Informatics, Deep Machine Learning and Data Visualization
Sara Murray, MD
Associate Professor of Medicine
Sara Murray, MD
Dr. Murray is an Associate Professor of Medicine in the Division of Hospital Medicine at the University of California, San Francisco (UCSF), and serves as the Medical Director of Clinical Informatics for UCSF Health. She works with the clinical systems teams at UCSF to optimize the current electronic health record (EHR) infrastructure and design novel informatics solutions for the medical center.
Computational health science interests:
Clinical Research Informatics
Srikantan Nagarajan, PhD
Professor in Residence of Radiology and Biomedical Imaging
Srikantan Nagarajan, PhD
Dr. Nagarajan is a Professor in Residence, Director of the Biomagnetic Imaging Laboratory, in the Department of Radiology and Biomedical Imaging at the University of California, San Francisco. He has joint appointments in the Department of Bioengineering and Therapeutic Sciences and in the Department of Otolaryngology, Head and Neck Surgery at UCSF. He is an active member in the UCB-UCSF Joint Graduate Program in Bioengineering and has served on the Executive Committee.
Computational health science interests:
Clinical Research Informatics, Computational Neuroscience, Deep Machine Learning and Data Visualization
Vasilis Ntranos, PhD
Assistant Professor of Epidemiology & Biostatistics
Vasilis Ntranos, PhD
Vasilis Ntranos obtained his PhD in Electrical Engineering from USC in 2015. After his graduate studies, Vasilis completed his postdoctoral training with Prof. Lior Pachter and Prof. David Tse in the Electrical Engineering & Computer Science Dept. at UC Berkeley (2015-2018), the Electrical Engineering Dept. at Stanford University (2015-2019), and the Biology and Biological Engineering Department at Caltech (2018-2019). Vasilis joined UCSF in November 2019, where he is currently an Assistant Professor in the Dept. of Epidemiology & Biostatistics, and the Diabetes Center. Vasilis’ main research interests are in computational methods development at the intersection of information theory, genomics, and machine learning, with a primary focus on single cell biology.
Computational health science interests:
Deep Machine Learning and Data Visualization, Population Precision Medicine, Very Large Data Molecular Measurements
Adam B. Olshen, PhD
Professor of Epidemiology and Biostatistics
Adam B. Olshen, PhD
Dr. Olshen is a professor in the Bioinformatics Division of the Department of Epidemiology and Biostatistics and Director of the Computation Biology and Informatics (CBI) Core in the Helen Diller Family Comprehensive Cancer Center at UCSF. His main research interest is statistical genomics in the context of cancer. His work includes developing tools for the analysis of genomic data and identifying biomarkers based on genomic and other types of data. He received a PhD in Biostatistics from the University of Washington and was previously faculty at the Memorial Sloan-Kettering Cancer Center.
Computational health science interests:
Cancer and Precision Oncology, Deep Machine Learning and Data Visualization, Very Large Data Molecular Measurements
Thomas A. Peterson, PhD
Assistant Professor of Orthopaedic Surgery
Thomas A. Peterson, PhD
Dr. Peterson works in close coordination with clinical experts to advance computational health sciences by leveraging advanced statistical, machine learning, and AI techniques on both prospective (RCT) and retrospective (EHR) datasets. As the director of the Analytics Core for UCSF REACH and the director for the Laboratory for Digital and Computational Health Science, Dr. Peterson specializes in techniques for studying and creating tools from a datasets of varying sizes, data modalities, and complexity.
Computational health science interests:
Clinical Research Informatics, Deep Machine Learning and Data Visualization, Population Precision Medicine
Kathryn Phillips, PhD
Professor of Health Economics & Health Services Research; Founding Director of TRANSPERS
Kathryn Phillips, PhD
Kathryn A. Phillips is an expert on the economic and reimbursement issues relevant to the translation of new technologies – particularly personalized/precision medicine – into clinical care and health policy.
Computational health science interests:
Cancer and Precision Oncology, Population Precision Medicine
Romain Pirrachio, MD, PhD
Professor of Anesthesia and Critical Care Medicine
Romain Pirrachio, MD, PhD
Dr. Pirrachio obtained his MD from Université Paris Diderot with a specialization in Anesthesiology and Critical Care. He received an MS, MPH, and PhD in Medical Research Methodology and Biostatistics. He was a postdoctoral fellow in the School of Public Health at UC Berkeley. He served as Chair for the Department of Anesthesia and Critical Care at European Hospital Geroges Pompidou and a researcher in Biostatistics at the INSERM U-1153 unit. He is currently a UCSF Professor, Chief of Anesthesia and Perioperative Care at ZSFGH, Vice Chair for the Department of Anesthesia and Perioperative Care at UCSF and Affiliate to the Division of Biostatistics at UC Berkeley. He is the co-founder of the ACTERREA research group.
