Shuijing Liu (刘水竞)
Welcome to my personal website! I’m a postdoc scholar in UT Austin Robot Perception and Learning Lab, advised by Professor Yuke Zhu. In 2024, I obtained my PhD from Human-Centered Autonomy Lab in Electrical and Computer Engineering, University of Illinois at Urbana Champaign, advised by Professor Katherine Driggs-Campbell.
My primary research interest is robotic systems that leverages on structured models to operate among humans. My long term goal is to enable robots to interact and collaborate with people in daily life. I advocate for robot learning from the people, with the people, and for the people.
[CV] [Research statement]
Previously, I earned my Bachelor’s Degree in Computer Engineering from University of Illinois at Urbana Champaign in May 2018. Before that, I was born and raised in Zhengzhou, China.
Areas of research:
- Learning-based Robotics
- Human-Robot Interaction
- Machine Learning
I’m open to research discussion and collaboration, please feel free to get in touch!
For junior PhD/Master/undergraduate students: I dedicate 30 minutes every two weeks to offer mentorship/advising/help, especially for students from underrepresented groups or whoever is in need. Topics include but are not limited to AI/robotics/HRI research, graduate school application, career development, life, etc. If you would like to chat with me, please fill this form to schedule.
News
- 08/16/2024: I started my postdoc at UT Austin RPL Lab! Also, I’m selected as an MIT EECS Rising Star in 2024!
- 05/23/2024: I passed my thesis defense! Big thanks to my advisor, my committee, and my colleagues in HCA lab!
- 01/21/2024: Our paper “DRAGON: A Dialogue-Based Robot for Assistive Navigation with Visual Language Grounding” is accepted to RA-L!
- 08/30/2023: Two papers in audio-vision robotics (poster) and long-horizon manipulation (oral) accepted in CoRL 2023!
- 01/2023: Three papers in crowd navigation and audio-vision robotics accepted in ICRA 2023!
- 01/10/2023: Please checkout the website and open-source code for our paper “Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph”.
- 01/03/2023: Our paper “Structural Attention-Based Recurrent Variational Autoencoder for Highway Vehicle Anomaly Detection” is accepted as full paper in AAMAS 2023 (Acceptance rate: 23.3%)! For details, please checkout our website and code.
- 11/28/2022: I passed my preliminary exam (also known as thesis proposal)! Big thanks to my advisor, my committee, and my colleagues in HCA lab!
- 06/16/2022: Our paper “Combining Model-Based Controllers And Generative Adversarial Imitation Learning for Traffic Simulation” is accepted in ITSC 2022!
- 05/2022–08/2022: Completed an applied scientist internship at Robotics and AI at Amazon!
- 01/21/2022: Two papers “Learning to Navigate Intersections with Unsupervised Driver Trait Inference” and “Off Environment Evaluation Using Convex Risk Minimization” are accepted in ICRA2022!
- 12/25/2021: Please checkout the open-source code for our paper “Learning to Navigate Intersections with Unsupervised Driver Trait Inference”.
- 03/25/2021: Our paper “Decentralized Structural-RNN for Robot Crowd Navigation with Deep Reinforcement Learning” is accepted in ICRA 2021! Also, checkout our code here!
- 06/30/2020: Our paper “Robot Sound Interpretation: Combining Sight and Sound in Learning-Based Control” is accepted in IROS 2020!
- 06/19/2020: Starting my PhD journey in HCA group!
- 09/28/2019: My personal website is live!