Publication and Preprint：
Stochastic process and Mathematical physics:
Central limit theorem for a partially observed interacting system of Hawkes processes I: subcritical case (joint with Liping Xu and An Zhang), submitted, 2026.
Scaling limits for supercritical nearly unstable Hawkes processes (joint with Liping Xu and An Zhang), Journal of Applied Probability, 2025.
How to beat a Bayesian adversary (joint with Zihan Ding, Kexin Jin, Jonas Latz), European Journal of Applied Mathematics, 2025.
Rate of convergence of the Kac particle system for the Boltzmann equation with hard potentials (joint with Liping Xu and An Zhang), submitted, 2024.
Convergence rates for Backward SDEs driven by Lévy processes (joint with Antonis Papapantoleon and Alexandros Saplaouras), submitted, 2024.
Statistical inference for a partially observed interacting system of Hawkes processes. Stochastic Processes and their Application, Volume 130 (2020), 5636-5694.
Mathematical machine learning:
Convergence of the generalization error for deep gradient flow methods for PDEs (joint with Antonis Papapantoleon and Jasper Rou), submitted, 2026.
Losing momentum in continuous-time stochastic optimisation (joint with Kexin Jin, Jonas Latz, and Alessandro Scagliotti), Journal of Machine Learning Research, 2025.
Subsampling Error in Stochastic Gradient Langevin Diffusions (joint with Kexin Jin and Jonas Latz), The 27th International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.
A continuous-time stochastic gradient descent method for continuous data (joint with Kexin Jin, Jonas Latz, and Carola-Bibiane Schönlieb), Journal of Machine Learning Research 24 (2023) 1-48.