|
Assistant professor (Juniorprofessor) Department of mathematics Humboldt University Berlin Email: sven.wang [at] hu-berlin [dot] de Research interests:
|
Before joining HU Berlin, I was a postdoc at MIT (2021-2023). I obtained my PhD at Cambridge University (2021) under the supervision of Richard Nickl. Here's my CV.
Together with Alexandra Carpentier, Sonja Greven, Markus Reiß and Vladimir Spokoiny, I co-organize the Mathematical Statistics Seminar at WIAS Berlin.
I'm delighted that I was elected to join the Junge Akademie from summer 2024, a scientific academy for young scholars and artists, with the goal of fostering interdisciplinary and societal dialogue. Looking forward to five exciting years!
NEWS
Together with Alexandra Carpentier, Sonja Greven, Markus Reiß and Vladimir Spokoiny, I co-organize the Mathematical Statistics Seminar at WIAS Berlin.
I'm delighted that I was elected to join the Junge Akademie from summer 2024, a scientific academy for young scholars and artists, with the goal of fostering interdisciplinary and societal dialogue. Looking forward to five exciting years!
NEWS
- July 2024 (PhD openings): There will be two openings for PhD positions in the DFG special priority program 'Foundations on Deep Learning'. We are looking for two excellent candidates in Heidelberg and Berlin. If you are interested, please contact me for more information.
- January 2024 (Postdoc opening): There is currently an opening for a two-year postdoctoral position in our group at HU Berlin. The position is part of the MATH+ Excellence Cluster in Berlin. If you're interested in working with me and at HU Berlin, please apply here.
- January 2024: I'll soon be speaking at SMSA (Delft, 2024/03), Oberwolfach (2024/05), ECM 2024 (Sevilla, 2024/07), Bernoulli world congress (Bochum, 2024/08).
Publications and preprints
[14] Statistical algorithms for low-frequency diffusion data: A PDE approach
M. Giordano and S. Wang
Preprint (2024)
[13] Wasserstein-based Minimax Estimation of Dependence in Multivariate Regularly Varying Extremes
X. Zhang, J. Blanchet, Y. Marzouk, V.A. Nguyen and S. Wang
Preprint (2023)
[12] Distribution learning via neural differential equations: a nonparametric statistical perspective
Y. Marzouk, R. Ren, S. Wang and J. Zech
Journal of Machine Learning Research 25 (232), 1-61 (2024)
[11] Manipulation-robust selection of citizens' assemblies
B. Flanigan, A. Procaccia and S. Wang
Proceedings of AAAI (2024, selected for oral presentation)
[10] Infinite-dimensional diffusion models for function spaces
J. Pidstrigach, Y. Marzouk, S. Reich and S. Wang
Preprint (2023)
[9] Accounting for stakes in democratic decisions
B. Flanigan, A. Procaccia and S. Wang
Foundations of Responsible Computing (FORC 2023)
[8] On free energy barriers in Gaussian priors and failure of MCMC for high-dimensional unimodal distributions
A.S. Bandeira, A. Maillard, R. Nickl and S. Wang
Philosophical Transactions of the Royal Society A 381 (2023)
[7] Distortion under Public-Spirited Voting
B. Flanigan, A. Procaccia and S. Wang
Economics and Computation (EC) (2023)
[6] On minimax density estimation via measure transport
S. Wang and Y. Marzouk
Preprint (2022)
[5] Wasserstein Distributionally Robust Gaussian Process Regression and Linear Inverse Problems
X. Zhang, J. Blanchet, Y. Marzouk, V.A. Nguyen and S. Wang
Preprint (2022)
[4] Laplace priors and spatial inhomogeneity in Bayesian inverse problems
S. Agapiou and S. Wang
Bernoulli 30(2) 878-910 (2024)
[3] On polynomial-time computation of high-dimensional posterior measures by Langevin-type algorithms
R. Nickl and S. Wang
Journal of the European Mathematical Society 26, 1031-1112 (2024)
Link to EMS online publication
[2] Convergence rates for Penalised Least Squares estimators in PDE-constrained regression problems
R. Nickl, S. van de Geer and S. Wang
SIAM/ASA Journal of Uncertainty Quantification 8, 374-413 (2020)
[1] The nonparametric LAN expansion for discretely observed diffusions
S. Wang
Electronic Journal of Statistics 13, 1329-1358 (2019)
[A] Statistical inference and computation in PDE models
S. Wang
PhD thesis, University of Cambridge (2021)
M. Giordano and S. Wang
Preprint (2024)
[13] Wasserstein-based Minimax Estimation of Dependence in Multivariate Regularly Varying Extremes
X. Zhang, J. Blanchet, Y. Marzouk, V.A. Nguyen and S. Wang
Preprint (2023)
[12] Distribution learning via neural differential equations: a nonparametric statistical perspective
Y. Marzouk, R. Ren, S. Wang and J. Zech
Journal of Machine Learning Research 25 (232), 1-61 (2024)
[11] Manipulation-robust selection of citizens' assemblies
B. Flanigan, A. Procaccia and S. Wang
Proceedings of AAAI (2024, selected for oral presentation)
[10] Infinite-dimensional diffusion models for function spaces
