We’re a diverse team of scientists, physicians, and students at the UCSF Institute for Computational Health Sciences (ICHS).

Atul Butte, MD, PhD Professor
Atul Butte, MD, PhD, Professor, Director of UCSF’s Institute for Computational Health Sciences (ICHS). Former Professor of Pediatrics and Genetics, and by courtesy, Medicine, Pathology, and Computer Science, at Stanford University and Lucile Packard Children’s Hospital. Dr. Butte trained in Computer Science at Brown University, worked as a software engineer at Apple and Microsoft, received his MD at Brown University, trained in Pediatrics and Pediatric Endocrinology at Children’s Hospital Boston, then received his PhD in Health Sciences and Technology from Harvard Medical School and MIT. Dr. Butte is Chief of the new Division of Systems Medicine at Stanford. Dr. Butte is also a founder of three investor-backed companies: Personalis, providing clinical interpretation of whole genome sequences, Carmenta, discovering diagnostics for pregnancy complications, and NuMedii, finding new uses for drugs through open molecular data. Dr. Butte has authored more than 160 publications, with research repeatedly featured in Wired Magazine, and in the New York Times Science Times and the International Herald Tribune (2008), Wall Street Journal (2010 -2012), San Jose Mercury News (2010), and the San Francisco Chronicle (2013). In 2013, Dr. Butte was recognized by the White House as an Open Science Champion of Change for promoting science through publicly available data. Other recent awards include the 2013 induction into the American Society for Clinical Investigation, the 2012 FierceBiotech IT “Top 10 Biotech Techies”, 2011 National Human Genome Research Institute Genomic Advance of the Month, 2010 Society for Pediatric Research Young Investigator Award, and the 2008 AMIA New Investigator Award.
Marina Sirota, PhD Assistant Professor
Marina is currently an Assistant Professor at the Institute for Computational Health Sciences at UCSF. Prior to that she was the Lead Research Scientist in the Division of Systems Medicine at Stanford University and has worked as a Senior Research Scientist at Pfizer where she focused on developing Precision Medicine strategies in drug discovery. She completed her PhD in Biomedical Informatics at Stanford University, where her graduate work focused on predicting drug-disease relationships based on gene expression to identify novel therapeutic indications for known drugs. Her research interests lie in developing computational integrative methods and applying these approaches in the context of disease diagnostics and therapeutics. Her primary focus is on leveraging and integrating different types of omics and clinical data to better understand the role of the immune system in disease.
Sanchita Bhattacharya Bioinformatics Project Leader
Sanchita Bhattacharya is currently leading the efforts to leverage open-access clinical trials and research data from ImmPort, a National Institute of Allergy and Infectious Diseases Division of Allergy, Immunology, and Transplantation (NIAID-DAIT) sponsored shared data repository for subject-level human immunology study data and protocols. Her projects involve “The 10,000 Immunomes Project”, a diverse human immunology reference derived from over 44,000 individuals across 291 studies. Sanchita comes with over sixteen years of work experience as a data scientist at various academic institutions such as Stanford School of Medicine, Lawrence Berkeley National Laboratory, and MIT. Her formal training in bioinformatics coupled with expertise in computational modeling and immunology has led to a number of publications demonstrating the repurposing of big data in Immunology and other research areas to facilitate translational research.
Dexter Hadley, MD, PhD Assistant Professor
Dr. Hadley’s expertise is in translating big data into precision medicine and digital health. His work has resulted in an ongoing precision medicine clinical trial for ADHD ( Identifier: NCT02286817) for a first-in-class, non-stimulant neuromodulator to be targeted across the neuropsychiatric disease spectrum. His laboratory was recently funded by the NIH Big Data to Knowledge initiative to integrate multiple large-scale open databases to allow cross platform computational analyzes powerful enough to discover the functional genes and their related biological pathways that are defective in disease. He received the inaugural UCSF Marcus Award for Precision Medicine to develop a digital health initiative to use smartphones to screen for skin cancer and reduce the mortality of melanoma. In general, the end point of his work is rapid proofs of concept clinical trials in humans that translate into better patient outcomes and reduced morbidity and mortality across the spectrum of disease.
