Publications
Please check my Google Scholar for the most updated publications.
Equal contributions are denoted by * and †.
Preprints
Sim-to-Real Adaptation with Graph-Based Neural Dynamics for Granular Object Manipulation
Kaiwen Hong, Haonan Chen *, Runxuan Wang *, Kaylan Wang *, Mingtong Zhang, Shuijing Liu, Yunzhu Li, Katherine Driggs-Campbell.
Under review for IEEE International Conference on Robotics and Automation (ICRA), 2025.
Learning Coordinated Bimanual Manipulation Policies using State Diffusion and Inverse Dynamics Models
Haonan Chen, Jiaming Xu *, Lily Sheng *, Tianchen Ji, Shuijing Liu, Yunzhu Li, Katherine Driggs-Campbell.
Under review for IEEE International Conference on Robotics and Automation (ICRA), 2025.
Structured Graph Network for Constrained Robot Crowd Navigation with Low Fidelity Simulation
Shuijing Liu, Kaiwen Hong, Neeloy Chakraborty, Katherine Driggs-Campbell.
[Paper] [Website & Video]
Topology-Guided ORCA: Smooth Multi-Agent Motion Planning in Constrained Environments
Fatemeh Cheraghi Pouria, Zhe Huang, Ananya Yammanuru, Shuijing Liu, Katherine Driggs-Campbell.
[Paper]
Journal
DRAGON: A Dialogue-Based Robot for Assistive Navigation with Visual Language Grounding
Shuijing Liu, Aamir Hasan, Kaiwen Hong, Runxuan Wang, Peixin Chang, Zachary Mizrachi, Justin Lin, D Livingston McPherson, Wendy A Rogers, Katherine Driggs-Campbell.
In IEEE Robotics and Automation Letters (RA-L), 2024.
[Paper] [Website] [Video] [Code]
Conference
A Data-Efficient Visual-Audio Representation with Intuitive Fine-tuning for Voice-Controlled Robots
Peixin Chang, Shuijing Liu, Tianchen Ji, Neeloy Chakraborty, Kaiwen Hong, and Katherine Driggs-Champbell.
In Conference on Robot Learning (CoRL), 2023.
[Paper]
Predicting Object Interactions with Behavior Primitives: An Application in Stowing Tasks
Haonan Chen, Yilong Niu, Kaiwen Hong, Shuijing Liu, Yixuan Wang, Yunzhu Li, Katherine Driggs-Campbell.
In Conference on Robot Learning (CoRL), 2023.
(Best Student Paper Award Finalist [link])
[Paper] [Website] [Code]
Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph
Shuijing Liu, Peixin Chang, Zhe Huang, Neeloy Chakraborty, Kaiwen Hong, Weihang Liang, D. Livingston McPherson, Junyi Geng, Katherine Driggs-Campbell.
In IEEE International Conference on Robotics and Automation (ICRA), 2023.
(Best poster award at IROS 2023 Last-Mile Robotics Workshop [link])
[Paper] [Website] [Video] [Code]
Learning Visual-Audio Representations for Voice-Controlled Robots
Peixin Chang, Shuijing Liu, and Katherine Driggs-Champbell.
In IEEE International Conference on Robotics and Automation (ICRA), 2023.
[Paper] [Video] [Code]
Occlusion-Aware Crowd Navigation Using People as Sensors
Ye-Ji Mun, Masha Itkina, Shuijing Liu, and Katherine Driggs-Campbell.
In IEEE International Conference on Robotics and Automation (ICRA), 2023.
[Paper] [Video] [Code] [Newspaper article]
Structural Attention-Based Recurrent Variational Autoencoder for Highway Vehicle Anomaly Detection
Neeloy Chakraborty, Aamir Hasan *, Shuijing Liu *, Tianchen Ji *, Eric Liang, D. Livingston McPherson, and Katherine Driggs-Campbell
In International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2023. (Full paper)
[Paper] [Website] [Code]
Combining Model-Based Controllers And Generative Adversarial Imitation Learning for Traffic Simulation
Haonan Chen, Tianchen Ji, Shuijing Liu, and Katherine Driggs-Champbell.
In IEEE International Conference on Intelligent Transportation Systems (ITSC), 2022.
[Paper]
Learning to Navigate Intersections with Unsupervised Driver Trait Inference
Shuijing Liu, Peixin Chang, Haonan Chen, Neeloy Chakraborty, and Katherine Driggs-Champbell.
In IEEE International Conference on Robotics and Automation (ICRA), 2022.
[Paper] [Website] [Code] [Video]
Off Environment Evaluation Using Convex Risk Minimization
Pulkit Katdare, Shuijing Liu, and Katherine Driggs-Champbell.
In IEEE International Conference on Robotics and Automation (ICRA), 2022.
[Paper] [Code]
Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning
Shuijing Liu *, Peixin Chang *, Weihang Liang † , Neeloy Chakraborty † , and Katherine Driggs-Champbell.
In IEEE International Conference on Robotics and Automation (ICRA), 2021.
[Paper] [Website] [Code] [Video]
Robot Sound Interpretation: Combining Sight and Sound in Learning-Based Control
Peixin Chang, Shuijing Liu, Haonan Chen, Katherine Driggs-Champbell.
In IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2020.
[Paper] [Website] [Video]
Robust Deep Reinforcement Learning with Adversarial Attacks
Anay Pattanaik, Zhenyi Tang *, Shuijing Liu *, Gautham Bommannan, Girish Chowdhary.
In 17th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), 2018. (Extended Abstract)
[Paper] [Video] [Poster] [Supplementary materials]
Thesis
Prostate Cancer Diagnosis by Deep Learning
Shuijing Liu.
Undergraduate Senior Thesis, May 2018.
[Abstract] [Paper] [Slides]