| Alistarh group (ML/CS) | Distributed machine learning; Concurrent data structures and applications; Molecular computation |
| Bronstein group (ML/ENG) | Computational data-driven methods to tackle complex challenges in natural and life sciences and engineering. |
| Monika Henzinger Group (CS/DP) | Differentially private algorithms; clustering algorithms; combinatorial optimization. |
| Kolmogorov group (OPT) | Inference in graphical models; Combinatorial optimization problems; Theory of discrete optimization |
| Lampert group (ML/CV) | Trustworthy learning (robustness, explainability, fairness); Transfer learning (lifelong learning, continual learning, learning theory); Generative models of 3D scenes |
| Locatello Group (ML/AI) | Causal learning, deep learning methods and representation learning, object discovery and visual reasoning, AI for Science. |
| Mondelli group (ML/IT) | Fundamental limits and efficient algorithms for deep learning; Non-convex optimization in high-dimensions; Optimal code design for short block lengths |
| Robinson group (LS/ML) | Statistical models for the genetic basis of common complex disease; The genetic basis of age of onset; The genetics of ageing; Maternal health; Genomic prediction for personalized health |