Computational health science interests:
Clinical Research Informatics
Katherine S. Pollard, PhD
Professor of Biostatistics;
Senior Investigator at Gladstone Institutes
Katherine S. Pollard, PhD
Katherine received her PhD and MA in Biostatistics from UC Berkeley under the supervision of Mark van der Laan. Her research there included developing computationally intensive statistical methods for analysis of microarray data, with applications in cancer biology. She then did a postdoc with Sandrine Dudoit. Katherine developed Bioconductor open source packages for clustering and multiple hypothesis testing. In 2003, she began a comparative genomics NIH Postdoctoral Fellowship with David Haussler and Todd Lowe at UC Santa Cruz. She was part of the consortium that published the sequence of the Chimpanzee Genome, and identified the fastest evolving regions in the human genome. In 2005, Katherine joined the faculty at the UC Davis Genome Center and Department of Statistics. She moved to UCSF in 2008.
Computational health science interests:
Very Large Data Molecular Measurements
Ashish Raj, PhD
Professor of Radiology
Ashish Raj, PhD
Dr. Raj earned his Bachelor’s in Electrical Engineering from the University of Auckland, and later his PhD in Electrical and Computer Engineering from Cornell. He has extensive experience in computer vision, signal processing, graph theory, medical imaging and informatics. He works with teams of basic and clinical scientists to find innovative ways to apply computation and algorithms to biomedical applications.
Computational health science interests:
Computational Neuroscience, Deep Machine Learning and Data Visualization
Vijay Ramani, PhD
Assistant Professional Researcher of Biochemistry & Biophysics
Vijay Ramani, PhD
Dr. Ramani earned a BSE in Chemical Engineering at Princeton University, with minors in Quantitative & Computational Biology, and Engineering Biology. Studying an Integrated Science Curriculum, he was motivated to pursue research in quantitative molecular biology. He spent time at Sangamo Therapeutics as a Computational Biologist developing high-throughput sequencing assays. He completed a PhD in Genome Sciences at the University of Washington, where he developed new molecular technologies to study biomolecular phenomena at scale and learned to apply novel bulk- and single-cell sequencing technologies. As a Sandler Fellow, he is developing an independent research program at UCSF.
Computational health science interests:
Biological Modeling, Very Large Data Molecular Measurements
Kate Rankin, PhD
Professor of Neurology
Kate Rankin, PhD
Dr. Rankin is a Professor in Residence in the Memory and Aging division of the UCSF Department of Neurology. She trained at Yale, Fuller, and UCSF, obtaining a PhD in Clinical Psychology with a specialization in Neuropsychology. At the MAC she investigates the quantitative neurology of human socioemotional behavior, and develops informatics tools to accelerate clinical research and patient care approaches.
Computational health science interests:
Clinical Research Informatics, Computational Neuroscience, Deep Machine Learning and Data Visualization
Andreas M. Rauschecker, MD, PhD
Assistant Professor of Radiology
Andreas M. Rauschecker, MD, PhD
Andreas Rauschecker earned his MD and PhD at Stanford with a PhD in Neuroscience studying the organization of the human brain’s visual system using fMRI and DTI. He completed his Radiology Residency at the University of Pennsylvania, where he translated methods used in his PhD to clinical brain imaging. Dr. Rauschecker also completed an Informatics Fellowship at Penn. At UCSF he completed a T-32 sponsored research fellowship and his clinical neuroradiology fellowship. Dr. Rauschecker joined the UCSF faculty as a neuroradiologist in 2020. Dr. Rauschecker’s work focuses on developing and applying algorithms to analyze and quantify clinical brain MRI in the context of a variety of pathologies.
Computational health science interests:
Clinical Research Informatics, Computational Neuroscience, Deep Machine Learning and Data Visualization
Neil Risch, PhD
Professor of Epidemiology & Biostatistics
Neil Risch, PhD
Dr. Risch is a statistical geneticist and genetic epidemiologist, studying both clinical and population genetics. He has identified several genes for specific subtypes of idiopathic dystonia. Current research involves yet-unmapped variant forms. Dr. Risch has been in large collaborations on genetic susceptibility to hypertension, CV endpoints and MS (NHLBI Family Blood Pressure Program, Reynolds Foundation Heart, Health and Heredity study). He plans admixture studies in CV and metabolic phenotypes in African-American and Hispanic study subjects; relationship between genetic variation, race and ethnicity; and collaborative efforts with Drs. Kathleen Giacomini (UCSF) and Catherine Schaefer (Kaiser, Oakland) on pharmacogenetics of membrane transporters. Before coming to UCSF in 2004, Dr. Risch was professor of genetics at Stanford, with appointments in statistics, health research and policy. Previously, he was at Yale in biostatistics.
Benjamin Rosner, MD, PhD
Associate Clinical Professor
Benjamin Rosner, MD, PhD
Dr. Rosner holds a PhD in engineering and an MD from the University of Minnesota. He is a digital health expert, researcher, entrepreneur, and practicing hospital-based physician. He publishes and speaks extensively on the use of digital health technologies in improving the four pillars of the quadruple aim. Prior to CLIIR, Dr. Rosner was the founding Chief Medical Information Officer of HealthLoop, a prominent digital patient engagement company. He has worked closely with top leadership at CMS, and was the lead author of an Improvement Activity in the Merit Based Incentive Payment System (MIPS) of CMS’ Quality Payment Program.
