Yingli Wang
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Yingli
Wang

Postdoctoral Fellow at the School of Mathematical Sciences, Fudan University. I work in applied probability, studying stochastic processes, Monte Carlo methods, and problems in financial mathematics.

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Portrait of Yingli Wang School of Mathematical Sciences · Fudan University
Applied probabilityShanghai, China
Current positionFudan University · Shanghai
Research homeApplied Probability
Academic backgroundPh.D., Shanghai University of Finance and Economics
01 / Research

Questions at the meeting point of probability and computation.

My work connects stochastic models with their scaling limits, numerical methods, and applications in quantitative finance.

01

Stochastic processes

Hawkes processes, heavy-tailed systems, limit theorems, and the emergence of rough dynamics.

02

Monte Carlo methods

Sampling algorithms, high-resolution dynamics, and their behavior in challenging probability landscapes.

03

Financial mathematics

Rough volatility models, scaling limits, hedging, and option pricing.

02 / Selected work

Publications & preprints

A selection of recent work. Author order and contribution notes follow the publication record.

2026

Accelerating constrained sampling: A large deviations approach

Wang, Y., Tu, C., Wang, X., and Zhu, L. · Journal of Machine Learning Research, 27(118):1–61

Journal article ↗First author
2026

Scaling limit of heavy-tailed nearly unstable cumulative INAR(∞) processes and rough fractional diffusions

Cai, C., He, P., Wang, Q., and Wang, Y. · Methodology and Computing in Applied Probability, 28(13)

DOI ↗Corresponding author · primary contributor
2026

Precise deviations for discrete marked Hawkes processes

Wang, Y. and He, P. · Communications in Statistics—Theory and Methods, 55(15):5040–5061

First author
2025

Rough Heston model as the scaling limit of bivariate cumulative heavy-tailed INAR processes: Weak-error bounds and option pricing

Wang, Y., Cui, Z., and Zhu, L. · SIAM Journal on Financial Mathematics

arXiv:2503.18259 ↗To appear · first author
2026

A Hawkes microfoundation for multitype inverse Gaussian subordinators

Wang, Y., Xu, W., and Zhu, L. · Preprint

arXiv:2610.10525 ↗Preprint
2026

Global convergence of third-order Langevin dynamics for non-convex optimization via simulated annealing

Wang, Y. and Zhu, L. · Preprint

arXiv:2609.28611 ↗Preprint
2026

Variance-optimal hedging in the rough Hawkes–Heston model

Wang, Y. and Wang, X. · Preprint

arXiv:2609.08541 ↗Preprint
03 / CV

Curriculum vitae

For my full academic background, appointments, publications, and teaching experience, download my CV.

Full academic CV

PDF · Updated November 2026

Download CV (PDF)
Contact

Let’s talk about probability.

Email Yingli ↗ GitHub ↗