I am postdoc at the Department of Decision Sciences, Bocconi University since Sep 2024. Prior, I was postdoc at Laboratoire Jacques-Louis Lions (LJLL), Sorbonne Université. I completed my PhD in 2022 at the Department of Mathematics, Imperial College London, under the supervision of Greg Pavliotis and Nikolas Kantas.

Email: martin.chak (at) unibocconi.it

Research

Links: [Google scholar] [arxiv]

Preprints:

Chak M, 2024, On theoretical guarantees and a blessing of dimensionality for nonconvex sampling [arxiv]

Chak M, Lelièvre T, Stoltz G, Vaes U, 2023, Optimal importance sampling for overdamped Langevin dynamics [arxiv][hal]

Publications:

Chak M, Monmarché P, 2025, Reflection coupling for unadjusted generalized Hamiltonian Monte Carlo in the nonconvex stochastic gradient case, IMA J. Numer. Anal. [arxiv][journal]

Chak M, 2024, Regularity preservation in Kolmogorov equations for non-Lipschitz coefficients under Lyapunov conditions, Probab. Theory Related Fields [arxiv][journal][article]

Chak M, Kantas N, Lelièvre T, Pavliotis GA, 2023, Optimal friction matrix for underdamped Langevin sampling, M2AN Math. Model. Numer. Anal. [arxiv][hal][journal]

Chak M, Kantas N, Pavliotis GA, 2023, On the Generalised Langevin Equation for Simulated Annealing, SIAM/ASA J. Uncertain. Quantif. [arxiv][journal]

My PhD thesis can be found here.