Computational health science interests:
Deep Machine Learning and Data Visualization, Population Precision Medicine
Vivek Rudrapatna, MD, PhD
Assistant Professor of Medicine; Co-Director of Center for Real-World Evidence
Vivek Rudrapatna, MD, PhD
Vivek Rudrapatna obtained his MD and PhD at the Icahn School of Medicine at Mount Sinai, followed by a residency in internal medicine at Baylor College of Medicine and a fellowship in gastroenterology at UCSF. He joined the UCSF faculty in 2020 as a physician scientist. He spends part of his time as a gastroenterologist and inflammatory bowel disease specialist, and spends the remainder as a clinical data science investigator at the Bakar Computational Health Sciences Institute. His research team develops methods for using clinical data to uncover real-world evidence on treatment effects and advance the goals of precision medicine across use cases.
Computational health science interests:
Clinical Research Informatics, Deep Machine Learning and Data Visualization, Population Precision Medicine
Andrej Sali, PhD
Professor of BioEngineering
Andrej Sali, PhD
Andrej Sali develops computational methods for determining and modulating structures and functions of protein assemblies. He has a BSc in Chemistry from the University of Ljubljana, Slovenia, and a PhD from University of London, where he developed the MODELLER program for comparative modeling of protein structures. He was a Jane Coffin Childs Memorial Fund fellow at Harvard, studying lattice Monte Carlo models of protein folding. From 1995 to 2002, he was at Rockefeller University. He then moved to UCSF as a Professor of Computational Biology, in the Departments of Bioengineering, Therapeutic Sciences, and Pharm. Chem.; and in California Institute for Quantitative Biosciences (QB3). Andrej has been Sinsheimer Scholar, Sloan Research Fellow, Hirschl Trust Career Scientist, Zois Awarded Science Ambassador of Slovenia, and elected Fellow of ISCB. He has been editor of Structure since 2002; and a founder of Prospect Genomix and Global Blood Therapeutics.
Urmimala Sarkar, MD, MPH
Professor of Medicine
Urmimala Sarkar, MD, MPH
Urmimala Sarkar MD, MPH is Associate Chair for Faculty Experience for the Department of Medicine, Professor of Medicine at UCSF in the Division of General Internal Medicine, Associate Director of the UCSF Center for Vulnerable Populations, and a primary care physician at Zuckerberg San Francisco General Hospital’s Richard H. Fine People’s Clinic. Dr. Sarkar’s work centers on innovating for health equity and improving safety and quality of outpatient care for everyone, especially low-income and diverse populations. Her expertise spans topics including medical errors and patient safety, diabetes, and cancer prevention and survivorship. Dr. Sarkar’s research is collaborative and intersects with methods found in human centered design, human factors engineering, data science, health services research, and implementation science.
Computational health science interests:
Cancer and Precision Oncology, Clinical Research Informatics, Deep Machine Learning and Data Visualization
Aaron Scheffler, PhD, MS
Assistant Professor of Biostatistics, Epidemiology & Biostatistics
Aaron Scheffler, PhD, MS
Dr. Scheffler received his PhD in biostatistics from the University of California, Los Angeles and is an Assistant Professor in the Department of Epidemiology and Biostatistics. His research addresses the statistical challenges posed by highly structured data collected in applications from imaging to wearable technologies.
Computational health science interests:
Clinical Research Informatics, Computational Neuroscience, Deep Machine Learning and Data Visualization, Population Precision Medicine
William Seeley, MD
Professor of Neurology and Pathology
William Seeley, MD
Dr. Seeley is a behavioral neurologist and neuroscientist who studies neurodegenerative disease. He received his MD from the UCSF School of Medicine before completing neurology residency at the Massachusetts General and Brigham and Women’s Hospitals. He is currently a Professor of Neurology and Pathology and a member of the UCSF Memory and Aging Center. He is also Director of the UCSF Neurodegenerative Disease Brain Bank. His laboratory uses advanced neural network analysis to model and predict the anatomical spread of neurodegeneration in living patients and high-dimensional neuropathological approaches to clarify disease pathogenesis. Dr. Seeley’s work was recognized in 2011 with a fellowship from the John D. and Catherine T. MacArthur foundation. He is also a Fellow of the American Academy for the Advancement of Science.
Computational health science interests:
Computational Neuroscience, Deep Machine Learning and Data Visualization
Mark Segal, PhD
Professor of Epidemiology & Biostatistics
Mark Segal, PhD
Dr. Segal obtained a BSc (Mathematics) from the University of Western Australia and a PhD (Statistics) from Stanford. He was on the faculty at Harvard before coming to UCSF in 1989. His primary research interests are in bioinformatics and modern regression techniques. His focus is on the development and application of statistical methods to address problems in computational biology and genomics.
