Mission
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
Sampling
statistical sampling, data gathering, active learning, design of experiments, sequential design, reinforcement learning
Modeling
surrogate modeling, multi-fidelity modeling, deep learning, time series modeling
Optimization
Bayesian optimization, non-convex optimization, surrogate-based single and multi-objective optimization
Inverse Problems
likelihood-free parameter estimation, approximate Bayesian computation, learning summary statistics