Sven Wang

I am an Assistant Professor (Juniorprofessor) at the Department of Mathematics of Humboldt University Berlin. I work in mathematical statistics and its intersections with analysis, data science, computation and PDE.

Research interests:

Email: sven.wang [at] hu-berlin [dot] de

Before joining HU Berlin, I was a postdoc at MIT (2021-2023) and obtained my PhD at Cambridge University (2021) under the supervision of Richard Nickl. From 2024-2029, I am elected member of the Junge Akademie which fosters interdisciplinary and societal dialogue. 

Google Scholar    CV (PDF)

Teaching: In the summer semester 2025, I am teaching Mathematical Statistics (Moodle page).

Seminars: I co-organize the WIAS Berlin Mathematical Statistics Seminar and the HU Mathematical Statistics Group seminar.

Research Group: Oleg Butkovsky (Postdoc, 2025-), Dennis Nieman (Postdoc, 2024-), Duc Ly Hoang (PhD student, 2025-)

Projects as (co-)PI:

News:

Papers and Preprints

[15] Statistical Learning Theory for Neural Operators (with N. Reinhardt and J. Zech)

Preprint (2024)

[14] Statistical algorithms for low-frequency diffusion data: A PDE approach (with M. Giordano)

Annals of Statistics, to appear

[13] Wasserstein-based Minimax Estimation of Dependence in Multivariate Regularly Varying Extremes (with X. Zhang, J. Blanchet, Y. Marzouk and V.A. Nguyen)

Preprint (2023)

[12] Distribution learning via neural differential equations: a nonparametric statistical perspective (with Y. Marzouk, R. Ren and J. Zech)

Journal of Machine Learning Research (2024)

[11] Manipulation-Robust selection of Citizens' Assemblies (with B. Flanigan and A. Procaccia)

Proceedings of AAAI (2024)

[10] Infinite-dimensional diffusion models for function spaces (with J. Pidstrigach, Y. Marzouk, S. Reich)

Journal of Machine Learning Research, to appear

[9] Voters with Stakes can Ward Off Bad Candidates (with B. Flanigan and A. Procaccia)

Foundations of Responsible Computing (2023)

[8] On free energy barriers in Gaussian priors and failure of MCMC for high-dimensional unimodal distributions (with A.S. Bandeira, A. Maillard, and R. Nickl)

Philosophical Transactions of the Royal Society A 381 (2023)

[7] Distortion under Public-Spirited Voting (with B. Flanigan and A. Procaccia)

Economics and Computation (2023)

[6] On minimax density estimation via measure transport (with Y. Marzouk)

Preprint (2022)

[5] Wasserstein Distributionally Robust Gaussian Process Regression and Linear Inverse Problems (with X. Zhang, J. Blanchet, Y. Marzouk, V.A. Nguyen)

Annals of Applied Probability, to appear

[4] Laplace priors and spatial inhomogeneity in Bayesian inverse problems (with S. Agapiou)

Bernoulli (2024)

[3] On polynomial-time computation of high-dimensional posterior measures by Langevin-type algorithms (with R. Nickl)

Journal of the European Mathematical Society (2024)

[2] Convergence rates for Penalised Least Squares estimators in PDE-constrained regression problems (with R. Nickl and S. van de Geer)

SIAM/ASA Journal of Uncertainty Quantification (2020)

[1] The nonparametric LAN expansion for discretely observed diffusions

Electronic Journal of Statistics (2019)

[A] Statistical inference and computation in PDE models

PhD thesis, University of Cambridge (2021)

Miscellanea

I love playing piano, singing and composing music. Some groups I've been lucky to be part of:

In former years, I was also very active outdoors.