Computational health science interests:
Cancer and Precision Oncology, Deep Machine Learning and Data Visualization, Very Large Data Molecular Measurements
Wagahta Semere, MD, MHS
Assistant Professor of Medicine
Wagahta Semere, MD, MHS
Dr. Semere is a health services researcher and primary care physician at UCSF in the Division of General Internal Medicine at Zuckerberg San Francisco General Hospital. Her work focuses on leveraging technology-based platforms and clinical informatics methods to develop communication tools that promote better engagement of racially/ethnically diverse and low-income patients with providers in chronic disease management.
Computational health science interests:
Clinical Research Informatics
Youngho Seo, PhD
Professor of Radiology
Youngho Seo, PhD
Dr. Seo received his bachelor’s degree in Physics from Korea Advanced Institute of Science and Technology. He completed a master’s degree in Physics at the University of Alabama in Huntsville, followed by a second master’s degree and then PhD in Physics from UCLA. Following postdoctoral training at UCLA in experimental neutrino physics, he joined the UCSF Physics Research Laboratory (PRL) in 2003, and was trained in medical imaging physics before joining the faculty in 2006. Dr. Seo now leads a group of physicists and engineers working in the field of radionuclide and x-ray imaging instrumentation and physics, and directs the UCSF PRL, and preclinical PET/SPECT/CT/Optical imaging core facility at the UCSF Center for Molecular and Functional Imaging.
Computational health science interests:
Cancer and Precision Oncology, Clinical Research Informatics, Computational Neuroscience, Deep Machine Learning and Data Visualization
Brian Shoichet, PhD
Professor of Pharmaceutical Chemistry
Brian Shoichet, PhD
Brian Shoichet received a BSc in Chemistry and a BSc in History from MIT, and his PhD for work with Tack Kuntz on molecular docking from UCSF. Shoichet’s postdoctoral research was largely experimental, focusing on protein structure and stability with Brian Matthews at the Institute of Molecular Biology in Eugene, Oregon, as a Damon Runyon Fellow. He joined the faculty at Northwestern University in the Department of Molecular Pharmacology & Biological Chemistry. In 2002, he was recruited back to UCSF.
Computational health science interests:
Biological Modeling
Ida Sim, MD, PhD
Professor of Medicine
Ida Sim, MD, PhD
Dr. Sim is a primary care physician, informatics researcher, and entrepreneur. She is Professor of Medicine at UCSF, where she co-directs Biomedical Informatics at UCSF’s Clinical and Translational Sciences Institute. Her current research focuses on the use of mobile apps and sensors to improve health and manage disease for populations and individuals, and to make clinical research faster and less expensive. She is a co-founder of Open mHealth, a non-profit organization that is breaking down barriers to mobile health app and data integration through an open software architecture. Dr. Sim is also a co-investigator and Consortium Core Lead with the Mobile Data to Knowledge NIH Center of Excellence.
Computational health science interests:
Clinical Research Informatics
Marina Sirota, PhD
Associate Professor of Pediatrics
Marina Sirota, PhD
Prior to this position, Marina was the Lead Research Scientist in Systems Medicine at Stanford. She has worked as a Senior Research Scientist at Pfizer where she focused on developing Precision Medicine strategies in drug discovery. Marina has a PhD in Biomedical Informatics from Stanford University, where her graduate work focused on predicting drug-disease relationships based on gene expression to identify novel therapeutic indications for known drugs.
Computational health science interests:
Biological Modeling, Clinical Research Informatics, Computational Pharmacology
Joanne Spetz, PhD
Professor of Medicine
Joanne Spetz, PhD
Joanne Spetz is Director and Brenda and Jeffrey L. Kang Presidential Chair in Healthcare Finance at the Philip R. Lee Institute for Health Policy Studies (IHPS) at UCSF. She also is Associate Director for Research at the Institute and at Healthforce Center at UCSF. Her research focuses on the health care workforce and organization of health care services, including how these influence adoption of new technologies and processes of care, and the resulting quality of care. With training in economics, she has expertise in the analysis of large secondary datasets, mixed methods evaluation research, survey research, and econometric analysis. She teaches health economics and finance in the Master’s in Translational Medicine program.
Computational health science interests:
Clinical Research Informatics
Matthew H. Spitzer, PhD
Assistant Professor of Otolaryngology
Matthew H. Spitzer, PhD
Dr. Spitzer completed his graduate training in Immunology at Stanford University in the laboratories of Garry Nolan and Edgar Engleman. There, he developed experimental and analytical methods to model the state of the immune system and immune responses to cancer using high dimensional single-cell data. Dr. Spitzer moved to UCSF as a UCSF Parker Fellow and a Sandler Faculty Fellow and is now an Assistant Professor in the Departments of Otolaryngology-Head and Neck Surgery and Microbiology & Immunology and an investigator of the Parker Institute for Cancer Immunotherapy and the Chan Zuckerberg Biohub.
