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— Faculty —

LI, Zhen

Title:

Research Assistant Professor

Education Background

PhD (University of Hong Kong)

Research Field
Deep Learning, Computational Biological and Computer Vision
Email

lizhen@cuhk.edu.cn

Biography:


Dr. Zhen Li got the Bachelor Degree and Master Degree at Sun Yat-Sen University in 2011 and 2014, and Ph.D. at University of Hong Kong in 2018. Dr. Zhen Li was visiting researcher in Toyota Technological Institute at Chicago (TTIC), the University of Chicago in 2016 and 2018. He joined The Chinese University of Hong Kong (Shenzhen) and Shenzhen Research Institute of Big Data (SRIBD) in September 2018.

Dr. Zhen Li is interested in the protein structure prediction from sequence to folding level using data-driven and deep learning algorithms. He is the core team member of protein structure prediction competition (CASP12) champion, which is reward the PLOS Computational Biology Research Prize 2018 in the category Breakthrough Advance/Innovation. He is also interested in machine learning algorithms and the following computer vision topics such as RGB-D semantic segmentation, shape completion and etc.


Academic Publications:


1.     Xiaoguang Han#, Zhen Li#, Haibin Huang, Evangelos Kalogerakis, and Yizhou Yu, High-Resolution Shape Completion Using Deep Neural Networks for Global Structure and Local Geometry Inference, International Conference on Computer Vision (ICCV), Venice, October 2017. (ICCV spotlight, 2.61%) 

2.     Sheng Wang#, Zhen Li#, Yizhou Yu and Jinbo Xu. Folding membrane proteins by deep transfer learning, Cell Systems,2017 5(3):202-211.

3.     Sheng Wang, Siqi Sun, Zhen Li, Renyu Zhang and Jinbo Xu. Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model. PLOS Computational Biology, 2017. (official 1st for CASP12, Highly cited paper of web of science, PLOS Computational Biology Research Prize 2018 in the category Breakthrough Advance/Innovation.).

4.     Zhen Li, Sheng Wang, Yizhou Yu and Jinbo Xu, Predicting membrane protein contacts from non-membrane proteins by deep transfer learning. The 21st International Conference on Research in Computational Molecular Biology (RECOMB) 2017

5.     Zhen Li, Yukang Gan, Xiaodan Liang, Yizhou Yu, Hui Cheng, and Liang Lin, LSTM-CF: Unifying Context Modeling and Fusion with LSTMs for RGB-D Scene Labeling, European Conference on Computer Vision (ECCV), Amsterdam

6.     Zhen Li and Yizhou Yu, Protein Secondary Structure Prediction Using Cascaded Convolutional and Recurrent Neural Networks, Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI), New York

7.     Sheng Wang#, Zhen Li#, Yizhou Yu, Xin Gao†. WaveNano: a signal-level nanopore base-caller via simultaneous prediction of nucleotide labels and move labels through bi-directional WaveNets. Quantitative Biology, 2018.