I am currently a Ph.D. candidate at UC Davis with guidance from Prof. Lifeng Lai. My research interests lie in risk-sensitive reinforcement learning, including algorithm efficiency, sample complexity and robustness. In particular, I have developed risk-sensitive RL algorithms based on new risk measures. On the other hand, I have also explored risk-sensitive RL under different setups, including the reward-free framework and with human feedback.

I received the B.E. degree in Information Engineering from Zhejiang University, Hangzhou, China in 2019.

Publications

• Xinyi Ni, Guanlin Liu and Lifeng Lai. “Risk-Sensitive Reward-Free Reinforcement Learning with CVaR.” 2024 41st International Conference on Machine Learning (ICML). 2024. Paper
• Xinyi Ni and Lifeng Lai. “Robust Risk-Sensitive Reinforcement Learning with Conditional Value-at-Risk.” IEEE Information Theory Workshop (ITW) 2024. Paper
• Xinyi Ni and Lifeng Lai. “Policy Gradient Based Entropic-VaR Optimization in Risk-Sensitive Reinforcement Learning.” 2022 58th Annual Allerton Conference on Communication, Control, and Computing (Allerton). IEEE, 2022. Paper
• Xinyi Ni and Lifeng Lai. “Risk-sensitive reinforcement learning via Entropic-VaR optimization.” 2022 56th Asilomar Conference on Signals, Systems, and Computers. IEEE, 2022. Paper
• Xinyi Ni and Lifeng Lai. “EVaR Optimization for Risk-Sensitive Reinforcement Learning.” 2021. Paper

Academic Activities

Reviewer

• AAAI Conference on Artificial Intelligence
• IEEE Transactions on Mobile Computing

Workshop

• 2024 UCDavis ECExpo
• 2023 UCDavis ECExpo

Work Experience

• Researcher Intern at Xbox Gaming AI, Microsoft, 2024 Summer