Join us for an in-person Distinguished Speaker event featuring Jian Ma, a pioneering leader in computational biology and AI whose groundbreaking research has transformed our understanding of genome structure, cellular organization, and the molecular mechanisms that drive human health.

Title: Learning Cellular Organization and Function Across Scales

Abstract: Despite major advances in high-throughput genomics and cell biology, a predictive understanding of human cell diversity and tissue function remains out of reach. A central challenge is integrating heterogeneous measurements across molecular, cellular, and tissue scales. Recent advances in AI and machine learning offer new ways to model cellular systems across these scales, learn biologically grounded representations from increasingly rich multimodal data, and generate predictions and hypotheses about complex cellular processes. I will present our recent work on modeling gene regulation and genome organization from single-cell epigenomic data, as well as cellular interactions and tissue dynamics from spatial molecular profiles. I will also discuss how generative and agentic AI can extend these approaches to predictive modeling and iterative scientific discovery. Together, these approaches provide new insights into how cellular states are established, coordinated, and perturbed in health and disease.

Jian Ma is the Ray and Stephanie Lane Professor of Computational Biology in the School of Computer Science at Carnegie Mellon University. His group develops AI and machine learning methods to study the structural and functional complexity of the human genome and cellular organization. He founded the Center for AI-Driven Biomedical Research (AI4BIO) at CMU to advance AI approaches integrated with autonomous experimentation for decoding the molecular language of cellular behavior. His honors include the NSF CAREER Award, Guggenheim Fellowship, Allen Newell Award for Research Excellence, and election as Fellow of the American Association for the Advancement of Science (AAAS), the International Society for Computational Biology (ISCB), and the Association for Computing Machinery (ACM).

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