Chunliang Hao

Dr. Chunliang Hao

Position:

Visitor

Email:

Biography

Chunliang Hao is an research associate in Chinese Academy of Science, and currently also an academic visitor in the iBug Group. He is currently working on affective analysis and affective realated computation system. Chunliang Hao obtained his BEng degree in Computer Science from Zhejiang University in 2005, and then obtained his Master degree in Software Engineering from Peking University in 2008. He then worked in multiple software companies in the position of software engineer. He obtained his Ph.D degree in Computer Science from Institute of Software, Chinese Academy of Science in 2017, and started to work as an research associate afterwards.  

Research Themes:

Face analysis:
Affect analysis

Audiovisual human behaviour analysis:
Affect analysis

HCI:
Integration platform for development of human-centered interfaces, Affect-sensitive HCI

Publications

Conference articles

Tiresias: low-overhead sample based scheduling with task hopping

C. Hao, J. Shen, H. Zhang, Y. Wu, M. Li. Proceedings of the 2016 IEEE International Conference on Cluster Computing. IEEE, 2016.

Bibtex reference [hide]
@inproceedings{hao2016tiresias,
    author = {C. Hao and J. Shen and H. Zhang and Y. Wu and M. Li},
    booktitle = {Proceedings of the 2016 IEEE International Conference on Cluster Computing},
    organization = {IEEE},
    title = {Tiresias: low-overhead sample based scheduling with task hopping},
    year = {2016},
}
Endnote reference [hide]

Sparkle: adaptive sample based scheduling for cluster computing

C. Hao, J. Shen, H. Zhang, X. Zhang, Y. Wu, M. Li. Proceedings of the 5th International Workshop on Cloud Data and Platforms. ACM, 2015.

Bibtex reference [hide]
@inproceedings{hao2015sparkle,
    author = {C. Hao and J. Shen and H. Zhang and X. Zhang and Y. Wu and M. Li},
    booktitle = {Proceedings of the 5th International Workshop on Cloud Data and Platforms},
    organization = {ACM},
    title = {Sparkle: adaptive sample based scheduling for cluster computing},
    year = {2015},
}
Endnote reference [hide]