Hosted on Wednesdays, 4:00-5:00 pm.
See below for seminar dates and speakers. Seminars will be recorded and updated to our YouTube channel.
Data Science Insitute
Center for Computational Molecular Biology
CCMB Seminar Series
The CCMB seminar series brings together colleagues from across the world to speak on recent research developments in computational biology, fostering robust conversations and diverse connections for our faculty and students.
Fall 2025 Seminar Schedule
Wednesday, September 3: Molly Schumer, Stanford University
Molly Schumer is an Assistant Professor in Biology. She is interested in genetics and evolutionary biology. After receiving her PhD at Princeton, she did her postdoctoral work at Columbia and was a Junior Fellow in the Harvard Society of Fellows and Hanna H. Gray Fellow at Harvard Medical School. Current research in the lab centers on understanding the genetic mechanisms of evolution, with a focus on natural populations.
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Wednesday, September 10: James Zou, Stanford University
James Zou is an associate professor of Biomedical Data Science, CS and EE at Stanford University. He works on developing cutting-edge AI for biomedical applications. His group developed many widely used innovations including EchoNet AI (FDA cleared for assessing cardiac function), Gradio (used by over a million developers), and SyntheMol (NY Times 2024 Good Tech). He has received a Sloan Fellowship, the Overton Prize, an NSF CAREER Award, two Chan-Zuckerberg Investigator Awards, a Top Ten Clinical Achievement Award, best paper awards at ICML and other AI conferences, and faculty awards from Google, Amazon, Adobe and Apple.
“Computational biology in the age of AI agents”
AI agents—large language models equipped with tools and reasoning capabilities—are emerging as powerful research enablers. This talk will explore how computational biology is particularly well-positioned to benefit from rapid advances in agentic AI. I’ll first introduce the Virtual Lab—a collaborative team of AI scientist agents conducting in silico research meetings to tackle open-ended research projects. As an example application, the Virtual Lab designed new nanobody binders to recent Covid variants that we experimentally validated. Then I will present CellVoyager, a data science agent that analyzes complex genomics data to derive new insights. Finally I will discuss using AI agents to discover and explain new biological concepts encoded by large protein foundation models (interPLM). I will conclude by discussing limits of agents and a roadmap for human researcher-AI collaboration.
Wednesday, October 22: Sendurai Mani, Brown University
Sendurai A. Mani is a Professor in the Department of Pathology and Laboratory Medicine at Brown University. He is also the Associate Director of Translational Oncology at Brown University Legorreta Cancer Center. Dr. Mani earned a Ph.D. from The Indian Institute of Science, Bangalore, India and then did postdoctoral work with Dr. Robert A. Weinberg at the Whitehead Institute/Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts, USA. He then joined the University of Texas MD Anderson Cancer Center, Houston, Texas as an Assistant Professor in December of 2007 and has been promoted to Associate Professor with tenure in 2013. In late 2022, Dr. Mani joined Brown University Legorreta Cancer Center as a professor and Associate Director of Translational Oncology. Dr. Mani has received numerous prizes and awards for his research, including a Jimmy V foundation’s V-Scholar Award and The American Cancer Society Research Scholar award. Dr. Mani’s original finding demonstrating the cancer cells acquire stem cell properties by activating latent embryonic epithelial-mesenchymal transition (EMT) program provided the foundation and explanation for the presence of plasticity within the tumor as well as the development of resistance to various treatments.
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Spring 2026 Seminar Schedule
Wednesday, January 28: Rajiv McCoy, Johns Hopkins University
Rajiv McCoy is an associate professor in the Department of Biology with interests in human genetics and evolution. He received his Ph.D. from Stanford University and completed his postdoctoral work at Princeton University and the University of Washington.
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Wednesday, April 29: Steve Reilly, Yale University
Steve Reilly is a genomicist specializing in human genetics, evolution, and gene-regulation. He is specifically interested in furthering our understanding of non-coding variation, the main cache of human genetic diversity. He develops novel computational + experimental approaches to identify and functionally characterize human variation at scale. These tools include DeepSweep: a machine learning method to identify variants under positive selection, HCR-FlowFISH: a method to directly characterize the functional targets of regulatory elements, and application of the Massively Parallel Reporter Assay (MPRA) to understand the regulatory impact of genomic variation.
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