I am an incoming Assistant Professor in the Kahlert School of Computing at the University of Utah. Currently, I am a Postdoctoral Scholar working with Jiajun Wu in the CogAI group and Stanford Vision and Learning Lab (SVL). I completed my Ph.D. in robotics at Georgia Institute of Technology, advised by Sonia Chernova. During my Ph.D., I interned at the NVIDIA Seattle Robotics Lab, working with Dieter Fox, Tucker Hermans, Animesh Garg, and Chris Paxton. Prior to joining the Ph.D. program, I received my Bachelor's degree in Electrical Engineering from Georgia Tech.
Email / CV (Dec 2024) / Google Scholar / Github / Twitter
The goal of my research is to develop robots that can effectively perceive, model, and interact with the real world. I am particularly interested in the application where human users can easily command robots to complete long-horizon tasks via simple language commands, such as "make the tea". Achieving this requires robust generalization across various dimensions, including objects, environments, actions, and tasks. My core insight is that strong generalization can be achieved through a structured representation of world knowledge. Rather than constructing this representation from scratch, robots should leverage the rich knowledge embedded in human language, grounding it through interactions with their environments to connect abstract knowledge to their sensorimotor capabilities.
My prior research has investigated core components of this structured knowledge representation, methods to extract and refine this knowledge extracted from humans, and algorithms that enable reasoning with this knowledge to support broad generalization.
I am looking for motivated and talented students to join my research group.
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Thank you for your interest in joining our research group! Please review the information below about our research environment and goals.
If you are a prospective PhD student interested in joining my group, especially for the coming application season, please fill out this PhD Opportunities Form. If you are interested in working with me as an undergraduate student, master's student, postdoc, research intern, or visiting scholar, please complete this Research Opportunities Form. I apologize that I might not be able to respond to all emails, but I will carefully review all submitted forms.
We tackle problems that bring new ideas and make a real-world difference. Our projects can lead to new algorithms, datasets, benchmarks, or integrated hardware and software solutions.
Publishing and DisseminationI encourage students to publish one paper each year, something you are genuinely proud to share. Alongside the paper, we release code, datasets, project websites, and other materials to help the community build on our work.
Mentorship and AdvisingI will schedule recurring meetings with all group members and make it a priority to meet individually with each PhD student every week. We also hold regular lab meetings / reading groups to share ideas and learn from one another. I believe strong research comes from a supportive, honest, and intellectually open environment.
For research, I will support your growth in identifying meaningful questions, developing solutions, writing, sharing work, managing projects, giving and receiving constructive feedback, and shaping a strong research narrative over time.
For your career, I will provide advice on finding internships, building your network, mentoring junior students, and preparing for academic or industry jobs.
For personal growth beyond research, I encourage you to balance work and life, travel (for example, by attending international conferences), and continue developing your interests and hobbies.
Funding and ResourcesI will work to secure funding to support PhD students. Students will have access to high-performance compute resources, robot hardware, personal computers, and travel support for attending conferences.
