Publications

 
 
 
 
 

Please check my Google Scholar:

Tutorials

(Research related)

 
 
 
 
 

October 2024: TutORial at INFORMS Annual Meeting, Seattle, USA

Course on “Machine Learning Methods for Large Population Games with Applications in Operations Research” with Gökçe Dayanıklı

 
 
 
 
 

February 2024: Tutorial at the AAAI conference, Vancouver, Canada

Course on “TH21: Scalability, Robustness, and Optimization of Learning in Large Stochastic Games” with Xin Guo

 
 
 
 
 

January 2024: Numerical methods for optimal transport problems, mean field games, and multi-agent dynamics, Universidad Técnica Federico Santa María (USM), Valparaíso, Chile

Course on “Learning methods in Mean Field Games

 
 
 
 
 

July 2023: Open Doctoral Lectures, University Mohammed VI Polytechnic’s Vanguard center (online)

Course on “Numerical Methods for Mean Field Games

  • Lecture 1 - Introduction: video and slides
  • Lecture 2 - Classical numerical methods: Part I: video and slides
  • Lecture 3 - Classical numerical methods: Part II: video and slides
  • Lecture 4 - Deep learning methods: Part I: video and slides
  • Lecture 5 - Deep learning methods: Part II: video and slides
  • Lecture 6 - Reinforcement learning methods: video and slides
 
 
 
 
 

December 2022: NYU Shanghai

Mini-course on “Introduction to Mean Field Games“: videos and slides
 
 
 
 
 

July-August 2021: Peking University (PKU) Summer School on Applied Mathematics (online)

Course on “Mean Field Games: numerical methods and applications in machine learning

  • Schedule of the summer school (2021年度北京大学“应用数学专题讲习班”) here
  • Part 1: Introduction and LQMFG
  • Part 2: Optimality conditions
  • Part 3: Numerical Schemes for MF PDE Systems
  • Part 4: Methods Based on the Probabilistic Approach
  • Part 5: Deep Learning for MFC and MKV FBSDE
  • Part 6: Deep Learning for MFG PDEs
  • Part 7: Mean Field Reinforcement Learning
  • Part 8: Learning in MFGs
  • Part 9: From MFG to ML: Three Examples
 
 
 
 
 

June 2021: Institute for Mathematical and Statistical Innovation (IMSI) (online)

Course on “Mean Field Games and Applications: Numerical Methods” (with Yves Achdou) for the summer school: Introduction to Mean Field Games and Applications
 
 
 
 
 

March 2021: King Abdullah University of Science and Technology (KAUST) (online)

Course on “Numerical Methods for Mean Field Games
 
 
 
 
 

January 2020: American Mathematical Society (AMS) Short Course (Denver, USA)

Course on “Numerical Methods for Mean Field Games

Codes

 
 
 
 
 

LQ MFG ODE solver

  • Colab notebook: click here
  • Linear-Quadratic Mean Field Game ODE system discretized with Euler scheme
  • Solved by fixed point, damped fixed point and Newton iterations
  • See references in the code
 
 
 
 
 

MFG PDE by finite difference scheme

  • Colab notebook: click here
  • Mean Field Game PDE system discretized by finite difference scheme
  • Solved by (damped) fixed point approach
  • See references in the code
 
 
 
 
 

MFG PDE by Semi-Lagrangian scheme

  • Colab notebook: click here
  • Mean Field Game PDE system discretized by finite difference scheme
  • Solved by (damped) fixed point approach
  • Congestion model
  • See references in the code
 
 
 
 
 

MFC by Deep Learning

  • Colab notebook: click here
  • Mean Field Control problem solved by a learning the control as a neural network
  • Price impact model
  • See references in the code
 
 
 
 
 

MKV FBSDE by Deep Learning

  • Colab notebook: click here
  • McKean-Vlasov FBSDE solved by deep learning
  • Systemic risk model
  • See references in the code
 
 
 
 
 

MFG PDE by Deep Learning

  • Colab notebook: click here
  • Mean Field Game PDE system solved by deep Galerkin method
  • See references in the code
 
 
 
 
 

Discrete MFC by Deep RL

  • Colab notebook: click here
  • Mean Field Control in discrete time and space solved by Deep Reinforcement Learning
  • Cybersecurity model
  • See references in the code
 
 
 
 
 

Introduction to OpenSpiel

  • Colab notebook: click here
  • Installation and imports; Creating a game; Running an algorithm; Visualizing the results
  • See references in the code
 
 
 
 
 

MFG in OpenSpiel: Comparing algorithms

  • Colab notebook: click here
  • Four room grid world
  • Several predefined algorithms
  • Exploitability computation
  • See references in the code
 
 
 
 
 

MFG in OpenSpiel: Game creation

  • Colab notebook: click here
  • Defining a game environment for MFG in OpenSpiel
 
 
 
 
 

Deep RL for MFG in OpenSpiel

  • Colab notebook: click here
  • Deep RL for MFG in OpenSpiel
  • Munchausen Deep Mirror Descent; Average Network Fictitious Play
 
 
 
 
 

