Focus Period lund 2026
PhD Student
ETH Zurich and an ETH AI Center Fellow (Switzerland)
Ilyas Fatkhullin is a Ph.D. candidate in Computer Science at ETH Zurich and an ETH AI Center Fellow. His research lies at the intersection of optimization theory and reinforcement learning, developing principled methods for reliable learning in high-dimensional, non-convex, and stochastic settings, including hidden convexity, heavy-tailed noise, and communication-efficient distributed training. His work has appeared in venues such as NeurIPS, ICML, and AISTATS, and in journals including SIAM Journal on Optimization, SIAM Journal on Control and Optimization, and JMLR. Highlights include an oral presentation at NeurIPS 2021 (main track), a spotlight presentation at ICML 2022 (main track), and oral presentations at the NeurIPS 2025 OPT and COML workshops. He is an invited early-career scholar at the ELLIIT Focus Period Lund 2026.