Computational health science interests:
Biological Modeling, Cancer and Precision Oncology, Deep Machine Learning and Data Visualization
Alejandro Sweet-Cordero, MD
Professor of Pediatrics
Alejandro Sweet-Cordero, MD
Dr. Sweet-Cordero studied Biology and Anthropology at Stanford, and earned his medical degree from UCSF in 1995. Further medical training included a residency in Pediatrics at UCSF, and subspecialty training in Pediatric Hematology/Oncology at Dana Farber Cancer Institute/Boston Children’s Hospital. He was a post-doctoral fellow in the laboratory of Tyler Jacks at the MIT Center for Cancer Research. As a post-doctoral fellow he also collaborated closely with Todd Golub and other members of the Broad Institute. Dr. Sweet-Cordero was an Associate Professor at Stanford up until 2016, when he joined UCSF as Associate Professor in Pediatrics and Benioff Chair of Child Health.
Computational health science interests:
Biological Modeling, Cancer and Precision Oncology, Clinical Research Informatics, Very Large Data Molecular Measurements
Geoff Tison, MD, MPH
Assistant Professor of Cardiology
Geoff Tison, MD, MPH
Geoff Tison, MD, MPH is a Cardiologist and Assistant Professor at the University of California, San Francisco (UCSF). His research focuses on cardiovascular prevention, using statistical and machine learning methods to analyze large-scale health data for disease prevention and phenotyping. He obtained formal training in machine learning, statistics, epidemiology and clinical research during his tenure at Johns Hopkins and as a National Institutes of Health T32 scholar. Dr. Tison received MD and MPH degrees from the Johns Hopkins Schools of Medicine and Public Health, completed internal medicine training at the Johns Hopkins Hospital, and fellowships in cardiology, advanced echocardiography and preventive cardiology at UCSF.
Computational health science interests:
Deep Machine Learning and Data Visualization, Population Precision Medicine
Duygu Tosun, PhD
Associate Professor of Radiology
Duygu Tosun, PhD
Dr. Tosun is an Assistant Professor of Radiology at UCSF and Co-Director of the Center for Imaging of Neurodegenerative Diseases (CIND) at the San Francisco Veterans Affairs Medical Center. Dr. Tosun obtained her BSc in Electrical and Electronic Engineering from Bilkent University, Turkey in 1999, and she received her MSE in Electrical and Computer Engineering from The Johns Hopkins University, Maryland in 2001. In 2003, she completed her MA in Mathematics, and later a PhD in Electrical and Computer Engineering from The Johns Hopkins University in 2005, followed by a postdoctoral fellowship in Neurology from UCLA in 2008.
Computational health science interests:
Clinical Research Informatics, Computational Neuroscience, Deep Machine Learning and Data Visualization, Population Precision Medicine
Daniela Ushizima, PhD
Affiliate Faculty
Daniela Ushizima, PhD
Dr. Ushizima is a Computer Scientist focused on Computer Vision. In 2015, she received the DOE Early Career award to develop AI/ML algorithms applied to scientific images across domains. She joined UCSF as Affiliate Faculty at BCHSI, UCSF, targeting biomedical data analyses. As Staff Scientist, Berkeley Lab, she leads the Image Processing team for CAMERA. She co-founded ImageXD as a Data Scientist at BIDS, UCB.
Computational health science interests:
Biological Modeling, Computational Neuroscience, Deep Machine Learning and Data Visualization
Laura van 't Veer, PhD
Professor of Laboratory Medicine; Endowed Chair in Cancer Research
Laura van 't Veer, PhD
Dr. van ‘t Veer received undergraduate training in biology and a MS in molecular oncology at the University of Amsterdam. She earned her PhD in Medicine at the University of Leiden and completed two postdoctoral fellowships, first at Harvard Medical School and later at the Netherlands Cancer Institute. Dr. van ‘t Veer has become a world renowned Molecular Biologist and inventor of MammaPrint®. In addition to her Professorship, she is the Program Leader of the UCSF Helen Diller Family Comprehensive Cancer Center Breast Oncology Program, Director of Applied Genomics with the HDFCCC, and UCSF-Site Principal Investigator of the Athena Breast Health Network.
Computational health science interests:
Cancer and Precision Oncology, Very Large Data Molecular Measurements
Paul Douglas Wesson, PhD
Assistant Professor of Epidemiology and Biostatistics
Paul Douglas Wesson, PhD
Dr. Wesson is an epidemiologist focused on quantifying health disparities among socially marginalized populations. As an HIV researcher, he works on the unique challenges of sampling hard-to-reach populations for HIV surveillance and leverage information from the sampling process to generate estimates of the population size. Valid population size estimates provide a denominator for the population at risk and inform the allocation of limited public health resources. He also uses advanced epidemiologic and statistical techniques to study the social determinants of infectious disease risk. Working at the intersection of infectious disease, data science, and social epidemiology, he incorporates theories and principles from social epidemiology to inform his study designs and analyses.
