We are pleased to host Dr. Hongtu Zhu, Kenan Distinguished Professor from the Department of Biostatistics at the University of North Carolina, as part of the CDS distinguished speaker series. His lecture, “Causal Generalist Medical AI,” will present a comprehensive and thought-provoking examination of this emerging field.

Speaker:

Dr. Hongtu Zhu

Kenan Distinguished Professor 

Department of Biostatistics 

University of North Carolina 

Date:

16 June 2026 (Tuesday)

Time:

11:00am-12:00pm

Venue:

HW312, Haking Wong Building, The University of Hong Kong

Abstract:
The rapid evolution of flexible, reusable foundation models is transforming medical science. This lecture introduces Causal Generalist Medical AI (Causal GMAI)—a paradigm that integrates causal inference into generalist AI architectures to enhance interpretability, robustness, and generalizability in clinical decision-making. Causal GMAI leverages advanced self-supervised, semi-supervised, and supervised learning across highly diverse, multimodal datasets, including medical imaging, electronic health records (EHR), clinical trials, genomics, knowledge graphs, and clinical narratives, to perform complex downstream tasks with minimal task-specific supervision.  

By embedding structural causal reasoning, these models move beyond traditional correlation-based prediction to infer underlying disease mechanisms and counterfactual outcomes, thereby advancing diagnostic precision and personalized medicine. This lecture will outline the mathematical and technical foundations of Causal GMAI—specifically focusing on causal discovery, counterfactual reasoning, and domain adaptation under covariate shift—alongside its real-world clinical applications. Finally, the lecture will address critical open challenges in regulatory compliance, statistical validation, and multi-center dataset curation required to ensure clinical reliability. Ultimately, this presentation provides a foundational framework for statisticians, data scientists, and AI practitioners to advance the next generation of trustworthy and interpretable medical AI.

 

Biography:

Dr. Hongtu Zhu is the Kenan Distinguished Professor of Biostatistics, Statistics, Radiology, Computer Science and Genetics at the University of North Carolina at Chapel Hill. He is the Fellow of ASA, IMS, AIMBE, and IEEE. He was a DiDi Fellow and Chief Scientist of Statistics at DiDi Chuxing between 2018 and 2020 and held the Endowed Bao-Shan Jing Professorship in Diagnostic Imaging at MD Anderson Cancer Center between 2016 and 2018. He is an internationally recognized expert in statistical learning, medical image analysis, precision medicine, biostatistics, artificial intelligence, and big data analytics. He received an established investigator award from the Cancer Prevention Research Institute of Texas in 2016, the INFORMS Daniel H. Wagner Prize for Excellence in Operations Research Practice in 2019, the ICSA 2025 Distinguished Achievement Award, the IMS 2027 Medallion award and Lecture, and the COPSS 2025 Snedecor Award. He has published more than 359 papers in top journals, including Nature, Science, Cell, Nature Genetics, Nature Communication, PNAS, AOS, JASA, Biometrika, and JRSSB, as well as presenting 71+ conference papers at top conferences, including meetings for Neurips, ICLR, ICML, AAAI, IPMI, MICCAI, and KDD. He is the coordinating editor of JASA and the editor of JASA ACS. 

   

All are welcome to attend.