ABOUT ME
I am a research scientist at Adobe Research where I research in image generative models and efficient deep learning (CV). Before that, I got my Ph.D. in the Department of Electrical and Computer Engineering at Princeton University in Novemeber 2022, fortunately supervised by Prof. Sun-Yuan Kung and Prof. David Wentzlaff. 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. Adobe Research is open to university collaboration in forms of internship and joint projects for motivated students. If you are interested in doing research projects with me, please drop me an email with your CV.
Experience
Adobe Research, San Jose, CA, December 2022 - Present
Research Scientist
Adobe Research, San Jose, CA, May - November 2021
Research Intern
Mentor: Dr. Zhixin Shu
Adobe Research, San Francisco, CA, May - November 2020
Research Intern
Mentor: Dr. Federico Perazzi and Dr. Zhixin Shu
Princeton University, Princeton, NJ, September 2017 - November 2022
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, AAAI2023, CVPR2023, ICML2023
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