Scholar
Anas Barakat
Google Scholar ID: 5YyyWPkAAAAJ
Research Fellow, Singapore University of Technology and Design
Citations & Impact
Citations
350
H-index
7
i10-index
7
Publications
15
Co-authors
15
list available
Publications
Resume (English only)
Academic Achievements
- Paper 'On the Global Optimality of Policy Gradient Methods in General Utility Reinforcement Learning' accepted to NeurIPS 2025 (Sep. 2025).
- Published multiple papers in top-tier venues including NeurIPS, ICML, AISTATS, IEEE CDC, and SIAM Journal on Control and Optimization.
- Key contributions in multi-agent reinforcement learning, learning in Markov games, online learning in games, general utility RL, and global optimality of policy gradient methods.
- Served as corresponding author (e.g., IEEE CDC 2024 paper).
- Several papers under review (e.g., 'Online Multi-Agent Control with Adversarial Disturbances', 'Optimistic Online Learning in Symmetric Cone Games').