Keiichi Kodama, MD, PhD Assistant Professor
Keiichi Kodama MD, PhD is Assistant Professor of the Pediatric Department at UCSF School of Medicine. Dr. Kodama’s research interests focus on integrating genomics (bioinformatics) to identify diagnostics biomarkers, disease mechanisms and therapeutical drugs for diabetes and other metabolic diseases.
Bin Chen, PhD Instructor
Bin Chen was trained as a chemist in college and as a chem/bioinformatician in PhD. He worked as a software engineer in cheminformatics for three years before graduate school and worked as an intern in Novartis , Pfizer and Merck for two years during his graduate school. His long term interest is to develop tools and methods for drug discovery. In Butte Lab, his primary research focus is on the target identification and drug repositioning for GIST, Ewing’s Sarcoma and liver cancer. In addition, he is interested in exploring the venture ideas that help scientists to do better science.
Hanna (Hyojung) Paik, PhD Postdoctoral Fellow
Research interests: 1) Drug repositioning using computational approach, 2) Network analysis of human diseases
Dvir Aran, PhD Postdoctoral Fellow
Dvir holds a PhD in Computational Biology from the Hebrew University of Jerusalem, Israel, where he used bioinformatic and machine learning tools to study epigenetic alterations in health and disease. His current focus is on employing public resources and computational cancer immunology methods for attaining better understanding of the tumor’s microenvironment. Specifically, he aims to better understand immunoediting in solid tumors and its effect on the response to immunotherapy toward improving current treatment strategies.
Uta Grieshammer, PhD Director, Initiative for Precision Medicine
Bio will come soon
Boris Oskotsky, PhD Bioinformatics Systems Admin
Boris Oskotsky studied at Saint Petersburg Technical University where he earned a M.S. in Computers Science and a Ph.D. in Solid State Physics. Previously worked at Stanford University in different departments within the School of Medicine including IRT, BMIR and Neurobiology. He loves tea and everything tea-related (e.g. teapots and teakettles). His favorite way to spend time is traveling with his wife.
Joseph Charalel Genetics PhD Student
Joe graduated from Columbia University with a BA in Mathematics. He began undergraduate research in the lab of Dr. Liza Pon studying mitochondrial dynamics where he continued as a research technician after graduation until beginning graduate studies in 2013. As a graduate student in the Genetics Department, his general research interest is in cancer genomics. In the Butte Lab, Joe is working to improve cancer outcomes by leveraging public datasets and computational methods to better understand cancer genetics and disease mechanisms.
James Pan Medical Student
James Pan is a medical student at Stanford University who is aspiring to become an academic neurosurgeon. His research interests lie in leveraging large datasets to define disease and to use such signatures to translate new therapies and diagnostic tools from the bench to the bedside. He is also interested in designing technologies that help both physicians and patients interact with healthcare systems. In his spare time, James enjoys weightlifting and photography.
Idit Kosti, PhD Postdoctoral Fellow
Idit has a PhD in computational biology from the Technion, Haifa, Israel, where she studied epigenetics, trancription and splicing co-regulation in the human gene expression pathway. Her current focus is in meta anaylsis and computational integrative methods of human microbiome towards better understanding of pre term births patients microenvironment. This work is done in collaboration with the march Of Dimes project at Stanford university.
Jieming Chen, PhD Postdoctoral Fellow
Jieming completed his undergraduate degree at the National University of Singapore and worked at the Genome Institute of Singapore as a bioinformatics specialist on population genetics, with a focus on population structure. In 2015, he graduated from Yale University with a Ph.D in Computational Biology and Bioinformatics, from the laboratories of Professors Mark Gerstein and Lynne Regan, working on large-scale computational annotation of personal genomes. His current interests lie at the intersection of big data analytics and translational medicine. He presently works in the fields of organ transplant and asthma. In his spare time, he reads, travels, plays squash and games. For publications and more details: linkedin
Thomas A. Peterson, Ph.D. Postdoctoral Fellow
Tom Peterson earned his Ph.D. In Biology with a specialization in Bioinformatics & Computational Biology from the University of Maryland, Baltimore County. He developed statistical models and used machine learning techniques for analyzing the functional impact of genetic variants in human diseases such as cancer.
