Zhu, Qi

Professor

My recent research spans the algorithmsoftwareand hardware layers for building safesecureand robust foundation model-driven AI systemssafety-assured learning and system designmultimodal time-series learningcontinual learning

代表成果

Enhancing Inverse Reinforcement Learning through Encoding Dynamic Information in Reward Shaping, L4DC, 2026.
Belief-Based Offline Reinforcement Learning for Delay-Robust Policy Optimization, ICLR, 2026.
Directly Forecasting Belief for Reinforcement Learning with Delays, ICML, 2025.
Can We Trust Embodied Agents? Exploring Backdoor Attacks against Embodied LLM-based Decision-Making Systems, ICLR, 2025.
On Large Language Model Continual Unlearning, ICLR, 2025.
Empowering Autonomous Driving with Large Language Models: A Safety Perspective, https://arxiv.org/abs/2312.00812.
Variational Delayed Policy Optimization, NeurIPS, 2024. (Spotlight)
Boosting Reinforcement Learning with Strongly Delayed Feedback Through Auxiliary Short Delays, ICML, 2024.
Case Study: Runtime Safety Verification of Neural Network Controlled System, RV, 2024.
State-wise Safe Reinforcement Learning with Pixel Observations, L4DC, 2024.

数据校验于 9/6/2026数据来源

学生评价

还没有评价。成为第一位分享经验的学生吧。