Computational health science interests:
Population Precision Medicine
Mary Whooley, MD
Professor of Medicine, Epidemiology & Biostatistics
Mary Whooley, MD
Dr. Whooley is a primary care physician and implementation scientist. She is currently Director of the VA Measurement Science QUERI and the Center for Healthcare Improvement and Medical Effectiveness (CHIME), PI of the 20-year Heart and Soul Study, and Site PI for the Million Veterans Program at the San Francisco VA. She also serves as San Francisco VA Site PI for the UCSF Clinical Informatics Fellowship, has mentored numerous junior investigators, and has coauthored more than 250 publications.
Computational health science interests:
Clinical Research Informatics, Deep Machine Learning and Data Visualization, Population Precision Medicine
Lani Wu, PhD
Professor of Pharmaceutical Chemistry
Lani Wu, PhD
Dr. Wu has come to biology by way of pure mathematics, computer science and electrical engineering. In her joint lab with Dr. Altschuler, they make use of experiment, quantitative data analysis, modeling, and theory to investigate fundamental questions about the origins and impact of cellular heterogeneity in cellular decision making, tissue development and homeostasis. Results from these studies are applied to investigate mechanisms of drug resistance, cancer evolution and new therapeutic strategies.
Computational health science interests:
Biological Modeling, Deep Machine Learning and Data Visualization
Duan Xu, PhD
Associate Professor of Radiology
Duan Xu, PhD
Duan Xu is an Associate Professor who leads the Imaging Research for Neurodevelopment Laboratory at UCSF in the Department of Radiology and Biomedical Imaging. He obtained his BA in Integrated Science and BS in Biomedical Engineering from Northwestern University in 1999, followed by his PhD in Bioengineering from UCSF and UC Berkeley in 2005. He is a member of the Advanced Imaging Technologies Resource Group and a member of the Pediatric and Fetal Research Interest Group specializing in the baby brain, and is an active member of the International Society of Magnetic Resonance in Medicine, the American Society of Neuroradiology, the Society of Molecular Imaging, and the Medical Image Computing and Computer Assisted Intervention Society.
Computational health science interests:
Clinical Research Informatics, Computational Neuroscience, Deep Machine Learning and Data Visualization
Adam Yala, PhD
Assistant Professor of Computational Precision Health, EECS at UC Berkeley and UCSF
Adam Yala, PhD
Adam Yala is an Assistant Professor of Computational Precision Health and EECS at UC Berkeley and UCSF. His research focuses on developing machine learning methods for personalized medicine and translating them to clinical care. His previous research has contributed to areas of: 1) predicting future cancer risk, 2) designing personalized screening policies. Adam’s tools underly multiple prospective trails and his research has been featured in the Washington Post, New York Times, Boston Globe and Wired. Prof Yala obtained his BS, MEng and PhD in Computer Science from MIT and he was a member of MIT Jameel Clinic and MIT CSAIL.
Keith Yamamoto, PhD
Vice Chancellor, Science Policy & Strategy; Vice Dean, Research, School of Medicine; Prof. of Cellular & Molecular Pharmacology
Keith Yamamoto, PhD
As UCSF’s first vice chancellor for Science Policy and Strategy, Keith Yamamoto leads efforts to anticipate the needs of an increasingly dynamic biomedical research endeavor, and to position UCSF optimally, by working within the University as well as influencing and shaping science policy at the state and national levels and beyond. Throughout his career, Yamamoto has been focused on the practice of science, science education and mentoring, peer review, communication of science, and advocacy for federal support for research. He also directs a basic research lab, making groundbreaking discoveries focused on signaling and transcriptional regulation by nuclear receptors.
Yang Yang, PhD
Associate Professor of Radiology
Yang Yang, PhD
Dr. Yang is an Associate Professor and Director of Mid-Field of MRI in the Department of Radiology and Biomedical Imaging at UCSF. He obtained his Ph.D. in Biomedical Engineering from the University of Virginia in 2016. He was an Assistant Professor in the Department of Radiology at Icahn School of Medicine at Mount Sinai from 2018 to 2022. Dr. Yang’s research focuses on developing and evaluating novel imaging techniques and incorporating AI to improve the clinical utility of MRI.
Computational health science interests:
Clinical Research Informatics, Deep Machine Learning and Data Visualization, Population Precision Medicine
Christina Yau, PhD
Associate Professor of Surgery
Christina Yau, PhD
Dr. Yau is an Associate Professor in the Department of Surgery with extensive experience developing biomarkers of response and prognosis in the translational setting. Dr Yau developed the standardized analysis approach for biomarker evaluation in the I-SPY 2 trial for high-risk early stage breast cancer. She co-led the Bioinformatics and Statistics core that evolved I-SPY 2 into I-SPY 2.2 to enable response-guided treatment adaption using a sequential multiple assignment randomized trial design. In addition to her work on developing biomarker-informed, patient-centered clinical trial designs, she is an active member of the NCI’s Center for Cancer Genomics Genome Data Analysis Network and serve on the statistics team of the WISDOM trial.