Matthew Kan, MD, PhD Postdoctoral Fellow
Matthew Kan, MD, PhD is a postdoctoral scholar in the lab of Atul Butte, MD, PhD. He is a graduate of Harvard College, where he was a research assistant to Dale Umetsu, MD, PhD and investigated the role of NKT cells in murine models of asthma. Dr. Kan received his MD and PhD in immunology at Duke University School of Medicine, where he was a Wakeman Scholar and Robert T. King, Jr. and Marie W. King Scholar. His PhD work with Carol Colton, PhD and Michael D. Gunn, MD described a novel immune-mediated theory for the pathogenesis of Alzheimer’s disease, leading to the repurposing of an FDA-approved drug for a planned Phase 2b clinical trial. He served in a number of leadership positions at Duke, including director of the AppleSeed Resident Teaching Awards and president of the Medical Scientist Training Program (MSTP) Student Council. and He was awarded a Kenan-Biddle Partnership grant to establish collaborative physician-scientist career training between Duke and UNC Chapel Hill Schools of Medicine. Dr. Kan also served on the selection committee for the Chancellor for Health Affairs and CEO of Duke University Health System. His research interests are in pediatric health and the identification and development of novel immune therapies.
Kelly Zalocusky, PhD Postdoctoral Fellow
Kelly earned her PhD in Neuroscience from Karl Deisseroth’s lab at Stanford University. She used neural imaging, optogenetic control, and machine learning methods to describe the neural basis of individual variability in risk-seeking behavior. Currently, she is focused on harnessing large-scale genetics and immunology data to advance our understanding and therapeutic options for neurodegenerative diseases.
Nadav Rappoport, PhD Postdoctoral Fellow
Nadav Rappoport, had earned his Ph.D. in Computer Science and Computational Biology from the Hebrew University of Jerusalem, Israel where he studies functional protein prediction using machine learning method working with prof. Michal Linial. His current research include preterm-birth genetic research, as well as big data analysis like Electronic Health Records (EHR), and its clinical applications.
Beau Norgeot, PSPG PhD Student Research Scientist
Beau earned a BS in Bioengineering & Bioinformatics from UC Santa Cruz. During his undergraduate research, he combined analytical protein chemistry with structural informatics to engineer a therapeutic peptide as a treatment for metastatic melanoma which earned him the University’s award for the best overall thesis. Following graduation Beau worked for David Haussler at the Computational Genomics Institute developing the ADAM big data genomics project and building predictive models as well as web applications to classify breast tumor samples and predict the effects of engineered mutations on antimicrobial peptide stability. Before completing his undergraduate degree, Beau founded 3 small companies and managed an international business intelligence division at a public company. Beau’s graduate focus is to leverage machine learning and artificial intelligence to improve clinical medicine and pharmacology outcomes.
Zicheng Hu, PhD Postdoctoral Fellow
Zicheng completed his undergraduate degree at the Hong Kong University of Science and Technology. After that, he moved to The University of Texas at Austin, where he earned his Master’s degree in Statistics and Ph.D. in Cell and Molecular Biology from Lauren Ehrlich’s lab. He used knock-out mouse models to study the roles chemokine receptors play in the autoimmune diseases. Currently, he is focused on characterizing dynamics of the human immune system using high through-put data.


  • Jeff Wiser, Patrick Dunn, Mike AtassiNorthrop Grumman
  • Ashley Xia and Quan ChenNIAID
  • Takashi Kadowaki, Momoko Horikoshi, Kazuo Hara, Hiroshi Ohtsu U Tokyo
  • Kyoko Toda, Satoru Yamada, Junichiro IrieKitasato Univ and Hospital
  • Shiro MaedaRIKEN
  • Alejandro Sweet-Cordero, Julien SagePediatric Oncology
  • Mark Davis, C. Garrison FathmanImmunology
  • Russ Altman, Steve QuakeBioengineering
  • Euan Ashley, Joseph Wu, Tom Quertermous Cardiology
  • Mike Snyder, Carlos Bustamante, Anne Brunet Genetics
  • Jay Pasricha Gastroenterology
  • Rob Tibshirani, Brad Efron Statistics
  • Hannah Valantine, Kiran Khush Cardiology
  • Ken Weinberg Pediatric Stem Cell Therapeutics
  • Mark Musen, Nigam Shah National Center for Biomedical Ontology
  • Minnie Sarwal Nephrology
  • David Miklos Oncology