Stochastic Particle Systems from Biology and Machine Learning
  • Home
  • Stochastic Particle Systems from Biology and Machine Learning

Stochastic Particle Systems from Biology and Machine Learning

Time:08:00:16/03/2026 to  17:00:18/03/2026

Venue/Location: Vietnam Institute for Advanced Study in Mathematics, 161 Chua Lang Street, Lang Ward, Hanoi

Objective: Stochastic interacting particle systems provide a powerful framework for describing aggregation, diffusion, and collective effects in both biological systems and modern machine learning. In mathematical biology, they arise in particular in stochastic Keller–Segel-type models and related chemotaxis systems, where singular interactions between particles can lead to pattern formation and blow-up phenomena. In machine learning, stochastic differential equations are central to diffusion-based models and sampling algorithms, motivating a detailed analysis of SDEs and their numerical discretisations, including stability properties and quantitative error estimates. This workshop aims to bring together researchers working on stochastic particle approximations, mean-field and propagation-of chaos limits, as well as the analysis of discretisation schemes for stochastic dynamics. By highlighting common analytical challenges, the workshop seeks to foster cross-fertilisation between stochastic models in mathematical biology and diffusion-driven methods in machine learning.

Expected participants: Researchers, graduate students, postgraduate students, and final-year students in Mathematics.

Organizing Committee

  • Le Minh Ha, Vietnam Institute for Advanced Study in Mathematics;
  • Ngo Hoang Long, Hanoi National University of Education, Vietnam;
  • Gaël Raoul, VIASM-CNRS, Ecole Polytechnique, France.

Scientific Committee

  • Marc Peigné, University of Tours, France;
  • Nguyen Huu Du, VNU University of Science, Hanoi, Vietnam.

Speakers & Lecturers

Speakers

  • Yoan Tardy, Ecole Polytechnique, France;
  • Le Tuyet Nhi Pham, Ecole Polytechnique, France;
  • Phan Thi Ha Duong, Institute of Mathematics, VAST, Vietnam;
  • Vincent Bansaye, Ecole Polytechnique, France ;
  • Huu Du Nguyen, VNU University of Science, Hanoi, Vietnam;
  • Hoang Long Ngo, Hanoi National University of Education, Vietnam;
  • Giovanni Conforti, Padova University, Italy .

Lecturer: Le Tuyet Nhi Pham, Ecole Polytechnique, France.

Meeting Format: Hybrid (Both in-person and online/The online meeting format is for participants outside of Hanoi only)

Language: English

General registration 

Contact: Mr. Le Dinh Hoang Giang, email: ldhgiang@viasm.edu.vn