Turning Tissue Maps into Tissue Models: Spatial Biology, Machine Learning, and Dynamics
Event details
| Date | 18.05.2026 |
| Hour | 12:15 › 13:15 |
| Speaker | Prof. John Hickey, Duke University, Durham, NC, USA |
| Location | Online |
| Category | Conferences - Seminars |
| Event Language | English |
EPFL BIOE TALKS SERIES (sandwiches provided)
Abstract:
Can we turn a biopsy into a tissue time machine? My lab combines spatial-omics, multiplexed imaging, machine learning, and agent-based modeling to ask how multicellular tissues are built, how they differ across disease, and how they change over time. We use machine learning to reconstruct tissue architecture and identify recurring organizational patterns, and mechanistic models to test how those patterns emerge and respond to perturbation. The long-term goal is to build virtual tissues that turn spatial biology from a descriptive map into a predictive framework.
Bio:
John Hickey is an Assistant Professor of Biomedical Engineering at Duke University whose lab creates next-generation spatial omics, imaging, biomaterials, and computational tools to map and engineer multicellular interactions in tissues. Hickey earned his PhD in Biomedical Engineering at Johns Hopkins and trained as a systems immunology postdoctoral fellow at Stanford. He has received major early-career honors, such as the NSF CAREER Award, V Foundation Scholar Award, HFSP Early Career Grant, and has been recently shortlisted for the oncology Takeda Innovator Award with Nature.
Zoom link (with one-time registration for the whole series) for attending remotely: https://go.epfl.ch/EPFLBioETalks
Instructions for 1st-year Ph.D. students planning to attend this talk, who are under EDBB’s mandatory seminar attendance rule:
IN CASE you cannot attend in-person in the room, please make sure to
Abstract:
Can we turn a biopsy into a tissue time machine? My lab combines spatial-omics, multiplexed imaging, machine learning, and agent-based modeling to ask how multicellular tissues are built, how they differ across disease, and how they change over time. We use machine learning to reconstruct tissue architecture and identify recurring organizational patterns, and mechanistic models to test how those patterns emerge and respond to perturbation. The long-term goal is to build virtual tissues that turn spatial biology from a descriptive map into a predictive framework.
Bio:
John Hickey is an Assistant Professor of Biomedical Engineering at Duke University whose lab creates next-generation spatial omics, imaging, biomaterials, and computational tools to map and engineer multicellular interactions in tissues. Hickey earned his PhD in Biomedical Engineering at Johns Hopkins and trained as a systems immunology postdoctoral fellow at Stanford. He has received major early-career honors, such as the NSF CAREER Award, V Foundation Scholar Award, HFSP Early Career Grant, and has been recently shortlisted for the oncology Takeda Innovator Award with Nature.
Zoom link (with one-time registration for the whole series) for attending remotely: https://go.epfl.ch/EPFLBioETalks
Instructions for 1st-year Ph.D. students planning to attend this talk, who are under EDBB’s mandatory seminar attendance rule:
IN CASE you cannot attend in-person in the room, please make sure to
- send Fiorella Ghisays a note well ahead of time (ideally before seminar day), informing that you plan to attend the talk online, and, during seminar:
- be signed in on Zoom with a recognizable user name (not any alias making it difficult or impossible to identify you).
Practical information
- Informed public
- Registration required
Organizer
- Prof. Maria Brbic, Machine Learning for Biomedicine Lab (MLBIO)
Contact
- Fiorella Ghisays, Institute of Bioengineering (IBI)