MHRC Research Seminar: Harnessing Multimodal AI for Knowledge-Enhanced Computational Pathology

Enjoy free admission, all are welcome.
* Seats are limited and will be arranged on a first-come-first-served basis.
* Please note that NO CPD points will be offered by the research seminar.

Topic:
Harnessing Multimodal AI for Knowledge-Enhanced Computational Pathology

Speaker:
Prof. Yu Lequan
Assistant Professor
School of Computing and Data Science
Faculty of Science
The University of Hong Kong

Abstract:
Computational pathology is transforming diagnostic practice by leveraging artificial intelligence to extract clinically relevant insights from Whole Slide Images (WSIs). The integration of multimodal AI offers new opportunities for building interpretable, accurate, and scalable diagnostic tools. In this talk, Prof. Yu will present his recent advances that demonstrate how incorporating domain knowledge and biological context can significantly enhance histopathological analysis. Prof. Yu will first introduce a knowledge-guided framework that integrates expert-derived knowledge into AI models, enabling more generalisable and clinically meaningful predictions across diverse cancer tasks. Prof. Yu then showcases a strategy for inferring cellular-level phenotypes directly from histology images, providing a cost-effective alternative to spatial transcriptomics for characterising the tumor microenvironment and predicting patient outcomes. Together, these works reflect a shift toward more human-aligned, knowledge grounded AI systems for computational pathology.

Biography:
Prof. Yu Lequan is an Assistant Professor at School of Computing and Data Science, The University of Hong Kong, and a former postdoctoral fellow at Stanford University. He received his Ph.D. and B.Eng. from The Chinese University of Hong Kong and Zhejiang University, respectively. His research focuses on medical AI, multimodal learning, and precision oncology. He has published over 100 papers, including Nature Communications, npj Digital Medicine, Cell Gemonics, and TPAMI, with 22,000+ Google Scholar citations. Prof. Yu was ranked by Clarivate Analytics in the top 1% of the citation list in 2023-2025 and won the MICCAI 2023&2024 Young Scientist Publication Impact Award Runner-Up. He serves as the Associated Editor of npj Digital Medicine, the Guest Associated Editor of TMI, and the Area Chair of NeurIPS, ICLR, CVPR, AAAI, and MICCAI.