Traffic routing MFG model in OpenSpiel

  • Github: click here
  • Traffic routing MFG model
  • Solved by Online Mirror Descent in OpenSpiel
 
 
 
 
 

Tabular and Deep RL for MFG in OpenSpiel

  • Github: click here
  • Comparison of tabular Q-learning and DQN for MFG
  • Implemented in OpenSpiel

Recent talks

 
 
 
 
 

2024 - Selected talks:

  • WONAPDE, Conception
  • Cornell University (SCAN seminar)
  • UT Dallas (Maths colloquium)
  • UC Santa Barbara (CFMAR seminar)
  • CISS conference, Princeton
  • NYU Abu Dhabi
  • University of International Business and Economics, Beijing
  • NTU, Singapore
  • ShanghaiTech, Shanghai
  • INRIA Saclay, H-CODE series
  • BIRS workshop (New Trends and Challenges in Stochastic Differential Games)
  • Bernoulli-IMS 11th World Congress in Probability and Statistics
  • North British Probability Seminar
  • INFORMS Annual meeting, Seattle
 
 
 
 
 

2023 - Selected talks:

  • Carnegie Mellon University, Pittsburgh (Probability/mathematical finance seminar)
  • Institute for Mathematical and Statistical Innovation (IMSI), Chicago
  • University of Illinois Urbana-Champaign, Champaign
  • Columbia University, New York (Applied probability seminar)
  • 11th Western Conference on Mathematical Finance, University of California, Berkeley
  • INFORMS APS meeting, Nancy
  • ICIAM, Tokyo
  • JP Morgan
  • Chennai mathematical institute (Statistical methods in finance)
 
 
 
 
 

2022 - Selected talks:

  • Institute for Mathematical and Statistical Innovation (IMSI), Chicago
  • SIAM Conference on Analysis of Partial Differential Equations (online)
  • Theory and numerics of Mean Field Games and Hamilton-Jacobi equations workshop, Rome, Italy
  • AMS-SMF-EMS Joint International Meeting, Grenoble, France
  • CEMRACS 2022, Marseille, France
  • INFORMS 2022 (online)
  • The University of Texas at Dallas (online)
 
 
 
 
 

2021 - Selected talks:

  • University of California, Santa Barbara (CFMAR seminar)
  • University of Chicago (CAMP seminar)
  • University Gustave Eiffel (Probability and Statistics seminar)
  • University of Oxford
  • ETH Zurich
  • NYU Shanghai
  • King Abdullah University of Science and Technology
  • Institute for Mathematical and Statistical Innovation (IMSI), Chicago, USA
  • Peking University, Summer School on Applied Mathematics
 
 
 
 
 

2020 - Selected talks:

  • Imperial College London
  • AMS Annual Meeting: Short course on Numerical aspects of MFG
  • MFG: Recent Progress workshop (U. Chicago)
  • Northwestern University (Probability seminar)
  • Joint Mathematics Meetings (Denver)
  • MFG Working Group (Paris)
  • UCLA (Optimal transport and Mean field game seminar)
  • INFORMS’20
  • 59th IEEE Conference on Decision and Control (CDC 2020)
  • Edinburgh University (North British Probability Seminar)
  • Linnaeus University (Stochastic analysis, statistics and machine learning DISA-LNU webinar)
  • Shanghai Jiaotong University (2020 Winter Young Mathematician Forum)
 
 
 
 
 

2019 - Selected talks:

  • SIAM PD’19
  • Chengdu (Southwestern University of Finance and Economics)
  • NYU Shanghai (Probability seminar)
  • Cornell University (SCAN seminar)
  • MFG and related topics 5 workshop (Levico Terme)
  • UC Berkeley
  • ICIAM’19
  • SIAM FM19
  • INFORMS’19
  • Columbia University (Mathematical Finance Seminar)
  • Google Brain, Paris
  • UC Santa Barbara (CFMAR seminar)
 
 
 
 
 

2018 - Selected talks:

  • Humboldt-Universität zu Berlin (Mathematical Finance Seminar)
  • 11th Oxford Princeton Workshop on Financial Mathematics and Stochastic Analysis (Princeton University)
  • ANR MFG days, University Paris 7
  • NYU-ECNU Institute of Mathematical Sciences (PDE seminar)
  • SIAM Annual Meeting, Mean Field Games session
  • INFORMS’18
 
 
 
 
 

2017 - Selected talks:

  • Analysis in Quantum Information Theory, IHP, Paris
  • CEMRACS17, CIRM, Marseille
  • Theory of Quantum Computation (TQC) conference, Paris
  • Second Paris-Asia Conference in Quantitative Finance, Suzhou
  • IQC, University of Waterloo
  • University of Michigan, Ann Arbor
  • 20th Quantum Information Processing conference (QIP)
  • 8th Innovations in Theoretical Computer Science conference (ITCS)
 
 
 
 
 

Before 2017 - Selected talks:

UCSB (CFMAR), U. Limoges (XLIM), Second Lions-Magenes Days, ICALP’15, ICITS’13, …

Contact

  • firstname_dot_lastname_at_nyu_dot_edu
  • NYU Shanghai