News
By Laurel Skurko
On March 11, 2026, the winners of the inaugural Atul Butte Student Award and Distinguished Fellowship were announced during AI Research Day at UCSF. UCSF student Alex Li and UCSF fellow Claire McDonell were recognized by the selection committees, based on their demonstrated innovation in biomedical research using data science-driven approaches, including AI, and discussed their work with the audience upon accepting their awards.
William Brown, III, PhD, director of recruitment, retention & representation; associate professor of prevention science introduced the awards program and shared more about its namesake, Atul Butte (1969-2025). “Atul not only helped define the field of biomedical data science,” said Brown, “but he advanced it through the people he trained and inspired.”
- Innovation in Biomedical Data Science Student Award
Brown explained that the Atul Butte Student Award was created to recognize a graduate student whose work exemplifies work at the intersection of computation and biology, and then presented the first award, Atul Butte Innovation in Biomedical Data Science Student Award, to Alex Jie Li, UC Berkeley-UCSF Ph.D. student, who then presented his research, modeling protein design, and used animation to show the audience how he is using AI to design new proteins in the lab.
Distinguished Fellow in Data Science and Health Research
Next, Brown explained the second award, the Fellow award, by saying, “For Atul, data science should not just advance discovery, but be applied to important questions in health care.” Brown then introduced the winner of the second award, the Atul Butte Distinguished Fellow in Data Science and Health Research, which he presented to Claire McDonell, PhD, for her work using causal inference methods to research marginalized communities and advance health equity.
Brown concluded that Atul Butte’s name is synonymous with generosity and mentorship, and joined the audience in applauding the two recipients who embody the level of rigor modeled by Atul Butte.
ABOUT THE 2026 ATUL BUTTE AWARDS PROGRAM AWARDEES
Alex Jie Li, winner of the Atul Butte Innovation in Biomedical Data Science Student Award, is a UC Berkeley-UCSF bioengineering PhD student studying de novo enzyme design. He is co-mentored by Tanja Kortemme, PhD, UCSF and Margaux Pinney, PhD, UC Berkeley.
Li presented his research, “ProteinZen: all-atom protein generation with SE(3) flow matching,” published on bioRxiv on October 18, 2025, for which he is the first author, a criterion for winning this award. ProteinZen is an AI method that designs proteins with atomic-level precision by using 3-D geometry-aware modeling (SE(3)), improving both realism and performance in complex protein design tasks. (See his abstract, below)
Claire McDonell, winner of the Atul Butte Distinguished Fellow in Data Science and Health Research, is an epidemiology & biostatistics graduate student whose research interests are at the intersection of causal inference, community-engagement, and drug use harm reduction. She aims to conduct rigorous research that amplifies the voices of socially marginalized communities, informs just social policy, and advances health equity. She works with Meghan Morris, PhD, UCSF on clinical trials and observational studies focused on improving the health outcomes of people who use drugs.
ABOUT THE ATUL BUTTE AWARDS PROGRAMS
- Atul Butte Innovation in Biomedical Data Science Student Award
- Sponsor: Bakar Computational Health Sciences Institute
- Organizer / Program: BCHSI
- Eligibility: Open to students from all UCSF graduate programs
- Focus: Recognizes innovation and potential impact in data-driven discovery in biology and health
- Selection Committee: Marina Sirota, Sharat Israni, Angela Rizk-Jackson, Ashish Raj, William Brown, Vivek Rudrapatna, Gundolf Schenk and Tony Capra
- Selection Notes: The committee highlighted the innovation, potential impact and alignment of the student’s work with the spirit of the award
Atul Butte Distinguished Fellowship in Data Science and Health Research
- Sponsor: DaTABASE training program
- Organizer / Program: UCSF Data Science Training to Advance Behavioral and Social Science Expertise for Health Disparities Research (DaTABASE) T32 Program, housed within the UCSF Department of Epidemiology and Biostatistics
- Eligibility: Predoctoral researchers studying social and behavioral determinants of health through the DaTABASE program
- Focus: Advanced data analytics training focused on health disparities research
- Selection Committee: William Brown, Aric Prather, Yulin Hswen and Raman Khanna, Marina Sirota
The 2027 Atul Butte Student and Fellow Awards Program cycle will be announced in early December, 2026 and will remain open through January 30, 2027. Please visit the BCSHI landing page and join the BCHSI mailing list to learn more.
ABOUT ATUL BUTTE
Atul Butte, MD, PhD (1969–2025) was a physician scientist and biomedical informatics pioneer who helped define modern, evidence-first precision medicine, showing how large-scale clinical and molecular data can be translated into decisions that improve patient care. He held leadership roles at Stanford University and Lucile Packard Children’s Hospital, including chief of the Division of Systems Medicine, and faculty appointments spanning Pediatrics and Medicine, with courtesy in Computer Science. He later joined UCSF as the inaugural director of the Bakar Computational Health Sciences Institute and served as UC Health’s inaugural chief data scientist, helping unify data-driven approaches across the UC academic medical centers. Beyond academia, Atul was a builder and mentor to founders focused on real-world clinical impact. He co-founded multiple data-driven companies, including Personalis, NuMedii, and Carmenta, and he was widely recognized for advancing rigorous, reproducible translation of data into care. To learn more about Atul Butte, please visit the Atul Butte Wikipedia page.
ABOUT THE BAKAR COMPUTATIONAL HEALTH SCIENCES INSTITUTE (BCHSI)
The UCSF Bakar Computational Health Sciences Institute is an academic home for faculty, students, trainees, and staff at the University who employ computational methodologies to address topics in health and wellness. Please visit the BCHSI landing page.
A multidisciplinary team from UCSF, including investigators at the Bakar Computational Health Sciences Institute, explored Alzheimer’s disease using a novel, cell–specific approach. Supported by…
Lead Author Julian Hong publishes in Cancer. “Over the past several years, we’ve had an increasing appreciation for the important relationship between cancer, its treatment, and mental…
BCHSI Affiliated Faculty Peng He, PhD, assistant professor in the Department of Pathology, recently published in Nature Computational Science "Toward informed batch correction for …
