Atul Butte, MD, PhD

Professor
Department of Pediatrics
+1 415 514-0528
Research Description: 

Atul Butte, MD, PhD
Priscilla Chan and Mark Zuckerberg Distinguished Professor of Pediatrics, Bioengineering and Therapeutic Sciences, and Epidemiology and Biostatistics at UCSF
Director, Bakar Computational Health Sciences Institute, UCSF
Chief Data Scientist, University of California Health System (UC Health)

Atul Butte, MD, PhD is the Priscilla Chan and Mark Zuckerberg Distinguished Professor and inaugural Director of the Bakar Computational Health Sciences Institute (bchsi.ucsf.edu) at the University of California, San Francisco (UCSF). Dr. Butte is also the Chief Data Scientist for the entire University of California Health System, with 20 health professional schools, 6 medical schools, 5 academic medical centers, 10 hospitals, and over 1000 care delivery sites. Dr. Butte has been continually funded by NIH for 20 years, is an inventor on 24 patents, and has authored over 200 publications, with research repeatedly featured in the New York Times, Wall Street Journal, and Wired Magazine. Dr. Butte was elected into the National Academy of Medicine in 2015, and in 2013, he was recognized by the Obama Administration as a White House Champion of Change in Open Science for promoting science through publicly available data. Dr. Butte is also a founder of three investor-backed data-driven companies: Personalis (IPO, 2019), providing medical genome sequencing services, Carmenta (acquired by Progenity, 2015), discovering diagnostics for pregnancy complications, and NuMedii, finding new uses for drugs through open molecular data. 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 from Harvard Medical School and MIT.

Primary Thematic Area: 
Human Genetics
Secondary Thematic Area: 
Immunology
Research Summary: 
Dr. Butte builds and applies tools that convert more than 400 trillion points of molecular, clinical, and epidemiological data into diagnostics, therapeutics, and new insights into disease.
Publications: 

Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist.

Nature medicine

Norgeot B, Quer G, Beaulieu-Jones BK, Torkamani A, Dias R, Gianfrancesco M, Arnaout R, Kohane IS, Saria S, Topol E, Obermeyer Z, Yu B, Butte AJ

A robust and interpretable end-to-end deep learning model for cytometry data.

Proceedings of the National Academy of Sciences of the United States of America

Hu Z, Tang A, Singh J, Bhattacharya S, Butte AJ

CovidCounties - an interactive, real-time tracker of the COVID-19 pandemic at the level of US counties.

medRxiv : the preprint server for health sciences

Arneson D, Elliott M, Mosenia A, Oskotsky B, Vashisht R, Zack T, Bleicher P, Butte AJ, Rudrapatna VA

Protected Health Information filter (Philter): accurately and securely de-identifying free-text clinical notes.

NPJ digital medicine

Norgeot B, Muenzen K, Peterson TA, Fan X, Glicksberg BS, Schenk G, Rutenberg E, Oskotsky B, Sirota M, Yazdany J, Schmajuk G, Ludwig D, Goldstein T, Butte AJ