Kun Lei

CS Ph.D. student at Washington University in St. Louis

I am a CS Ph.D. student at Washington University in St. Louis. Prior to this, I worked as a research assistant at Shanghai Qizhi institute, where I am fortunate to work with Prof. Huazhe Xu at Tsinghua University. Previously, I graduated from Southwest Jiaotong University, where I fortunately worked with Prof. Peng Guo at SWJTU and Prof. Yi Wang at Auburn University.

Research interest

I am currently focused on the post-training of robotics foundation models to enhance specific objectives such as acceleration, robustness, generalization, and precision. I am working on robotics, RL, and vision.

Previously, I conducted research on neural solvers for combinatorial optimization problems, i.e., in the field of AI for Operations Research. These neural agents have the potential to solve NP-hard problems with linear time complexity, see Zhihu.

Publications and preprints (Offline & online RL algorithms and robotics)

Papers sorted by recency, * indicates equal contribution.

Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization
Kun Lei, Zhengmao He*, Chenhao Lu*, Kaizhe Hu, Yang Gao, Huazhe Xu.
International Conference on Learning Representations (ICLR), 2024
with a nice rating 6688 / project page / arXiv / code / twitter
Behavior proximal policy optimization
Kun Lei*, Zifeng Zhuang*, Jinxin Liu, Donglin Wang, Yilang Guo.
International Conference on Learning Representations (ICLR), 2023
paper / arXiv / code
Learning Visual Quadrupedal Loco-Manipulation from Demonstrations
Zhengmao He, Kun Lei, Yanjie Ze, Koushil Sreenath, Zhongyu Li, Huazhe Xu.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024
proj page / arXiv

Publications and preprints (RL for Operations Research)

Papers sorted by recency.

Large-scale Dynamic Scheduling for Flexible Job-shop with Random New Job Arrival by Hierarchical RL. (This work has been featured as ESI Highly Cited Papers)
Kun Lei, Peng Guo, Yi Wang, Jian Zhang, Xiangyin Meng, Linmao Qian.
IEEE Transactions on Industrial Informatics (TII, IF: 11.7) , 2023
paper
Solve routing problems with a residual edge-graph attention neural network.
Kun Lei, Peng Guo, Yi Wang, Xiao Wu, Wenchao Zhao.
Neurocomputing, IF: 5.5, 2022
paper / code / covered by 运筹OR帷幄PaperWeekly

Misc. open-source projects

Behavior proximal policy optimization⭐ 54
Public code release for "BPPO", Feb 2023
code
End-to-end-DRL-for-FJSP.⭐ 168
Public code release for "A Multi-action Deep Reinforcement Learning Framework for Flexible Job-shop Scheduling Problem", Sep 2022
code
DRL-and-graph-neural-network-for-routing-problems.⭐ 112
Public code release for "Solve routing problems with a residual edge-graph attention neural network" June 2022
code
Dispatching-rules-for-FJSP.⭐ 54
Coed for dispatching rules for flexible job-shop scheduling problems", Sep 2022
code
FJSP-benchmarks.⭐ 27
The public benchmark instances of flexible job shop scheduling problem, Feb 2022
code
MIP-model-for-FJSP-and-solved-by-Gurobi.⭐ 17
Coed for solving MIP model using Gurobi", Feb 2022
code


I am from Si Chuan, China. My name in chinese is 雷坤. I used to live in the charming cities of Chengdu and Hangzhou in China. Currently, I live in the vibrant city of Shanghai (as depicted in the background picture).

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