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Programme

All talk slots include time for discussion.

  • Standard talks: 25 min presentation + 5 min Q&A
  • Short talks: 15 min presentation + 5 min Q&A
  • Shared talks: 20 min combined presentation + 10 min Q&A

29 September 2026

Time Session
09:30–10:00 Registration
10:00–10:10 Opening remarks
10:10–10:40 Dr. Alessandro Bonetti
Therapeutic discovery and industry perspectives
10:40–11:10 Dr. Mikhail Kabeshov
Therapeutic discovery and industry perspectives
11:10–11:40 Coffee break
11:40–12:10 Fabio Bove + Marco Ferrarini
AI-driven therapeutic discovery
12:10–12:40 Dr. Gabriele Corso
Generative models and biological design
12:40–13:10 Dr. Esther Wershof
Machine learning for cell-state biology
13:10–14:10 Lunch
14:10–14:40 Dr. Fabian Frohlich
Disease modelling and cellular systems
14:40–15:10 Dr. Michail Mamalakis
From Genes to Brain Imaging: Interpretable and Adaptable AI for Understanding Brain Disease
15:10–15:40 Dr. Tiansi Dong
Foundation models and representation learning
15:40–16:10 Coffee break
16:10–16:40 Dr. Larry Melidis
Computational biology and therapeutic discovery
16:40–17:10 Dr. Anurag Limdi
Machine learning for molecular and biomedical data
17:10–17:40 Tom McClelland
The Problem of Artificial Consciousness
17:40–18:00 General discussion / wrap-up

30 September 2026

Time Session
09:30–09:50 Dr. Johann Hawe
Machine learning for biomedical data
09:50–10:10 Dr. Ilaria Billato
Single-cell and multimodal data analysis
10:10–10:30 Dr. Bianca Pierattini
Cell-state modelling and biological regulation
10:30–11:00 Coffee break
11:00–11:20 Dr. Tania Bobbo
Machine Learning for Probiotics Discovery: The PROB-AI Project
11:20–11:40 Dr. Davide Rigoni
Omics data analysis and biological modelling
11:40–12:00 Flavio Sartori
Scoring Tissue Health from Microscopy to Enable Causal Analysis in Dry AMD
12:00–13:00 Lunch
13:00–13:20 Matteo Baldan
Learning to Simulate: Neural Operators and the Generation of Physical Dynamics with Applications in Cardiac Electrophysiology
13:20–13:40 Massimiliano Caretti
Title to be announced
13:40–14:00 Andrea G. Di Francesco
RAG Beyond NLP: Learning Relevant Context for Cellular Prediction
14:00–14:20 David Miller
Emerging research talk
14:20–14:40 Salvatore Romano
Emerging research talk
14:40–15:10 Coffee break
15:10–15:30 Andrea Rubbi
Emerging research talk
15:30–15:50 Wageesha Widuranga
Emerging research talk
15:50–16:20 Discussion: future directions in generative models for therapeutic discovery
16:20–16:35 Closing remarks

Generative Models for Therapeutic Discovery

University of Cambridge · Computer Laboratory · 29–30 September 2026

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