I’m a third-year Ph.D. student at Boston University Center for Computing and Data Sciences where I’m fortunate to be advised by Aldo Pacchiano. Previously, I did my master in the Robotics Department at the University of Michigan. I also spent time in Honda Research Institute US as a Research Intern in Summer 2022

My research focuses on sequential decision-making, particularly in reinforcement learning and bandits. I am currently especially interested in two directions: (1) learning general decision-making and experimental design rules from offline datasets, and (2) developing continual-learning agents that perform well in non-stationary environments.

Manuscripts Under Review

• Yichen Song, Alessio Russo, Aldo Pacchiano, “Future Information-Directed Sampling for Bayesian Nonstationary Bandits”.

Publications

• Alessio Russo, Yichen Song, Aldo Pacchiano, Pure exploration with feedback graphs, International Conference on Artificial Intelligence and Statistics (AISTATS) 2025 (Oral presentation).
• Hongyu Zhou, Yichen Song, Vasileios Tzoumas, Safe non-stochastic control of control-affine systems: An online convex optimization approach, IEEE Robotics and Automation Letters (RA-L), 2023.