Computational health science interests:
Cancer and Precision Oncology
Jimmie Ye, PhD
Josephine Ione James Associate Professor of Epidemiology & Biostatistics
Jimmie Ye, PhD
The Ye lab is interested in how the interaction between genetics and environment affect human variation at the level of molecular phenotypes. To study these interactions, the lab couples high-throughput sequencing approaches that measure cellular response under environmental challenges with population genetics where such measurements are collected and analyzed across large patient cohorts. The lab develops novel experimental approaches that enable the large-scale collection of functional genomic data en masse and computational approaches that translate the data into novel biological insights. This approach is used to initially study primary human immune cells in both healthy and diseased patients to understand host pathogen interactions and its role in autoimmunity.
Computational health science interests:
Deep Machine Learning and Data Visualization, Population Precision Medicine, Very Large Data Molecular Measurements
STAFF
Habibeh Ashouri Choshali, PhD
Data Scientist
Habibeh Ashouri Choshali, PhD
Habibeh earned her PhD at Worcester Polytechnique Institute in 2021, working in Bioinspired Material Design Lab and Tissue Mechanics &
Mechanobiology Lab. Her studies focused on multi-disciplinary research at the boundary of computational science, data science, and biomaterials. Her current interests are in utilizing the power of data science and big data analytics to tackle complex problems in biology and healthcare.
Oksana Gologorskaya, MS
Associate Director User Experience
Oksana Gologorskaya, MS
Oksana graduated from the National Technical University of Ukraine (Kiev) with an MS in Applied Mathematics/Systems Analysis and Control. She has 15 years of experience as a technical product manager, business systems analyst, applications designer and software engineer in the enterprise software industry. Her background and natural inclinations combine technical, creative and analytic expertise with strong interests in the human part of the human-computer interaction and, on the other hand, deriving knowledge from data. For the last 10 years she has been focusing on business requirements, usability and user experience, and holistic approach to systems analysis and design.
Sharat Israni, PhD
Executive Director
Sharat Israni, PhD
Sharat Israni is the Executive Director of BCHSI. Previously, he was the Executive Director of Data Science in the Dean’s Office at Stanford Medicine. Sharat pioneered the use of “Big Data.” He served as Vice President of Data at both Yahoo! and Intuit, as these companies re-invented their products using Data Sciences. Previously, Sharat led Digital Media systems for broadcast and interactive TV at Silicon Graphics; and led data systems teams at IBM and HP. Sharat has a PhD in Industrial Engineering (Computer Science minor) and an MSIE (Systems) from the University of Wisconsin/Madison; and a B.Tech. in Mechanical Engineering from the Indian Institute of Technology, Kanpur. He has taught in the Graduate School of Business at Santa Clara University. Sharat has authored several patents and refereed publications.
Brandan La, BS
Technical Project Manager
Brandan La, BS
Brandan is a technical project and product manager interested in harnessing data science to solve problems in healthcare and research. Prior to joining the Bakar Institute, he was a data operations and product manager at the digital health company Stride Health where he helped build a platform for self-employed and contract workers to access affordable health insurance and benefits. Within academia, he has research experience in stem cell and cancer bioinformatics. Brandan obtained his undergraduate degree in Molecular & Cellular Biology from Stanford University. At BCHSI, he works on products in the Information Commons as well as projects related to Real World Evidence.
Nooshin Navidi Latour, MA
Communications Strategist
Nooshin Navidi Latour, MA
Nooshin is a seasoned health and science communicator who has also worked in the non-profit and media sectors. Nooshin led communications and marketing at the UCSF Clinical and Translational Science Institute (CTSI) for several years raising awareness of CTSI’s program services and resources, overseeing news story production, social media, websites and other digital media (infographics, videos, podcasts, etc). She obtained both her Bachelor’s degree in Communications and Master’s degree in Sociology from Stanford University.
Albert Lee, BA
Instructional Designer & Analyst
Albert Lee, BA
Albert’s professional interests lie at the intersection of data science and education. Before joining UCSF, he developed computer science, data science, and AI curricula, and his learners ranged from K-12 students to industry professionals. Outside of work, he is passionate about developing tech talent in Detroit, MI, and he collaborates with community organizations to create and deliver STEM enrichment programs for kids. Albert holds a bachelor’s degree in Industrial and Operations Engineering, and he expects to complete his Master of Applied Data Science degree later this year (2021).
Grace Loll, MAE
Academic Administrative Officer
Grace Loll, MAE
Most of Grace Loll’s 45-year career has been serving as an Executive Assistant in the education and legal sectors. She served as an Instructional Designer for Hewlett-Packard Corporate Education and a Special Education Assistant at Amador Valley High School. She supported C-Tier executives, legal counsel at UCOP/UC Health.
