Biography

S. Joshua Swamidass, MD PhD, is an Associate Professor of Pathology & Immunology in the Division of Laboratory and Genomic Medicine at Washington University School of Medicine in St. Louis, with appointments in Biomedical Engineering and in Computer Science & Engineering. His research develops artificial intelligence for problems in biology, medicine and chemistry, with a focus on tools that directly affect drug safety and patient care.

He is best known for deep learning models of bioactivation, the process by which the body metabolizes some medicines into toxic forms. Supported by the National Institutes of Health, this work produced the XenoSite family of models, which are used by pharmaceutical companies to guide the development of safer medicines. More recently his group has developed AI for pathology practice and was among the first academic groups to deploy AI into a pathology workflow. A deep learning model for assessing donor kidney biopsies, developed with Joseph Gaut, is licensed to Trusted Kidney and is now used in clinical practice to help transplant more donated kidneys. He also founded ReMedical to commercialize the bioactivation models.

He trained in computer science and medicine at the University of California, Irvine, earning a BS in biology, an MS and PhD in Information and Computer Sciences under Pierre Baldi, and an MD. After residency in clinical pathology at Washington University, and visiting appointments at the Broad Institute of MIT and Harvard and at Pfizer, he joined the Washington University faculty in 2010. He has mentored PhD students, postdoctoral fellows, residents and junior faculty, and teaches population genetics and AI for image analysis in pathology.

In 2023 he was elected a Fellow of the American Association for the Advancement of Science (AAAS), for “distinguished contributions to the field of deep learning in computational biology, and for extraordinary public outreach promoting an understanding of science among communities of faith.”

Public engagement with science

The outreach recognized by the AAAS focuses on explaining evolutionary science, human origins, race and artificial intelligence to public audiences, especially communities that are often skeptical of scientific findings. He has given plenaries, named lectures and invited talks at universities and conferences including MIT, Cambridge, Oxford, Emory and New York University. His writing has appeared in Science, Nature, The Wall Street Journal and Christianity Today, and his work has been covered by WIRED,USA Today and NPR.

The book explains the difference between genetic and genealogical ancestry, a distinction that is often overlooked in public discussions of human origins. Drawing on population genetics and computational models of genealogy, it shows how everyone alive today shares common genealogical ancestors who lived surprisingly recently, even though our genetic ancestry traces back to a large population over a much longer time. The book also explains the scientific problems with polygenesis, the discredited claim that human races arose separately, which historically supported racist ideas about inherent racial differences.

Peer reviewed and published by an academic press, the book has sold more than 10,000 copies and was endorsed by scientists including population geneticist Alan Templeton.

Articles and reviews

Reception of the book

Public writing

Service and public dialogue

In the media

Selected invited talks

  • Plenary, Computer Aided Drug Design Gordon Research Conference 2023
  • AI and Chemistry, Department of Mathematics, Iowa State University 2023
  • Applying AI in Chemistry, Biology, and Medicine Southern California AI & Biomedicine Symposium, UC Irvine, 2022
  • Deep Learning the Bioactivation of Drugs Division of Chemical Toxicology, American Chemical Society, 2022
  • Translating from Chemistry to Clinic with Deep Learning National Institutes of Health, 2018
  • Plenary, International Biocuration Conference Fudan University, Shanghai, 2018
  • Plenary, Chemical Biology Workshop University of Minnesota, 2018
  • Of Apes and Artificial Minds, McDonald Lecture Hong Kong University, 2017
  • Plenary, Gordon Research Conference Exploring Advances in Quantitative Predictions of Drug Metabolism, Transport, Safety and Pharmacokinetics, 2017
  • Machine Learning of Drug Metabolism CADD Forum, Janssen Research & Development, 2016

Research in the news

Lab alumni

  • Tyler B. Hughes, PhD, 2018 AI scientist in industry
  • Na Le (Lena) Dang, MD PhD, 2018 Physician-scientist, pediatrics, WashU
  • Matthew K. Matlock, MD PhD, 2019 Emergency medicine
  • Arghya Datta, PhD, 2021 Scientist, Amazon
  • Noah R. Flynn, PhD, 2021 Scientist, pharmaceutical industry
  • Kathryn Sarullo, PhD, 2023; postdoc, 2023–2025 Research scientist
  • Jed Zaretzki, Postdoc, 2012–2013 Computational scientist, biotech
  • Rohit Farmer, Postdoc, 2018–2019 NCBI, National Institutes of Health
  • Jon N. Marsh, Staff scientist, 2017–2023 Industry scientist