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We study and advance the foundations of data-driven science and engineering.

We power scientific discovery, driven by AI and statistical science.

Recent News

– Feb 20, 2023: We have one open PostDoc position in our group in the area of constrained statistical design of experiments addressing fairness and bias in scientific experiments. Link to advertisement. [Position Filled]

– Mar 10, 2023: Thesis project available in collaboration with Prof. Stefano Moretti’s lab in the area of ML for High Energy Physics.

Research Areas


statistical sampling, data gathering, active learning, design of experiments, sequential design, reinforcement learning


surrogate modeling, multi-fidelity modeling, deep learning, time series modeling


Bayesian optimization, non-convex optimization, surrogate-based single and multi-objective optimization

Inverse Problems

likelihood-free parameter estimation, approximate Bayesian computation, learning summary statistics