Mathematics Webinar | Stochastics: Analysis and Statistics
Mathematics Webinar | Stochastics: Analysis and Statistics
Part of the MDPI Mathematics Webinars series
17 April 2026
Dirichlet Processes, Stochastic Differential Equations, Stochastic Partial Differential Equations, Attention-Style Models, FeynmanKac Formula, Bernsteinvon Mises Theorem, BerryEsseen Bound, Statistical Learning, Minimax Rate
Welcome from the Chair
23rd Mathematics Webinar
Stochastics: Analysis and Statistics
It is my great pleasure and privilege to welcome you to today’s webinar on “Stochastics: analysis and statistics”. I am honored to serve as the chair of this session and to facilitate the presentations and exchange of ideas on the current state of the art in this field and its related topics.
In recent times, with the help of AI, researchers can easily find the information they need for their research exploration. However, the inter-person exchange is still an indispensable way for our humanity to expand our knowledge boundaries. The webinar is one of the most effective and economic ways for this inter-person interaction. This webinar features three key talks presented by rising star experts. The topics range from the Bayesian nonparametrics, learning of single-layer attention-style models and further analysis of stochastic partial differential equations, including Dirichlet processes, stochastic differential equations, stochastic partial differential equations, Attention-Style Models, Feynman–Kac formula, Bernstein–von Mises theorem, Berry–Esseen bounds, statistical learning, minimax rate.
Audience are encouraged to raise questions and express opinions or any comments during and after each lecture.
Date: 17 April 2026
Time: 2:00 pm CEST | 8:00 am EDT
Webinar Secretariat: journal.webinar@mdpi.com
Event Chair
Department of Mathematical and Statistical Sciences, University of Alberta, Canada
Yaozhong Hu got his Ph.D in mathematics/probability in the University of Strasbourg, France in 1992 under the supervision of Paul Andre Meyer. He visited the University of Oslo, University of North Carolina at Chapel Hill, University of California at Irvine before joining University of Kansas 1997. In 2017, he moved to the University of Alberta at Edmonton as a centennial professor. His research areas cover a wide range of topics in probability theory, statistics, mathematical finance, stochastic control, mathematical physics. He was elected as a fellow of the institute of mathematical statistics in 2015.
Invited Speakers
Department of Mathematics & Statistics, Concordia University, Montreal, Canada
A Bernstein-von Mises Theorem for the Generalized Dirichlet Processes
Junxi Zhang got his Ph.D in statistics from the University of Alberta in 2023 and continued to stay in the University of Alberta for a postdoctoral position. He joined Concordia University, Montreal for a tenure track assistant professor position 2024. His research focuses on probability, random measures, Bayesian nonparametrics, trustworthy AI, and optimization in reinforcement learning. He published a sequence of papers in top journals including Bayesian Analysis, Canadian Journal of Statistics, Scientia Sinica Mathematica, NeurIPS, and AISTATS.
School of Mathematics and Statistics, Sun Yat-sen University, China
Minimax Rates for Learning Pairwise Interactions in Attention-Style Models
Xiong Wang got his Ph.D in Mathematics from the University of Alberta 2022 and joined John Hopkins University as J.J. Sylvester assistant professor from 2022 to 2025. He joined the Sun Yat-sen University as an associate professor 2025. Professor Wang’s research covers a wide range of topics in mathematics, including Statistical/Machine learning in complex dynamics; interacting particle systems; nonparametric inference of interaction kernel; Bayesian learning of kernel; random matrix theory, Stochastic partial differential equations and related stochastic heat equation; stochastic wave equation; stochastic fractional diffusion; super-Brownian motion; intermittency properties; KPZ universality, Gaussian processes, Sample path properties of Gaussian processes; Fractional Brownian motions; Talagrand’s Majorizing theorem; concentration inequality, numerical analysis, stability analysis; Euler–Maruyama scheme. He published nearly 20 papers in top mathematics and statistics journals.
School of Mathematics, Southern University of Science and Technology, China
Stochastic partial differential equations associated with Feller processes
Yuan completed his postdoctoral studies in the University of Ottawa in 2021–2022 and in the University of Luxemburg in 2022–2024. He is an assistant professor at Southern University of Science and Technology since 2024. Wangjun Yuan’s research covers a wide range of topics including Random matrix theory, free probability, Stochastic differential equations, Stochastic partially differential equations, Malliavin calculus, matrix-valued stochastic processes. He published about 20 papers in the top mathematical and probability journals.
Registration
This is a FREE webinar. After registering, you will receive a confirmation email containing information on how to join the webinar. Registrations with academic institutional email addresses will be prioritized.
Certificates of attendance will be delivered to those who attend the live webinar.
Can’t attend? Register anyway and we’ll let you know when the recording is available to watch.
Program
|
Speaker/Presentation |
Time in CEST |
Time in EDT |
|
MDPI Host Mathematics and Webinar Introduction |
14:00-14:05 |
8:00-8:05 |
|
Yaozhong Hu (Chair) Chair Introduction |
14:05-14:10 |
8:05-8:10 |
|
Junxi Zhang (Speaker 1) A Bernstein-von Mises Theorem for the Generalized Dirichlet Processes |
14:10-15:00 |
8:10-9:00 |
|
Xiong Wang (Speaker 2) Minimax Rates for Learning Pairwise Interactions in Attention-Style Models |
15:00-15:50 |
9:00-9:50 |
|
Wangjun Yuan (Speaker 3) Stochastic Partial Differential Equations Associated with Feller Processes |
15:50-16:40 |
9:50-10:40 |
|
Q&A |
16:40-16:55 |
10:40-10:55 |
|
Closing of Webinar Yaozhong Hu (Chair) |
16:55-17:00 |
10:55-11:00 |
Relevant Special Issue
Research Progress of Probability Statistics
Edited by Prof. Dr. Wanyang Dai
Deadline for manuscript submissions: 30 April 2026
Sponsors and Partners
Organizers
