FinRL-podracer: high performance and scalable deep reinforcement learning for quantitative finance. - Zechu Li; Xiao-Yang Liu; Jiahao Zheng 002; Zhaoran Wang 001; Anwar Walid; Jian Guo (ICAIF, 2021)

ElegantRL-Podracer: Scalable and Elastic Library for Cloud-Native Deep Reinforcement Learning. - Xiao-Yang Liu; Zechu Li; Zhuoran Yang; Jiahao Zheng 002; Zhaoran Wang 001; Anwar Walid; Jian Guo; Michael I. Jordan (CoRR, 2021)

Social Learning In Markov Games: Empowering Autonomous Driving. - Xu Chen 033; Zechu Li; Xuan Di (IV, 2022)

Parallel Q-Learning: Scaling Off-policy Reinforcement Learning under Massively Parallel Simulation. - Zechu Li; Tao Chen 046; Zhang-Wei Hong; Anurag Ajay; Pulkit Agrawal 001 (ICML, 2023)

Social Learning for Sequential Driving Dilemmas. - Xu Chen 033; Xuan Di; Zechu Li (Games, 2023)

Reconciling Reality through Simulation: A Real-To-Sim-to-Real Approach for Robust Manipulation. - Marcel Torne Villasevil; Anthony Simeonov; Zechu Li; April Chan; Tao Chen 046; Abhishek Gupta 004; Pulkit Agrawal 001 (Robotics: Science and Systems, 2024)

Learning Multimodal Behaviors from Scratch with Diffusion Policy Gradient. - Zechu Li; Rickmer Krohn; Tao Chen 046; Anurag Ajay; Pulkit Agrawal 001; Georgia Chalvatzaki (CoRR, 2024)

DIME:Diffusion-Based Maximum Entropy Reinforcement Learning. - Onur Celik; Zechu Li; Denis Blessing; Ge Li; Daniel Palanicek; Jan Peters 001; Georgia Chalvatzaki; Gerhard Neumann (CoRR, 2025)

Morphologically Symmetric Reinforcement Learning for Ambidextrous Bimanual Manipulation. - Zechu Li; Yufeng Jin; Daniel Felipe Ordoñez Apraez; Claudio Semini; Puze Liu; Georgia Chalvatzaki (CoRR, 2025)