Xujie Song

M.Phil

Tsinghua University

Biography

I am an M.Phil graduated from the Intelligent Driving Lab (iDLab), Tsinghua University, working with Prof. Shengbo Li and Prof. Bo Cheng. Currently, my research covers neural network, reinforcement learning, autonomous driving and quantum computing. I have been committed to building more intelligent and safer AI for the decision-making and control of automated vehicles, and to developing the next generation of diagram for neural network training.

Interests

Neural Network
Reinforcement Learning
Autonomous Driving
Quantum Computing

Education

Tsinghua University, 2021-2024
M.Phil in Vehicle Engineering
Minor in Big Data (certificate program)
Delft University of Technology, 2017-2021
Joint Education Program
Beijing Jiaotong University, 2017-2021
B.Eng in Traffic and Transportation
B.Eng in Computer Science and Technology (dual degree)

Experiences

Research Assistant

Tsinghua University

June 2024 – Present Beijing

Research Intern

QBosoN Ltd.

February 2024 – July 2024 Beijing

Research Intern

Alibaba Group Ltd.

July 2023 – September 2023 Beijing

Research Intern

MEGVII Technology Ltd.

March 2022 – January 2023 Beijing

Research Intern

ProbQuant Ltd.

January 2022 – February 2022 Beijing

Research Intern

SenseTime Group Inc.

June 2021 – August 2021 Shanghai

Featured Publications

Xujie Song, Tong Liu, Jingliang Duan, Wenxuan Wang, Yin Ma, Hai Wei, Kai Wen, Shengbo Eben Li

September, 2024 Nature Computational Science (NCS), 2024 (under review)

Training Multilayer Neural Networks on Ising Machines

We proposed Ising learning algorithm, the first technique to train multilayer feedforward neural networks on Ising machines (quantum computers). The training time is reduced by 90% compared to CPU/GPU.

Wenxuan Wang, Jingliang Duan, Xujie Song, Liming Xiao, Liangfa Chen, Yinuo Wang, Bo Cheng, Shengbo Eben Li

August, 2024 IEEE Transactions on Intelligent Vehicles (TIV), 2024

Smooth Filtering Neural Network for Reinforcement Learning

We proposed a policy network for RL with low-pass filtering ability, named Smonet, to alleviate the action nonsmoothness issue by learning a low-frequency representation within hidden layers.

Yinuo Wang, Wenxuan Wang, Xujie Song, Tong Liu, Yuming Yin, Liangfa Chen, Likun Wang, Jingliang Duan, Shengbo Eben Li

May, 2024 Annual Conference on Neural Information Processing Systems (NeurIPS), 2024 (under review)

Smoothing Neural Network with Adaptive Liquid Time-constant for Reinforcement Learning Tasks

we proposed a variant of neural ODE, called ALTC network, to smooth out control actions in RL. A mapping function is incorporated to estimate the changing speed of system dynamics.

Liangfa Chen*, Xujie Song*, Wenxuan Wang, Yinuo Wang, Liming Xiao, Junjie Zhao, Shengbo Eben Li, Fei Ma, Jingliang Duan

February, 2024 IEEE Transactions on Intelligent Transportation Systems (TITS), 2024 (under review)

A Smooth Reinforcement Learning Method for Trajectory Tracking and Collision Avoidance of Wheeled Vehicle

We proposed a smooth policy network (LipsNeXt) and a smooth distributed soft actor-critic (DSAC-S) algorithm to achieve coordinated optimization of control precision and action smoothness.

Xujie Song, Jingliang Duan, Wenxuan Wang, Shengbo Eben Li, Chen Chen, Bo Cheng, Bo Zhang, Junqing Wei, Xiaoming Simon Wang

July, 2023 International Conference on Machine Learning (ICML), 2023

LipsNet: A Smooth and Robust Neural Network with Adaptive Lipschitz Constant for High Accuracy Optimal Control

We proposed LipsNet, a smooth and robust neural network with adaptive Lipschitz constant, to deal with the action fluctuation problem in RL (reinforcement learning).

