معرفی
Alexander Olshevsky is a Professor in the Department of Electrical and Computer Engineering and Systems Engineering at Boston University. He holds a PhD from MIT (2010) and is affiliated with the Hariri Institute and the Intelligent, Autonomous & Secure Systems group. His research focuses on reinforcement learning, distributed optimization for machine learning, control systems, and network science, with applications to epidemic control and federated learning.
Key achievements include the NSF CAREER Award (2014), AFOSR Young Investigator Award (2015), and the SIAM SIGEST Selection (2011). His work bridges theoretical foundations in control systems and machine learning, with recent emphasis on distributed algorithms and their convergence properties.
Publications span topics like MDP analysis, sample complexity in LQR systems, and network-based epidemic control. He leads projects funded by NSF and AFOSR, including federated learning for energy consumption prediction and sparse control algorithms. His interdisciplinary collaborations involve systems engineering, computer science, and public health domains.
