Anas Barakat

Anas Barakat

Research Fellow

Singapore University of Technology and Design

I am currently a research fellow at Singapore University of Technology and Design working with Georgios Piliouras and Antonios Varvitsiotis.

My research interests lie in the span of optimization, multi-agent learning, and reinforcement learning. I am broadly interested in understanding and designing optimization and multi-agent learning algorithms for sequential decision-making motivated by machine learning, RL, and multi-agent RL applications using tools from stochastic approximation, optimization, game theory, and dynamical systems.

Previously, I was a postdoctoral fellow at ETH Zurich working with Niao He in the department of computer science. I obtained my PhD in applied mathematics and computer science from Institut Polytechnique de Paris at Télécom Paris under the supervision of Pascal Bianchi and Walid Hachem. I received my engineering Master’s degree in applied mathematics and computer science from Télécom Paris and a Master’s degree in data science from Université Paris Saclay.

You can find more information about me on my CV.

Interests

  • Optimization
  • Learning in Games
  • Reinforcement Learning
  • Stochastic Approximation

Education

  • PhD in Applied Mathematics and CS, 2021

    Institut Polytechnique de Paris (Télécom Paris)

  • MSc in Data Science, 2018

    Université Paris Saclay

  • MSc in Applied Mathematics and CS, 2018

    Télécom Paris

Research

Talks

Invited talk - 4th Symposium on Machine Learning and Dynamical Systems
Invited talk - ICCOPT 2022
Invited talk - 14th CMStatistics International Conference
Invited talk - Seminar of the 'Image, Optimization and Probabilities' (IOP) team
Talk - 2nd Symposium on Machine Learning and Dynamical Systems 2020

Reviewing

  • Journals: Journal of Machine Learning Research (JMLR), Mathematical Programming, SIAM Journal on Optimization (SIOPT), Journal of Optimization Theory and Applications (JOTA), Systems & Control Letters, Mathematics of Control, Signals, and Systems (MCSS), Stochastic Systems, IEEE Transactions on Automatic Control, IEEE Control Systems Letters, Transactions on Machine Learning Research (TMLR).

  • Conferences: NeurIPS, ICLR, ICML, COLT, AISTATS, IEEE CDC.

Teaching

ETH Zurich (2022-2024):

Télécom Paris (2018-2021): Teaching Assistant