Huihan Liu bio photo

Huihan Liu

PhD in Computing Science @ UT Austin

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I am a second-year Ph.D. student in Computer Science at the University of Texas at Austin. I am fortunate to be advised by Professor Yuke Zhu, and I am a member of the Robot Perception and Learning Lab. I am broadly interested in Robotics, Reinforcement Learning and Machine Learning. My current research focuses on the intersection of Reinforcement Learning and Imitation Learning, and Human-in-the-Loop robot learning.


I previously did my undergraduate in Computer Science at the University of California, Berkeley, and I was affiliated with the Berkeley Artificial Intelligence Research (BAIR) Lab. I had the pleasure to work with Professor Sergey Levine and Professor Costas Spanos.

Recent Publications

  • Huihan Liu, Soroush Nasiriany, Lance Zhang, Zhiyao Bao, Yuke Zhu
    Robot Learning on the Job: Human-in-the-Loop Manipulation and Learning During Deployment
    Robotics: Science and Systems (RSS), 2023
    [PDF] [Website] [BibTeX]

        @misc{liu2022robot,
          title={Robot Learning on the Job: Human-in-the-Loop Autonomy and Learning During Deployment}, 
          author={Huihan Liu and Soroush Nasiriany and Lance Zhang and Zhiyao Bao and Yuke Zhu},
          year={2022},
          eprint={2211.08416},
          archivePrefix={arXiv},
          primaryClass={cs.RO}
        }
    }
      
  • Soroush Nasiriany, Huihan Liu, Yuke Zhu
    Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks
    IEEE International Conference on Robotics and Automation (ICRA), 2022
    [PDF] [Website] [BibTeX]
    Outstanding Learning Paper

        @misc{nasiriany2021augmenting,
          title={Augmenting Reinforcement Learning with Behavior Primitives for Diverse Manipulation Tasks}, 
          author={Soroush Nasiriany and Huihan Liu and Yuke Zhu},
          year={2021},
          eprint={2110.03655},
          archivePrefix={arXiv},
          primaryClass={cs.LG}
    }
      
  • Avi Singh*, Huihan Liu*, Gaoyue Zhou, Albert Yu, Nicholas Rhinehart, Sergey Levine
    Parrot: Data-Driven Behavioral Priors for Reinforcement Learning
    International Conference on Learning Representations (ICLR), 2021
    [PDF] [Website] [BibTeX]
    Oral Presentation (top 1.8% of submissions)

        @misc{singh2020parrot,
          title={Parrot: Data-Driven Behavioral Priors for Reinforcement Learning}, 
          author={Avi Singh and Huihan Liu and Gaoyue Zhou and Albert Yu and Nicholas Rhinehart and Sergey Levine},
          year={2020},
          eprint={2011.10024},
          archivePrefix={arXiv},
          primaryClass={cs.LG}
    }
      
  • Han Zou, Yuxun Zhou, Jianfei Yang, Huihan Liu, Hari Prasanna Das, Costas J. Spanos
    Consensus Adversarial Domain Adaptation
    AAAI Conference on Artificial Intelligence, 2019
    [PDF] [BibTeX]

        @inproceedings{Zou2019ConsensusAD,
            title={Consensus Adversarial Domain Adaptation},
            author={Han Zou and Yuxun Zhou and Jianfei Yang and Huihan Liu and H. Das and C. Spanos},
            booktitle={AAAI},
            year={2019}
            }
        }
      
  • Han Zou, Jianfei Yang, Hari Prasanna Das, Huihan Liu, Yuxun Zhou, Costas J. Spanos
    WiFi and Vision Multimodal Learning for Accurate and Robust Device-Free Human Activity Recognition
    Multimodal Learning and Applications (MULA) Workshop, Conference on Computer Vision and Pattern Recognition (CVPR), 2019
    [PDF] [BibTeX]

        @InProceedings{Zou_2019_CVPR_Workshops,
            author = {Zou, Han and Yang, Jianfei and Prasanna Das, Hari and Liu, Huihan and Zhou, Yuxun and Spanos, Costas J.},
            title = {WiFi and Vision Multimodal Learning for Accurate and Robust Device-Free Human Activity Recognition},
            booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
            month = {June},
            year = {2019}
        }
      
  • Ioannis Konstantakopoulos, Andrew R.Barkan, Shiying He, Tanya Veeravalli, Huihan Liu, Costas Spanos
    A Deep Learning and Gamification Approach to Energy Conservation at Nanyang Technological University
    Applied Energy Journal, Volume 237, 1 March 2019
    [PDF] [BibTeX]

        @misc{konstantakopoulos2018deep,
              title={A Deep Learning and Gamification Approach to Energy Conservation at Nanyang Technological University}, 
              author={Ioannis C. Konstantakopoulos and Andrew R. Barkan and Shiying He and Tanya Veeravalli and Huihan Liu and Costas Spanos},
              year={2018},
              eprint={1809.05142},
              archivePrefix={arXiv},
              primaryClass={cs.LG}
        }