Steven Altschuler

Dr. Steven Altschuler is a Professor in the Department of Pharmaceutical Chemistry at the University of California San Francisco (UCSF), part of the School of Pharmacy. His research focuses on systems biology, cell signaling, and drug discovery, integrating experimental science with mathematics and computational methods. He holds a PhD in Mathematics from UC San Diego (1990) and has extensive experience in academia and industry, including roles at Microsoft Research and Harvard University. His lab develops high-throughput screening tools and quantitative imaging techniques to study cellular behavior and disease mechanisms, with a focus on cancer persistence, drug resistance, and hypoxia responses.

• Education:
  • PhD in Mathematics, University of California, San Diego, 1990
  • Masters in Mathematics, University of California, San Diego, 1986
  • Bachelor of Arts in Mathematics, University of Pennsylvania, 1985

Research interests include understanding cellular individuality, collective cell behaviors, and the evolution of drug resistance. His lab employs machine learning, microscopy, and mathematical modeling to uncover design principles of biological systems. Key projects involve developing therapies for cancer and neurodegenerative diseases, and optimizing drug discovery pipelines using phenotypic screening platforms.

Publications highlight work on cancer persisters, TET2 mutations in leukemia, and single-cell heterogeneity. His lab collaborates with institutions like the Quantitative Biosciences Institute (QBI) and has pioneered technologies like MUSE for spatial analysis of cell morphologies. Current projects address ALS mechanisms and drug resistance in lung cancer.

Advising and training include mentoring graduate students and postdocs in interdisciplinary approaches. The lab’s tools, such as PhenoRipper and SimuCell, are widely used in drug discovery and systems biology.