Chengshu (Eric) Li
I am currently a third-year Ph.D. student in Computer Science at Stanford University. I am advised by Prof. Fei-Fei Li and Prof. Silvio Savarese at the Stanford Vision and Learning Lab. My research interest lies at the intersection of robot learning and computer vision.
I received my B.S. in Computer Science with Distinction from Stanford University in 2017 and M.S. in Management Science & Engineering from Stanford University in 2020. In the past, I've worked/interned at Nvidia (2022-2023), Google Brain Robotics (2019-2020), AutoX (2017-2018), Shift (2016), and Tableau (2015).
Email: chengshu@stanford.edu
CV | Google Scholar | LinkedIn
News
2022/09/10: Our paper BEHAVIOR-1K: A Benchmark for Embodied AI with 1,000 Everyday Activities and Realistic Simulation is accepted at CoRL 2022 and nominated for best paper!
2021/09/13: Our papers BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments and iGibson 2.0: Object-Centric Simulation for Robot Learning of Everyday Household Tasks are accepted at CoRL 2021!
2021/06/30: Our paper iGibson 1.0: a Simulation Environment for Interactive Tasks in Large Realistic Scenes is accepted at IROS 2021!
2021/06/20: We concluded the iGibson Challenge 2021 and the CVPR2021 Embodied AI Workshop. Check out our video for the challenge and the panel discussions that I was a part of.
2021/02/28: Our paper ReLMoGen: Leveraging Motion Generation in Reinforcement Learning for Mobile Manipulation is accepted at ICRA 2021!
2021/02/17: We launched the iGibson Challenge 2021 at the CVPR2021 Embodied AI Workshop! We featured Interactive and Social Navigation in dynamic environments in iGibson.
Education
Stanford University
Ph.D. Candidate in Computer Science
2020/09 - Present
Stanford, CA
Stanford University
Master of Science in Management Science and Engineering
2019/01 - 2020/06
Stanford, CA
GPA: 4.0 / 4.0
Stanford University
Bachelor of Science in Computer Science with Distinction
2013/09 - 2017/06
Stanford, CA
GPA: 3.93 / 4.0
Publications (First-Author/Co-First Author)
BEHAVIOR-1K: A Benchmark for Embodied AI with 1,000 Everyday Activities and Realistic Simulation
Chengshu Li*, Ruohan Zhang*, Josiah Wong*, Cem Gokmen*, Sanjana Srivastava*, Roberto Martín-Martín*, Chen Wang*, Gabrael Levine*, Michael Lingelbach, Jiankai Sun, Mona Anvari, Minjune Hwang, Manasi Sharma, Arman Aydin, Dhruva Bansal, Samuel Hunter, Kyu-Young Kim, Alan Lou, Caleb R Matthews, Ivan Villa-Renteria, Jerry Huayang Tang, Claire Tang, Fei Xia, Silvio Savarese, Hyowon Gweon, Karen Liu, Jiajun Wu, Li Fei-Fei
Conference on Robot Learning (CoRL) 2022
BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments
iGibson 2.0: Object-Centric Simulation for Robot Learning of Everyday Household Tasks
iGibson 1.0: A Simulation Environment for Interactive Tasks in Large Realistic Scenes
Bokui Shen* , Fei Xia* , Chengshu Li* , Roberto Martín-Martín* , Linxi Fan, Guanzhi Wang, Claudia Pérez-D'Arpino, Shyamal Buch, Sanjana Srivastava, Lyne Tchapmi, Micael Tchapmi, Kent Vainio, Josiah Wong, Li Fei-Fei, Silvio Savarese
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) 2021
Publications (Other)
Modeling Dynamic Environments with Scene Graph Memory
Andrey Kurenkov, Michael Lingelbach, Agarwal Tanmay, Chengshu Li, Emily Jin, Li Fei-Fei, Jiajun Wu, Silvio Savarese, Roberto Martín-Martín
Internal Conference on Machine Learning (ICML) 2023
Task-Driven Graph Attention for Hierarchical Relational Object Navigation
Michael Lingelbach, Chengshu Li, Minjune Hwang, Andrey Kurenkov, Alan Lou, Roberto Martín-Martín, Ruohan Zhang, Li Fei-Fei, Jiajun Wu
IEEE International Conference on Robotics and Automation (ICRA) 2023
SONICVERSE: A Multisensory Simulation Platform for Embodied Household Agents that See and Hear
Ruohan Gao*, Hao Li*, Gokul Dharan, Zhuzhu Wang, Chengshu Li, Fei Xia, Silvio Savarese, Li Fei-Fei, Jiajun Wu
IEEE International Conference on Robotics and Automation (ICRA) 2023
Eye-BEHAVIOR: An Eye-Tracking Dataset for Everyday Household Activities in Virtual, Interactive, and Ecological Environments
Cem Gokmen, Ruohan Zhang, Sanjana Srivastava, Chengshu Li, Michael Lingelbach, Roberto Martín-Martín, Silvio Savarese, Jiajun Wu, Li Fei-Fei
Journal of Vision December 2022, Volume 22, Issue 14, 3819
Interactive Gibson Benchmark (iGibson 0.5): A Benchmark for Interactive Navigation in Cluttered Environments
Fei Xia, William B. Shen, Chengshu Li, Priya Kasimbeg, Micael Tchapmi, Alexander Toshev, Roberto Martín-Martín, Silvio Savarese
IEEE Robotics and Automation Letters (RA-L) and International Conference on Robotics and Automation (ICRA) 2020
* denotes equal contribution
Industry Experience
NVIDIA Corporation
Research Intern (Part-time)
2022/01 - 2023/01
Santa Clara, CA
Google Brain Robotics
Student Researcher (Part-time)
2019/11 - 2020/05
Mountain View, CA
AutoX, Inc.
Research Engineer for Deep Learning and Perception
2017/09 - 2018/12
San Jose, CA
Shift Technologies, Inc.
Software Engineering Intern
2016/06 - 2016/09
San Francisco, CA
Tableau Software
Software Engineering Intern
2015/06 - 2015/09
Seattle, WA
Tech Reports
Indexed Value Function Learning via Distributional Temporal Difference
Tian Tan*, Zhihan Xiong*, Chengshu Li*
[paper]
DeepShuai: Deep Reinforcement Learning based Chinese Chess Player
Chengshu Li*, Kedao Wang*, Zihua Liu*
[paper]
Effective Word Representation for Named Entity Recognition
Jun-Ting Hsieh*, Chengshu Li*, Wendi Liu*
[paper]
* denotes equal contribution