Junjia LIU 刘浚嘉

The Chinese University of Hong Kong

Hong Kong

I’m a final year Ph.D. student at The Chinese University of Hong Kong (CUHK). I received an academic master’s degree from Shanghai Jiao Tong University (SJTU). My work lies in the intersection between Robotics and AI, with a focus on human-level domestic service manipulation skill learning for humanoid robots. I was previously an intern at Huawei 2012 Lab.

I am an existentialist as well as a Heideggerian, agree with the Heraus-fordem of technology on humanity but also believe that “where danger is, grows the saving power also”. The humanoid embodied intelligence is the process of humans knowing themselves, understanding themselves, and “self-Entbergen”. It is always passionate to do research for the sake of human self-transcendence.

news

Aug 28, 2024	Chair the RO-MAN 2024 session “Non-verbal cues and Experissiveness” & “Linguisitc Communication and Dialogue” and co-chair the session “Machine Learning and Adaptation II”.
Aug 27, 2024	Present at the 33rd IEEE International Conference on Robot and Human Interactive Communication, Pasadena, California, USA.
Jan 24, 2024	Rofunc v0.0.2.6 is released with plenty of robot skill learning examples!

latest posts

Jan 24, 2024	Rofunc-The Full Process Python Package for Robot Learning from Demonstration and Robot Manipulation

selected publications

Rofunc: The Full Process Python Package for Robot Learning from Demonstration and Robot Manipulation

Junjia Liu, Chenzui Li , Donatien Delehelle , Zhihao Li , and Fei Chen

2023

Bib Blog Code Website

@software{liu2023rofunc,
  title = {Rofunc: The Full Process Python Package for Robot Learning from Demonstration and Robot Manipulation},
  author = {Liu, Junjia and Li, Chenzui and Delehelle, Donatien and Li, Zhihao and Chen, Fei},
  year = {2023},
  publisher = {Zenodo},
  doi = {10.5281/zenodo.10016946},
  url = {https://doi.org/10.5281/zenodo.10016946},
  dimensions = {true},
  google_scholar_id = {0EnyYjriUFMC},
}

BiRP: Learning Robot Generalized Bimanual Coordination using Relative Parameterization Method on Human Demonstration

Junjia Liu, Hengyi Sim , Chenzui Li , Kay Chen Tan , and Fei Chen

In 2023 62nd IEEE Conference on Decision and Control (CDC) , 2023

Bib PDF Code

@inproceedings{liu2023birp,
  title = {BiRP: Learning Robot Generalized Bimanual Coordination using Relative Parameterization Method on Human Demonstration},
  author = {Liu, Junjia and Sim, Hengyi and Li, Chenzui and Tan, Kay Chen and Chen, Fei},
  booktitle = {2023 62nd IEEE Conference on Decision and Control (CDC)},
  pages = {8300--8305},
  year = {2023},
  organization = {IEEE},
  dimensions = {true},
  google_scholar_id = {Se3iqnhoufwC},
}

SoftGPT: Learn Goal-Oriented Soft Object Manipulation Skills by Generative Pre-Trained Heterogeneous Graph Transformer

Junjia Liu, Zhihao Li , Wanyu Lin , Sylvain Calinon , Kay Chen Tan , and Fei Chen

In 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2023

Bib PDF

@inproceedings{liu2023softgpt,
  title = {SoftGPT: Learn Goal-Oriented Soft Object Manipulation Skills by Generative Pre-Trained Heterogeneous Graph Transformer},
  author = {Liu, Junjia and Li, Zhihao and Lin, Wanyu and Calinon, Sylvain and Tan, Kay Chen and Chen, Fei},
  booktitle = {2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  pages = {4920--4925},
  year = {2023},
  organization = {IEEE},
  dimensions = {true},
  google_scholar_id = {roLk4NBRz8UC},
}

Robot Cooking with Stir-fry: Bimanual Non-prehensile Manipulation of Semi-fluid Objects

Junjia Liu, Yiting Chen , Zhipeng Dong , Shixiong Wang , Sylvain Calinon , Miao Li , and Fei Chen

IEEE Robotics and Automation Letters, 2022

Bib PDF

@article{liu2022robot,
  title = {Robot Cooking with Stir-fry: Bimanual Non-prehensile Manipulation of Semi-fluid Objects},
  author = {Liu, Junjia and Chen, Yiting and Dong, Zhipeng and Wang, Shixiong and Calinon, Sylvain and Li, Miao and Chen, Fei},
  journal = {IEEE Robotics and Automation Letters},
  volume = {7},
  number = {2},
  pages = {5159--5166},
  year = {2022},
  publisher = {IEEE},
  dimensions = {true},
  google_scholar_id = {qjMakFHDy7sC},
}