Xujie Song, Zexi Lin

February, 2023 arXiv preprint, 2023

Non-zero-sum Game Control for Multi-vehicle Driving via Reinforcement Learning

This paper constructs the multi-vehicle driving scenario as a non-zero-sum game and proposes a novel game control framework, which consider prediction, decision and control as a whole.

Publications

Xujie Song, Tong Liu, Jingliang Duan, Wenxuan Wang, Yin Ma, Hai Wei, Kai Wen, Shengbo Eben Li. Training Multilayer Neural Networks on Ising Machines. Nature Computational Science (NCS), 2024 (under review).

PDF

Wenxuan Wang, Jingliang Duan, Xujie Song, Liming Xiao, Liangfa Chen, Yinuo Wang, Bo Cheng, Shengbo Eben Li. Smooth Filtering Neural Network for Reinforcement Learning. IEEE Transactions on Intelligent Vehicles (TIV), 2024.

PDF Video

Yinuo Wang, Wenxuan Wang, Xujie Song, Tong Liu, Yuming Yin, Liangfa Chen, Likun Wang, Jingliang Duan, Shengbo Eben Li. Smoothing Neural Network with Adaptive Liquid Time-constant for Reinforcement Learning Tasks. Annual Conference on Neural Information Processing Systems (NeurIPS), 2024 (under review).

Liangfa Chen*, Xujie Song*, Wenxuan Wang, Yinuo Wang, Liming Xiao, Junjie Zhao, Shengbo Eben Li, Fei Ma, Jingliang Duan. A Smooth Reinforcement Learning Method for Trajectory Tracking and Collision Avoidance of Wheeled Vehicle. IEEE Transactions on Intelligent Transportation Systems (TITS), 2024 (under review).

Shengbo Eben Li, Xujie Song, Tong Liu, Jingliang Duan, Wenxuan Wang, Bo Cheng. A Method for Training Feedforward Neural Network on Ising Machine. Patent, No. 2023113797497, 2023 (under review).

Liangfa Chen*, Xujie Song*, Liming Xiao, Lulu Gao, Fawang Zhang, Shengbo Eben Li, Fei Ma, Jingliang Duan. Smooth Reinforcement Learning Based Trajectory Tracking for Articulated Vehicles. Journal of Harbin Institute of Technology, 2023.

Xujie Song, Jingliang Duan, Wenxuan Wang, Shengbo Eben Li, Chen Chen, Bo Cheng, Bo Zhang, Junqing Wei, Xiaoming Simon Wang. LipsNet: A Smooth and Robust Neural Network with Adaptive Lipschitz Constant for High Accuracy Optimal Control. International Conference on Machine Learning (ICML), 2023.

PDF Code Poster Video

Xujie Song, Zexi Lin. Non-zero-sum Game Control for Multi-vehicle Driving via Reinforcement Learning. arXiv preprint, 2023.

PDF Code

Shengbo Eben Li, Wenxuan Wang, Zhilong Zheng, Congsheng Zhang, Yujie Yang, Yuhang Zhang, Jiaxin Gao, Jie Li, Xujie Song, Tong Liu. Offline Simulation System for the General Optimal Control Problem Solver (V2.0). Software Copyright, No. 2023SR0225863, 2023.

Code Docs

Xujie Song, Sunhao Dai, Chunyu Lin, Shutao Zhan, Yao Zhao. LiDAR Data Enhancement via Pseudo-LiDAR Point Cloud Correction. Journal of image and Graphics (JIG), 2021.

PDF Code

Chunyu Lin, Xujie Song, Sunhao Dai, Shutao Zhan. A Method and Device for 3D Point Cloud Densification Based on Stereo RGB Images. Patent, No. CN111612728B, 2020.