Hunter Mills, MS
Data Scientist
Hunter Mills, MS
Hunter Mills double majored in Physics and Mathematics during his undergraduate studies at Sonoma State University, and holds a master’s degree from Stanford University in Computational and Mathematical Engineering. He has previously worked on small space satellites, two of which are in orbit. At BCHSI, he works on a number of NLP initiatives predominantly focused around clinical text.
Boris Oskotsky, PhD
Lead Systems Administrator
Boris Oskotsky, PhD
Boris received his PhD in Condensed Matter Physics and a MS in Computer Science from Saint Petersburg Polytechnic University, Russia. As a research scientist, Boris worked on creating a computer simulation of quantum processes in semiconductors. Boris worked at Stanford University in different groups within the School of Medicine including Information Resources and Technology (IRT), Biomedical Informatics Research (BMIR), Neurobiology, and Dr. Atul Butte’s research lab. Since 2015, Boris has served as a Bioinformatics Systems Administrator for Dr. Butte’s lab at UCSF. He then joined the BCHSI team where he provides his knowledge and expertise as the Lead Systems Administrator.
Ayan Patel, MS
Lead Data Scientist, Center for Data-driven Insights & Innovation (UC Health)
Ayan Patel, MS
Ayan received his MS degree in Health Informatics from the UC Davis School of Medicine and his BS degree in Computer Science from the UC Davis College of Engineering. He currently leads the data operations of the UC Health Data Warehouse (UCHDW) which includes coordinating, maintaining, and updating source ETLs from all UC Health sites into a single dataset. He also is responsible for ensuring data is harmonized from the source systems so that it can consistently be referenced. The UCHDW is used for clinical operations, population health, and research across the UC Health campuses.
Lakshmi Radhakrishnan, MS
Data Scientist
Lakshmi Radhakrishnan, MS
Lakshmi’s expertise resides in the intersection of Computer Science and Biomedical Informatics. Her passion is in developing novel systems and algorithms to solve complex problems in Biology. She holds an undergraduate degree in Electrical Engineering, a Masters degree in Bioinformatics and has 8+ years of experience working in the industry as a Bioinformatics Scientist. At BCHSI, her primary focus is on the application of advanced machine learning and NLP techniques for automated de-identification of clinical notes. Before then, she was employed as a Bioinformatics Scientist at Thermofisher Scientific where she led the development of LIMS tools and design of micro-array chips.
Angela Rizk-Jackson, PhD
Director of Operations
Angela Rizk-Jackson, PhD
Angela is a seasoned professional in the realm of academic research. Her experience spans laboratory, clinical, and administrative settings. She obtained her PhD in neuroscience from UCLA, and completed postdoctoral work at UCSF in the area of neuroimaging, using machine learning analytical methods. As a Program Manager at UCSF’s Clinical and Translational Science Institute, she led Open Data efforts by helping to establish DataShare, and worked to facilitate several strategic initiatives aimed at accelerating research. She has filled many roles throughout her career, and as Director of Operations for BCHSI, she will strive to support the enterprise of Computational Health Sciences at the University.
Gundolf Schenk, PhD
Principal Data Scientist
Gundolf Schenk, PhD
Gundolf is interested in modeling biological data and providing informatics tools for biomedical research. His background comprises structural bioinformatics, x-ray scattering experiments of biomolecules in solution, and machine learning. He graduated from the Universities of Hamburg and Goettingen, Germany, and continued theoretical and experimental method development and data analysis for biomolecular research at the European Molecular Biology Laboratory and at Stanford University. At BCHSI he applies skills to integrate clinical notes and the automatic detection of structure within various modalities of biomedical data.
Yongmei Shi, PhD
Data Scientist
Yongmei Shi, PhD
Yongmei Shi obtained her PhD in Computer Science from the University of Maryland, Baltimore County. She has a background in natural language processing and semantic technology. At BCHSI, she primarily works on genomic testing data management.
Karen Shuster, MA
Web Designer/Developer
Karen Shuster, MA
Karen designs, develops, and maintains custom websites for the Bakar Institute and across many units at UCSF. She builds the sites on Drupal or WordPress platforms. She provides marketing support, including brochures and business cards and creates visual branding for large scientific symposia and conferences, including web sites, digital signage, programs, stage banners, slides, table materials, posters, Mailchimp announcements, and more. Additionally, she provides professional photography of faculty members and staff, conferences and events, and procures eclectic images for website visuals. She is both a communications advisor and designer / technical implementer, and is responsible for upholding the UCSF identity guidelines, while creating individualism for a division or project.
Rohit Vashisht, PhD
Clinical Data Scientist
Rohit Vashisht, PhD
Rohit Vashisht is a clinical data scientist at the Bakar Computational Health Sciences Institute, UCSF. Dr. Rohit’s research involves causal inference and machine learning analysis of large-scale real-world data in healthcare to generate real-world evidence for medical and policy level decision making. Dr. Rohit completed his post-doctoral at Stanford University. He holds a PhD in biomedical science from the Academy of Scientific and Innovative Research, New Delhi, India, and Bachelor of Engineering in biotechnology from Acharya Institute of Technology, Bangalore, India.