What I'm Looking ForI'm looking for students who are excited in the research directions we pursue. Ideal candidates:
Weiyu Liu*,
Neil Nie*,
Ruohan Zhang,
Jiayuan Mao†,
Jiajun Wu†
Conference on Robot Learning (CoRL), 2024
2nd Workshop on Learning Effective Abstractions for Planning (LEAP), 2024 (Oral Presentation)
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Weiyu Liu,
Jiayuan Mao,
Joy Hsu,
Tucker Hermans,
Animesh Garg,
Jiajun Wu
Conference on Robot Learning (CoRL), 2023
arxiv /
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bibtex
Weiyu Liu*,
Geng Chen*,
Joy Hsu,
Jiayuan Mao†,
Jiajun Wu†
International Conference on Learning Representations (ICLR), 2024
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Yunong Liu,
Cristobal Eyzaguirre,
Manling Li,
Shubh Khanna,
Juan Carlos Niebles,
Vineeth Ravi,
Saumitra Mishra,
Weiyu Liu†,
Jiajun Wu†
Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2024
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Manling Li*,
Shiyu Zhao*,
Qineng Wang*,
Kangrui Wang*,
Yu Zhou*,
Sanjana Srivastava,
Cem Gokmen,
Tony Lee,
Li Erran Li,
Ruohan Zhang,
Weiyu Liu,
Percy Liang,
Li Fei-Fei,
Jiayuan Mao,
Jiajun Wu
Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2024
(Oral Presentation)
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Emily Jin,
Zhuoyi Huang,
Jan-Philipp Fränken,
Weiyu Liu,
Hannah Cha,
Sarah A. Wu,
Erik Brockbank,
Ruohan Zhang,
Jiajun Wu,
Tobias Gerstenberg
Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2024
arxiv /
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Weiyu Liu1,
Angel Daruna1,
Maithili Patel2,
Kartik Ramachandruni2,
Sonia Chernova
Robotics and Autonomous Systems, 2023
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Weiyu Liu,
Yilun Du,
Tucker Hermans,
Sonia Chernova,
Chris Paxton
Robotics: Science and Systems (RSS), 2023
CoRL Workshop on Language and Robot Learning, 2022
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code & data /
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Yixuan Huang,
Nichols Crawford Taylor,
Adam Conkey,
Weiyu Liu,
Tucker Hermans
Transactions on Robotics (TR-O), 2023
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Chao Tang,
Dehao Huang
Wenqi Ge,
Weiyu Liu,
Hong Zhang
Robotics and Automation Letters (RA-L), 2023
arxiv /
code & data /
website /
bibtex
Weiyu Liu,
Chris Paxton,
Tucker Hermans,
Dieter Fox
International Conference on Robotics and Automation (ICRA), 2022
arxiv /
code & data /
website /
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Weiyu Liu,
Dhruva Bansal,
Angel Daruna,
Sonia Chernova
Robotics: Science and Systems (RSS), 2021
Autonomous Robots, 2023 (Invited Submission)
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Angel Daruna,
Lakshmi Nair,
Weiyu Liu,
Sonia Chernova
International Conference on Robotics and Automation (ICRA), 2021
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Ruinian Xu,
Fu-Jen Chu,
Chao Tang,
Weiyu Liu,
Patricio Vela
IEEE Robotics and Automation Letters (RA-L), 2021
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code & data /
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Adithya Murali,
Weiyu Liu,
Kenneth Marino,
Sonia Chernova,
Abhinav Gupta
Conference on Robot Learning (CoRL), 2020
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code & data /
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project page /
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Weiyu Liu,
Angel Daruna,
Sonia Chernova
International Conference on Robotics and Automation (ICRA), 2020
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Weiyu Liu,
Angel Daruna,
Zsolt Kira,
Sonia Chernova
Conference on Artificial Intelligence (AAAI), 2020 (Oral Presentation)
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Angel Daruna,
Weiyu Liu,
Zsolt Kira,
Sonia Chernova
International Conference on Robotics and Automation (ICRA), 2019
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Siddhartha Banerjee*,
Angel Daruna*,
David Kent*,
Weiyu Liu*,
Jonathan Balloch,
Abhinav Jain,
Akshay Krishnan,
Muhammad Asif Rana,
Harish Ravichandar,
Binit Shah,
Nithin Shrivatsav,
Sonia Chernova
International Symposium on Robotics Research (ISRR), 2019
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Ningshi Yao,
Qiuyang Tao,
Weiyu Liu,
Zhen Liu,
Ye Tian,
Peiyu Wang,
Timothy Li,
Fumin Zhang
Frontiers of Information Technology & Electronic Engineering, 2019
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Sonia Chernova,
Vivian Chu,
Angel Daruna,
Haley Garrison,
Meera Hahn,
Priyanka Khante,
Weiyu Liu,
Andrea Thomaz
AAAI Spring Symposium Series (AAAI-SSS), 2018
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Sonia Chernova,
Vivian Chu,
Angel Daruna,
Haley Garrison,
Meera Hahn,
Priyanka Khante,
Weiyu Liu,
Andrea Thomaz
International Symposium on Robotics Research (ISRR), 2017
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