Date: 25 August 2026 (Tuesday)
Time: 4:00 pm – 5:00 pm
Venue: Lecture Theatre 1, 1/F, 3 Sassoon Road 
Host: Professor Mu He

Guangdun Peng, Ph.D., is a Principal Investigator at the Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences. He obtained his PhD from the Shanghai Institute of Biochemistry and Cell Biology, CAS, and completed his postdoctoral training at UCLA. As one of the pioneering figures in establishing spatial transcriptome methods, his research integrates the development of spatial multi-omics technologies with their application to fundamental questions in developmental biology and regenerative medicine. He developed the spatial transcriptomics platform Geo-seq and subsequently advanced the field into the multi-omics era through MISAR-seq, Chem-map and DuTracer. With more than 30 corresponding-author papers and 6,000+ citations in journals including Nature, Cell, Nature Methods, Nature Cell Biology and Developmental Cell, his contributions have been recognized among China's Top 10 Advances in Life Sciences.

Understanding how cellular spatial organization governs lineage specification is fundamental to developmental biology and disease. Spatial location is not merely context but a determinant of cell fate: where a cell resides shapes its identity and behavior within complex tissue architectures. Equally important is the integration of space and time—single-cell-resolved temporal omics that track cell fate and molecular states as they unfold, capturing the dynamics of development, tissue injury, and regeneration. Modern spatial technologies thus move beyond cataloging cells toward explaining why they adopt particular fates, mapping gene regulatory programs in native contexts and exposing therapeutic entry points invisible to static snapshots. Looking forward, automated, AI-driven workflows will unify transcriptomic, epigenetic, and proteomic layers into a holistic molecular view, establishing the foundation for digital and virtual life—computational frameworks that simulate and predict the logic of development and disease.

All are welcome.