The lab is focused on the algorithms and computation selected by evolution to perform biological decision-making. We address this topic with an interdisciplinary approach mixing statistical physics, Bayesian machine learning, information theory and various experimental biological setups. We are pursuing 4 research axis:
- Probabilistic pipelines and Artificial Intelligence to probe single biomolecule random walks
- Decision-making of biological system
- Amortized inference in Virtual Reality: DIVA + Genuage
- Numerical Methods for temporal networks
Expertise of the Team:
- Probabilistic pipelines for microscopy data analysis
- Virtual reality and augmented reality applied to visualisation and analysis
- Bayesian Inference, amortised inference and physics-based Bayesian induction.