DREAM: Disease Reasoning, Experimentation, And Modelling

AI in disease biology has mostly been about classification. DREAM asks what comes next: how do we build AI scientists that construct, simulate, and revise mechanistic models of disease?

DREAM is a free, one-day workshop bringing machine learning and disease biology together.

Imagine “virtual cells,” “virtual brains,” and “virtual organisms,” models you can simulate, perturb, and question. Each one encodes testable hypotheses and drives a closed loop: model, predict, experiment, revise.

Why Attend 

• Meet ML researchers, biologists, and clinicians in one room
• Tackle real challenges, from tumour evolution to neurodegeneration
• Help shape the benchmarks, datasets, and standards for AI scientists in disease
• Push AI beyond predictions toward genuine mechanistic insight
• Showcase your research to field leaders in a dedicated poster session

Themes

AI Scientists and Mechanistic Model Construction: Methodological advances in agentic AI, foundation models, and generative dynamical systems for inferring mechanistic models from biological data

Disease Dynamics and Lab-in-the-Loop Biology: Application of these methods to disease processes, including tumour evolution, therapy resistance, neurodegeneration, and immune dynamics, and the design of closed-loop experimental systems.

Invited Speakers

• Maria Brbic (École Polytechnique Fédérale de Lausanne)
• Kristy Robledo (University of Sydney)
• Guy Wolf (Université de Montréal)
• John Lock (UNSW)
• Christine Chaffer (Garvan)