Personal Profile

Kailing Guo, Tenure-track Assistant Professor and Ph.D. Supervisor at South China University of Technology, received his Ph.D. through a joint program between South China University of Technology and University of Technology Sydney. His research focuses on low-rank and sparse learning, deep learning optimization and model compression, and multimodal human data processing. In the past five years, he has led one project each from the National Natural Science Foundation of China (Youth Program), Guangdong Provincial Natural Science Foundation, and China Postdoctoral Science Foundation, and has undertaken a key research project under the Guangzhou Major Field R&D Program. He has published over 20 papers in top-tier journals and conferences and has been granted 4 Chinese national invention patents.

Education Background

2011.09—2017.06, South China University of Technology, Information and Communication Engineering (Ph.D. program directly after bachelor's), Supervisor: Xu Xiangmin

2015.01—2017.01, University of Technology Sydney, Joint Ph.D. Training, Supervisor: Dacheng Tao

2007.09—2011.06, South China University of Technology, Information Engineering (Bachelor's)

Work Experience

2020.09-present, South China University of Technology, Tenure-track Assistant Professor

2017.12-2020.09, South China University of Technology, Type II Postdoctoral Fellow (Collaborating Supervisor: Chen Junlong)

Research Projects

National Natural Science Foundation of China (Youth Program): Lightweight Model Design for Deep Convolutional Neural Networks Based on Tensor Structures, 2019.01-2021.12 (Principal Investigator)

China Postdoctoral Science Foundation (General Program, Grade A): Application of Low-Rank Structural Properties in Deep Learning Model Optimization, 2018.05-2020.06 (Principal Investigator)

Guangdong Provincial Natural Science Foundation: Application of Low-Rank and Sparsity Properties in Deep Learning, 2018.05-2021.04 (Principal Investigator)

Guangzhou Major Field R&D Program: Research and Validation of Key Technologies for the Integration of Ultra-High-Definition and 5G Applications, 2021.04-2024.03 (Sub-project Leader)

Flagship Achievements

1. Kailing Guo, Liu Liu, Xiangmin Xu, Dong Xu, and Dacheng Tao, “GoDec+: Fast and Robust Low-rank Matrix Decomposition Based on Maximum Correntropy”, IEEE Transactions on Neural Network and Learning Systems, 2018 (TNNLS, JCR Q1, Impact Factor 11.683).

2. Kailing Guo, Xiangmin Xu, and Dacheng Tao, “Discriminative GoDec+ for Classification”, IEEE Transactions on Signal Processing , 2017(TSP, JCR Q1, Impact Factor 4.203).

3. Zhenquan Lin, Kailing Guo, Xiaofen Xing, Xiangmin Xu, “Weight Evolution: Improving Deep Neural Networks Training through Evolving Inferior Weight Values”, ACM International Conference on Multimedia, 2021(top conference in the field)

4. Bolun cai, Xiangmin Xu, Kailing Guo, Kui Jia, Bin Hu, Dacheng Tao, A Joint Intrinsic-Extrinsic Prior Model for Retinex, IEEE International Conference on Computer Vision, 2017(top conference in the field)

5. Yucheng Cai, Zhuowen Yin, Kailing Guo, Xiangmin Xu, “Pruning the Unimportant or Redundant Filters? Synergy Makes Better”, IEEE International Joint Conference on Neural Networks, 2021(important conference in the field)

1. Kailing Guo, Xinxin Zhou, Xiangmin Xu, "A Model Compression Method and System Based on Joint Quantization and Pruning Search," Chinese Invention Patent ZL202110620864.3

2. Xiangmin Xu, Kailing Guo, Renli Shi, Yongyi Tang, "Behavior Recognition Method Based on Sparse Coding Slow Feature Functions," Chinese Invention Patent ZL201410259135.X

3. Xiangmin Xu, Nanhai Zhang, Kailing Guo, Yuehong Zhong, Yongbin Chen, "An Object Tracking Method Utilizing Motion Blur Information," Chinese Invention Patent ZL201410280387.0

4. Xiangmin Xu, Kailing Guo, Jie Miao, "Scene Awareness Method," Chinese Invention Patent ZL201110039695.0