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 efficient deep learning, explainable 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 a wonderful summer at Adobe Research working with Dr. Federico Perazzi and Dr. Zhixin Shu in 2020.

Publication

• Content-Aware GAN Compression
  Yuchen Liu, Zhixin Shu, Yijun Li, Zhe Lin, Federico Perazzi, and S.Y. Kung
  To appear in 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)

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