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About me : I am maître de conférences (~associate professor) at CEREMADE, Paris Dauphine University – PSL, since 2020.
My research combines numerical probability and statistics for stochastic processes, with a particular focus on McKean–Vlasov equations, interacting particle systems, and learning-based methods. I also work on optimal quantization, k-means clustering, and other unsupervised learning techniques, with applications to high-dimensional and mean-field models. My work builds on tools from stochastic analysis, numerical methods, and statistical learning.
Before joining Dauphine, I completed my PhD in applied mathematics in 2019 at Sorbonne University under the supervision of Gilles Pagès (LPSM). I also held an ATER (~temporary teaching and research assistant) position at Dauphine before taking up my current position.
Office: F409. E-mail: liu 'at' ceremade.dauphine.fr
Publications and Preprints
Armand Bernou, Théophile Le Gall, Yating Liu. Convex order and increasing convex order for McKean-Vlasov processes with common noise, (2025). ArXiv:2504.17576.
Marc Hoffmann, Yating Liu. A statistical approach for simulating the density solution of a McKean-Vlasov equation, (2023). ArXiv:2305.06876.
Yating Liu. Particle method and quantization-based schemes for the simulation of the McKean-Vlasov equation, ESAIM: M2AN 58 (2) 571-612 (2024). ArXiv: 2212.14853.
Armand Bernou, Yating Liu. Particle method for the numerical simulation of the path-dependent McKean-Vlasov equation, (2022). ArXiv: 2211.03869v4.
Yating Liu, Gilles Pagès. Monotone convex order for the McKean-Vlasov processes, Stochastic Processes and their Applications (2022), ArXiv: 2104.10421.
Yating Liu, Gilles Pagès. Functional convex order for the scaled McKean-Vlasov processes, The Annals of Applied Probability 33, no. 6A (2023): 4491-4527. ArXiv:2005.03154v3.
Yating Liu, Gilles Pagès. Convergence Rate of Optimal Quantization Grids and Application to the Clustering Performance of the Empirical Measure, Journal of Machine Learning Research 21(86):1 - 36, 2020.
Yating Liu, Gilles Pagès. Characterization of probability distribution convergence in Wasserstein distance by $L^{p}$-quantization error function. Bernoulli 26, no. 2 (2020): 1171-1204.
Teaching
2023-2024
Probability 1, Tutorials, Bachelor's degree - 2nd year.
Monte Carlo Method, Lecture course (FR + EN), Master's Degree - 1st year.
2022-2023
Probability 1, Tutorials, Bachelor's Degree - 2nd year.
Statistical Learning, Lecture course, Master's Degree - 1st year.
Python/Pytorch project, Lecture course, Master's Degree Masef - 2nd year.
Before 2022 - [Click]
2021-2022
Probability 1, Tutorials, Bachelor's Degree - 2nd year.
Statistical Learning, Lecture course, Master's Degree - 1st year.
Python/Pytorch project, Lecture course, Master's Degree Masef - 2nd year.
2020-2021
Linear Algebra 2, Tutorials, Bachelor's Degree - 1st year.
Research project, Master's Degree - 1st year.
2019-2020
Multidimensional Probabilitys, Tutorials, Bachelor's Degree - 2nd year.
Numerical Methods: Optimization, Tutorials, and Practical Work, Bachelor's Degree - 3rd year.
2018-2019
Stochastic Modeling, Monte Carlo, and Simulation in R, Tutorials, 1st year at ISUP.
2017-2018
Measure Theory, Integration, and Probability, Tutorials, 1st year at ISUP.
2016-2017
Series of Functions, Parametric Integration, and Application to PDEs, Tutorials, Pierre and Marie Curie University, Bachelor's Degree - 2nd year.
Presentations
Jul 2025 - 44th Conference on Stochastic Processes and their Applications, Wroclaw, Poland.
Jun 2025 - DYNSTOCH workshop 2025, Institut du Risque et de l’Assurance, Le Mans, France.
Mar 2025 - Groupe de Travail Méthodes Stochastiques et Finance, École nationale des ponts et chaussées, Champs-sur-Marne, France.
Feb 2025 - Séminaire FDD-FiME-MiRTE, Institut Henri Poincaré, Paris, France.
Dec 2024 - Workshop Recent Progress in Mean-Field Dynamics, Lyon, France.
Nov 2024 - Séminaire de probabilités du LAGA, Université Sorbonne-Paris-Nord, Villetaneuse, France.
Oct 2024 - Séminaire parisien de statistique, Institut Henri Poincaré, Paris, France.
Sept 2024 - London-Paris Bachelier Workshop, Institut Henri Poincaré, Paris, France.
Jun 2024 - New Trends and Challenges in Stochastic Differential Games, Kelowna, BC, Canada.
Jun 2024 - New Directions for Stochastic Differential Equations and Machine Learning, ICMS, Bayes Centre, Edinburgh, UK.
Before 2024 - [Click]
Oct 2023 - Stochastic Analysis and Mathematical Finance Seminar, University of Oxford, UK.
Aug 2023 - 10th International Congress on Industrial and Applied Mathematics (ICIAM 2023), Waseda University, Tokyo, Japan.
Jul 2023 - 43rd Conference on Stochastic Processes and their Applications (SPA Conference), Lisbon, Portugal.
May 2022 - Journées de Probabilités 2022, Orbey, France.
Dec 2021 - Paris Bachelier Seminar, Institut Henri Poincare, Paris, France.
Sept 2021 - Advances in Stochastic Analysis for Handling Risks in Finance and Insurance, CIRM.
Jan 2021 - Méthodes Stochastiques et Finance seminar, ENPC-INRIA-Université de Marne-la-vallée.
Oct 2020 - Séminaire d’Analyse-Probabilités du Ceremade, Ceremade, Université Paris-Dauphine.
Apr 2020 - Séminaire de probabilités et mathématiques financières du LaMME, Université d’Évry.
Nov 2019 - Ceremade’s Young researcher seminar, Ceremade, Université Paris-Dauphine.
Oct 2019 - Finance mathématique, probabilité numériques et statistique des processus seminar, LPSM, Sorbonne Université.
Nov 2018 - Finance mathématique, probabilité numériques et statistique des processus seminar, LPSM, Sorbonne Université.
May 2017 - Finance mathématique, probabilité numériques et statistique des processus seminar, LPSM, Sorbonne Université.
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