Huihan Liu bio photo

Huihan Liu

PhD in Computing Science @ UT Austin

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Publications

Huihan Liu, Yu Zhang, Vaarij Betala, Evan Zhang, James Liu, Crystal Ding, Yuke Zhu
Multi-Task Interactive Robot Fleet Learning with Visual World Models
Conference on Robot Learning (CoRL), 2024
[PDF] [Website] [BibTeX]

@inproceedings{liumulti,
      title={Multi-Task Interactive Robot Fleet Learning with Visual World Models},
      author={Liu, Huihan and Zhang, Yu and Betala, Vaarij and Zhang, Evan and Liu, James and Ding, Crystal and Zhu, Yuke},
      booktitle={8th Annual Conference on Robot Learning}
    }
  

Huihan Liu, Soroush Nasiriany, Lance Zhang, Zhiyao Bao, Yuke Zhu
Robot Learning on the Job: Human-in-the-Loop Manipulation and Learning During Deployment (Extended Version)
The International Journal of Robotics Research (IJRR), 2024
[PDF] [Website] [BibTeX]

    @inproceedings{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},
    booktitle = {Robotics: Science and Systems (RSS)},
    year = {2023}
    }
  

Tian Gao, Soroush Nasiriany, Huihan Liu, Quantao Yang, Yuke Zhu
PRIME: Scaffolding Manipulation Tasks with Behavior Primitives for Data-Efficient Imitation Learning
IEEE Robotics and Automation Letters (RA-L), 2024
[PDF] [Website] [BibTeX]

@misc{gao2024prime,
      title={PRIME: Scaffolding Manipulation Tasks with Behavior Primitives for Data-Efficient Imitation Learning}, 
      author={Tian Gao and Soroush Nasiriany and Huihan Liu and Quantao Yang and Yuke Zhu},
      year={2024},
      eprint={2403.00929},
      archivePrefix={arXiv},
      primaryClass={cs.RO}
}

Huihan Liu, Shivin Dass, Roberto Martín-Martín, Yuke Zhu
Model-Based Runtime Monitoring with Interactive Imitation Learning
IEEE International Conference on Robotics and Automation (ICRA), 2024
[PDF] [Website] [BibTeX]

  @misc{liu2023modelbased,
    title={Model-Based Runtime Monitoring with Interactive Imitation Learning}, 
    author={Huihan Liu and Shivin Dass and Roberto Martín-Martín and Yuke Zhu},
    year={2023},
    eprint={2310.17552},
    archivePrefix={arXiv},
    primaryClass={cs.RO}
}

Huihan Liu, Alice Chen, Yuke Zhu, Adith Swaminathan, Andrey Kolobov, Ching-An Cheng
Interactive Robot Learning from Verbal Correction
CoRL Workshop on Language and Robot Learning (LangRob), 2023
[PDF] [Website] [BibTeX]

  @misc{liu2023interactive,
    title={Interactive Robot Learning from Verbal Correction}, 
    author={Huihan Liu and Alice Chen and Yuke Zhu and Adith Swaminathan and Andrey Kolobov and Ching-An Cheng},
    year={2023},
    eprint={2310.17555},
    archivePrefix={arXiv},
    primaryClass={cs.RO}
}

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]
Best Paper Award Finalist

    @inproceedings{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},
    booktitle = {Robotics: Science and Systems (RSS)},
    year = {2023}
    }
  

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 J. 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}
    }