J. Pidstrigach, Y. Marzouk, S. Reich and S. Wang
Preprint (2023)
[9] Accounting for stakes in democratic decisions
B. Flanigan, A. Procaccia and S. Wang
Foundations of Responsible Computing (FORC 2023)
[8] On free energy barriers in Gaussian priors and failure of MCMC for high-dimensional unimodal distributions
A.S. Bandeira, A. Maillard, R. Nickl and S. Wang
Philosophical Transactions of the Royal Society A 381 (2023)
[7] Distortion under Public-Spirited Voting
B. Flanigan, A. Procaccia and S. Wang
Economics and Computation (EC) (2023)
[6] On minimax density estimation via measure transport
S. Wang and Y. Marzouk
Preprint (2022)
[5] Wasserstein Distributionally Robust Gaussian Process Regression and Linear Inverse Problems
X. Zhang, J. Blanchet, Y. Marzouk, V.A. Nguyen and S. Wang
Preprint (2022)
[4] Laplace priors and spatial inhomogeneity in Bayesian inverse problems
S. Agapiou and S. Wang
Bernoulli 30(2) 878-910 (2024)
[3] On polynomial-time computation of high-dimensional posterior measures by Langevin-type algorithms
R. Nickl and S. Wang
Journal of the European Mathematical Society 26, 1031-1112 (2024)
Link to EMS online publication
[2] Convergence rates for Penalised Least Squares estimators in PDE-constrained regression problems
R. Nickl, S. van de Geer and S. Wang
SIAM/ASA Journal of Uncertainty Quantification 8, 374-413 (2020)
[1] The nonparametric LAN expansion for discretely observed diffusions
S. Wang
Electronic Journal of Statistics 13, 1329-1358 (2019)
[A] Statistical inference and computation in PDE models
S. Wang
PhD thesis, University of Cambridge (2021)
Invited conference talks (upcoming & past):
SIAM Conference on Computational Science and Engineering (2023/02)
Statistics for Stochastic Processes: SDEs, SPDEs and concentration of measure (2022/09)
ESI Vienna workshop "Statistical estimation and deep learning in UQ for PDEs" (2022/05, link to program)
AMS Sectional meeting (2022/05, link to program)
BNP workshop Cyprus (2022/04, link to program)
SIAM Conference on Uncertainty Quantification (2022/04)
Oberwolfach "Data Assimilation -- Mathematical Foundation and Applications" (2022/02)
BANFF "Statistical Aspects of Non-Linear Inverse Problems" (link to video)
Oberwolfach "Foundations of Bayesian Inference for Complex Statistical Models"
DPMMS Cambridge workshop "Mathematical and Statistical challenges in Uncertainty Quantification" (link to video)
Selected seminar talks: UMass Amherst (2022/03); WIAS, Berlin (2021/01, 2020/01); University of Chicago (2020/10); ETH Zurich YDSSZ seminar (2020/07); Caltech (2020/01); CREST Paris (2019/11); U of Sussex (2019/10)
SIAM Conference on Computational Science and Engineering (2023/02)
Statistics for Stochastic Processes: SDEs, SPDEs and concentration of measure (2022/09)
ESI Vienna workshop "Statistical estimation and deep learning in UQ for PDEs" (2022/05, link to program)
AMS Sectional meeting (2022/05, link to program)
BNP workshop Cyprus (2022/04, link to program)
SIAM Conference on Uncertainty Quantification (2022/04)
Oberwolfach "Data Assimilation -- Mathematical Foundation and Applications" (2022/02)
BANFF "Statistical Aspects of Non-Linear Inverse Problems" (link to video)
Oberwolfach "Foundations of Bayesian Inference for Complex Statistical Models"
DPMMS Cambridge workshop "Mathematical and Statistical challenges in Uncertainty Quantification" (link to video)
Selected seminar talks: UMass Amherst (2022/03); WIAS, Berlin (2021/01, 2020/01); University of Chicago (2020/10); ETH Zurich YDSSZ seminar (2020/07); Caltech (2020/01); CREST Paris (2019/11); U of Sussex (2019/10)
Music & Miscellanea
I love playing piano, singing and composing music. Some groups I've been lucky to be part of:
I also love being outdoors.
- Cambridge's Pembroke lieder scheme, where I studied with Joseph Middleton
- Munich Bach choir
- MIT Chamber Music Society
- Kammermusikkreis Unterwachingen
- Michael Schopper, my mentor and singing teacher
- Here is me playing some late Schubert in 2019, recorded in Trinity College Chapel
I also love being outdoors.
- In 2015, I biked through 22 European countries for 6 months (with my very good friend Niklas from Berlin). We paired our trip with a fundraising project towards medical care for refugees from the war in Syria, which has completely disappeared from the news but is unfortunately still timely.
- In 2012, my friend Nick came up with the glorious idea of hiking across the alps with a donkey (named Thomas) from our German hometown Aschaffenburg to the Mediterranean Sea in Italy. It was truly life-changing for 16-year-old me. Thomas had a solar panel on his back, and we funded our trip by playing the accordion in the streets. We were (unintentionally) discovered by the Italian media -- they must have had a summer drought of stories to report about.
