Biography

Shaocong Ma is a postdoctoral researcher at UMIACS, working under the supervision of Professor Heng Huang. He received his Ph.D. in Electrical and Computer Engineering from the University of Utah, where he was advised by Professor Yi Zhou. Previously, he completed an M.A. in Statistics at the University of California, Santa Barbara, and earned his B.S. in Statistics at Sichuan University.

For more information, refer to his CV (PDF) or research statement.

📊 Research Interests

• Optimization & RL Theory: I design robust, efficient, and scalable algorithms for reinforcement learning and large-scale optimization, with a focus on their sample efficiency, convergence guarantees, and distributional robustness.

• AI for Science: I previously collaborated with researchers at Lawrence Livermore National Laboratory to integrate deep learning with traditional scientific computing software. I am currently extending this line of research at UMD, focusing on addressing non-differentiability in scientific pipelines using modern machine learning techniques.

🔥 News

• 2025.04: Best Reviewer Award by AISTATS 2025!
• 2025.02: One paper selected as a spotlight by ICLR 2025!
• 2024.06: Joined UMD as a postdoctoral researcher.