Chengshu (Eric) Li

I am currently a fourth-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 robot learning and 3D simulation environment.

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 Google Deepmind (robotics team) (2023), Nvidia (2022-2023), Google Brain Robotics (2019-2020), AutoX (2017-2018), Shift (2016), and Tableau (2015).

Email: chengshu@stanford.edu

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News

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)
* denotes equal contribution

Chain of Code: Reasoning with a Language Model-Augmented Code Emulator

Chengshu Li, Jacky Liang, Andy Zeng, Xinyun Chen, Karol Hausman, Dorsa Sadigh, Sergey Levine, Li Fei-Fei, Fei Xia, Brian Ichter

Foundation Models for Decision Making Workshop @ NeurIPS 2023

[paper][website]

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

[paper][website][code]

BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments

Sanjana Srivastava*, Chengshu Li*, Michael Lingelbach*, Roberto Martín-Martín*, Fei Xia, Kent Vainio, Zheng Lian, Cem Gokmen, Shyamal Buch, C. Karen Liu, Silvio Savarese, Hyowon Gweon, Jiajun Wu, Li Fei-Fei

Conference on Robot Learning (CoRL) 2021

[paper][website]

iGibson 2.0: Object-Centric Simulation for Robot Learning of Everyday Household Tasks

Chengshu Li*, Fei Xia*, Roberto Martín-Martín*, Michael Lingelbach, Sanjana Srivastava, Bokui Shen, Kent Vainio, Cem Gokmen, Gokul Dharan, Tanish Jain, Andrey Kurenkov, C. Karen Liu, Hyowon Gweon, Jiajun Wu, Li Fei-Fei, Silvio Savarese

Conference on Robot Learning (CoRL) 2021

[paper][website][code]

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

[paper][website][code]

Fei Xia*, Chengshu Li*, Roberto Martín-Martín, Or Litany, Alexander Toshev, Silvio Savarese

IEEE International Conference on Robotics and Automation (ICRA) 2021

[paper][website]

HRL4IN: Hierarchical Reinforcement Learning for Interactive Navigation with Mobile Manipulators

Chengshu Li, Fei Xia, Roberto Martín-Martín,  Silvio Savarese

Conference on Robot Learning (CoRL) 2019

[paper][website][code]

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

[paper][project website][igibson website][code]

Principles and Guidelines for Evaluating Social Robot Navigation Algorithms

Anthony Francis, Claudia Pérez-d'Arpino, Chengshu Li, Fei Xia, Alexandre Alahi, Rachid Alami, Aniket Bera, Abhijat Biswas, Joydeep Biswas, Rohan Chandra, Hao-Tien Lewis Chiang, Michael Everett, Sehoon Ha, Justin Hart, Jonathan P How, Haresh Karnan, Tsang-Wei Edward Lee, Luis J Manso, Reuth Mirksy, Soeren Pirk, Phani Teja Singamaneni, Peter Stone, Ada V Taylor, Peter Trautman, Nathan Tsoi, Marynel Vazquez, Xuesu Xiao, Peng Xu, Naoki Yokoyama, Alexander Toshev, Roberto Martín-Martín

arXiv pre-print

[paper]

Retrospectives on the Embodied AI Workshop

Matt Deitke, Dhruv Batra, Yonatan Bisk, Tommaso Campari, Angel X Chang, Devendra Singh Chaplot, Changan Chen, Claudia Pérez D'Arpino, Kiana Ehsani, Ali Farhadi, Li Fei-Fei, Anthony Francis, Chuang Gan, Kristen Grauman, David Hall, Winson Han, Unnat Jain, Aniruddha Kembhavi, Jacob Krantz, Stefan Lee, Chengshu Li, Sagnik Majumder, Oleksandr Maksymets, Roberto Martín-Martín, Roozbeh Mottaghi, Sonia Raychaudhuri, Mike Roberts, Silvio Savarese, Manolis Savva, Mohit Shridhar, Niko Sünderhauf, Andrew Szot, Ben Talbot, Joshua B Tenenbaum, Jesse Thomason, Alexander Toshev, Joanne Truong, Luca Weihs, Jiajun Wu

arXiv pre-print

[paper]

Gibson Env V2: Embodied Simulation Environments for Interactive Navigation

Fei Xia, Chengshu Li, Kevin Chen, Bokui Shen, Roberto Martín-Martín, Noriaki Hirose, Amir R. Zamir, Li Fei-Fei, Silvio Savarese

Deep Learning for Semantic Visual Navigation Workshop @ CVPR 2019

[paper]

Industry Experience

Google Deepmind (robotics team)

Student Researcher

2023/06 - 2023/11

Mountain View, CA

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]

Spotlight: A Smart Video Highlight Generator

Jun-Ting Hsieh*, Chengshu Li*, Wendi Liu*

[paper]

Effective Word Representation for Named Entity Recognition

Jun-Ting Hsieh*, Chengshu Li*, Wendi Liu*

[paper]

Predicting Information Virality in WeChat

Chengshu Li*, Jun-Ting Hsieh*, Yuyang Xia*

[paper]