Ph.D. Candidate @ TTIC

Specializing in Robotics Planning and Diffusion Models

luzhesun@ttic.edu | luzhesun@uchicago.edu

Biography

I'm a Ph.D. candidate at TTIC focusing on Robotics Planning and Diffusion Models, advised by Professor Matthew R. Walter working in the Robot Intelligence through Perception Lab (RIPL).

Prior to joining TTIC, I completed my Masters Program in Computer Science at the University of Chicago. I studied at the School of Information Science at Xiamen University as an undergraduate, where I conducted research on graph theory with Professor Zhihong Zhang.

In my free time, I really enjoy photography, painting Chinese paintings and playing the Erhu.

🀝 Open to collaborations | πŸ” Seeking summer 2026 internships | Feel free to reach out!

Education

Ph.D. in Computer Science
Toyota Technological Institute at Chicago
2023 - Present
Master of Computer Science
University of Chicago
2021 - 2022
B.Eng in Information Science (Graduates With Honor)
Xiamen University
2017 - 2021
Publications GitHub Scholar
Luzhe Sun

Latest News

Sep 2025
Paper Accepted! Our paper "FlashBack: Consistency Model-Accelerated Shared Autonomy" has been accepted to CoRL 2025.
Sep 2025
Oral Presentation! Our paper "StackGen: Generating Stable Structures from Silhouettes via Diffusion" will be presented as an oral at IROS 2025.
Jul 2024
Workshop Organizer Successfully organized the Multimodal Artificial Intelligence Workshop at TTIC.
Apr 2024
Demo Invitation Invited to demonstrate our embodied AI system at the 2024 Robot Block Party at Museum of Science and Industry.
Jun 2023
RSS 2023 Oral Our work "To the Noise and Back: Diffusion for Shared Autonomy" was accepted as an oral presentation at RSS 2023.
View All News

Publications

FlashBack Paper
FlashBack: Consistency Model-Accelerated Shared Autonomy
Luzhe Sun, Jingtian Ji, Xiangshan(Vincent) Tan, Matthew R. Walter
CoRL 2025 arXiv Website Blog(ηŸ₯乎)
StackGen Paper
StackGen: Generating Stable Structures from Silhouettes via Diffusion
Luzhe Sun*, Takuma Yoneda*, Samuel W. Wheeler, Tianchong Jiang, Matthew R. Walter
IROS 2025 [Oral] arXiv Website Blog(ηŸ₯乎)
Diffusion Shared Autonomy Paper
To the Noise and Back: Diffusion for Shared Autonomy
Takuma Yoneda, Luzhe Sun, Ge Yang, Bradly Stadie, Matthew R. Walter
RSS 2023 [Oral] Website arXiv Code
Quantum GNN Paper
Decompositional Quantum Graph Neural Network
Xing Ai, Luzhe Sun, Zhihong Zhang, Junchi Yan, Edwin Hancock
arXiv

Service and Volunteer

Conference Reviewer
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE International Conference on Robotics and Automation (ICRA), Conference on Robot Learning (CoRL)
Organizer
Multimodal Artificial Intelligence Workshop at TTIC, Chicago, IL (2024)
Invited Demo
2024 Robot Block Party at Griffin Museum of Science, Chicago, IL
Invited Demo
2023 Robot Block Party at Griffin Museum of Science, Chicago, IL
Volunteer
Midwest Robotics Workshop at TTIC, Chicago, IL

Awards and Honors

China National Scholarship (Top 0.1%)
2020 β€’ Chinese Ministry of Education, China
China National Scholarship (Top 0.1%)
2019 β€’ Chinese Ministry of Education, China
Honored Graduate Student
2021 β€’ Xiamen University, China
National Second Prize of Contemporary Undergraduate Mathematical Contest in Modeling
2019 β€’ China Society for Industrial and Applied Mathematics, China
National Third Prize of China Students Service Outsourcing Competition
2018 β€’ Ministry of Education & Ministry of Commerce, China
Xiamen University "Xilie Huang" Annual Scholarship (2/200)
2018 β€’ Xiamen University, China
Xiamen University Outstanding Student Worker Scholarship
2018 β€’ Xiamen University, China

Projects

Embodied ChatGPT | Robot Block Party 2023
We implemented the Code as Policies algorithm on the UR5 robot. The robot is able to respond to the user's voice command and execute the corresponding task. The project was presented during the 2023 National Robotics Week at the Museum of Science and Industry in Chicago, and at the University of Chicago for the 2023 South Side Science Festival.
AI Transnational Free Travel Assistant APP
An auxiliary application for tourists from China and Japan to travel independently. Using modern AI technology to assist tourists, provide and recommend information on local attractions, restaurants, accommodation, transportation, etc. The app addresses language barriers in transnational free travel.
GitHub