ABOUT ME
I am a Ph.D. student in the Department of Electrical and Computer Engineering at Princeton University, working with Prof. Sun-Yuan Kung and Prof. David Wentzlaff, since September 2017 (CV). My research interest lies in generative models, efficient deep learning, and machine learning for systems.
I received my BEng in Electronic and Computer Engineering from Hong Kong University of Science and Technology (HKUST) in June 2017. I spent two wonderful summers at Adobe Research working with Dr. Zhixin Shu, Dr. Yijun Li, Dr. Zhe Lin, Dr. Richard Zhang, and Dr. Federico Perazzi in 2020 and 2021.
Experience
Adobe Research, San Jose, CA, May - November 2021
Research Intern
Advisor: Dr. Zhixin Shu
Adobe Research, San Francisco, CA, May - November 2020
Research Intern
Advisor: Dr. Federico Perazzi and Dr. Zhixin Shu
Princeton University, Princeton, NJ, September 2017 - Present
Research Assistant
Advisor: Prof. Sun-Yuan Kung and Prof. David Wentzlaff
Massachusetts Institute of Technology, Cambridge, MA, June - August 2016
Research Intern
Advisor: Prof. Dina Katabi
Publication
- 3D-FM GAN: Towards 3D-Controllable Face Manipulation
Yuchen Liu, Zhixin Shu, Yijun Li, Zhe Lin, Richard Zhang, and S.Y. Kung
To appear in European Conference on Computer Vision (ECCV 2022).
(arxiv) (webpage) (video) (poster) - Evolving Transferable Neural Pruning Functions
Yuchen Liu, S.Y. Kung, and David Wentzlaff
Genetic and Evolutionary Computation Conference (GECCO 2022).
(paper) (arxiv) (code)
- Class-Discriminative CNN Compression
Yuchen Liu, David Wentzlaff, and S.Y. Kung
International Conference on Pattern Recognition (ICPR 2022).
(paper) (code)
- Content-Aware GAN Compression
Yuchen Liu, Zhixin Shu, Yijun Li, Zhe Lin, Federico Perazzi, and S.Y. Kung
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2021).
(paper) (arxiv) (webpage) (code)
- Rethinking Class-Discrimination Based CNN Channel Pruning
Yuchen Liu, David Wentzlaff, and S.Y. Kung
arXiv preprint arXiv:2004.14492 (2020).
(paper)
- Methodical Design and Trimming of Deep Learning Networks: Enhancing External BP Learning with Internal Omnipresent-supervision Training Paradigm
S.Y. Kung, Zejiang Hou, and Yuchen Liu
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2019). (paper) - Extracting gait velocity and stride length from surrounding radio signals
Chen-Yu Hsu, Yuchen Liu, Zachary Kabelac, Rumen Hristov, Dina Katabi, Christine Liu
ACM Conference on Human Factors in Computing Systems (CHI 2017).
(paper)
Service
- Reviewer - CVPR2021, NeurIPS2021, ICML2022, NeurIPS2022, WACV2023
Awards and Honors
- HKUST Outstanding Undergraduate - HKUST, Hong Kong, May 2017
Awareded to top 3% of graduating undergraduate students - The 14th National Challenge Cup, National Round, Third Prize - HKUST, Hong Kong, October 2015
Innovation competition joined by more than 2.5 million students from over 3,000 institutions - Scholarship Scheme for Continuing Undergraduate Students - HKUST, Hong Kong, 2013 - 2017
Awarded to the top 5% of undergraduate students - Dean's List - HKUST, Hong Kong, 2014 - 2017
Acknowledgement from HKUST's dean to students with excellent academic performance