Dear Dr. Zhang,

I am an M.Sc. student in Electrical Engineering at Sharif University of Technology applying for PhD positions in reinforcement learning and stochastic control. Your work at the intersection of machine learning, stochastic games, and finance is closely aligned with the direction I want to pursue.

I completed Convex Optimization 1 with a grade of 20/20, providing a solid grounding in duality, nonsmooth analysis, and convergence-rate arguments that I consistently leverage in my research.

I read your research program on theoretically grounded reinforcement learning for single-agent and multi-agent settings with close attention—especially the emphasis on combining stochastic modeling with modern learning techniques for high-stakes decisions where reliability matters as much as performance. Given my background in duality and convergence analysis, I wondered whether such theoretically grounded principles could yield sample-efficiency guarantees for data-driven control in non-stationary environments. Would that direction fit within your research group?

I would appreciate knowing whether you expect to take PhD students next year. My CV and transcript are attached for your consideration. Thank you for your time.

Best regards,
[Candidate Researcher | Sharif University of Technology]