Introduction

POSITION/TITLE

Research Scientist of SRIBD

Assistant Professor of CUHKSZ

RESEARCH FIELD

Machine Learning, Computer Vision, Optimization, Statistical Process Control, Neural Signal Processing

EMAIL

fanjicong@cuhk.edu.cn

EDUCATION BACKGROUND

Ph.D. Electronic Engineering, City University of Hong Kong, 2013-2018
M.S. Control Science and Engineering, Beijing University of Chemical Technology, 2010-2013
B.S. Automation, Beijing University of Chemical Technology, 2006-2010

PERSONAL INTRODUCTION

Professor Jicong Fan is a Research Scientise of SRIBD, Assistant Professor at the School of Data Science, The Chinese University of Hong Kong, Shenzhen. Professor Fan previously obtained his Ph.D. from the Department of Electronic Engineering, City University of Hong Kong in 2018, and his Master’s degree in Control Science and Engineering and Bachelor’s degree in Automation from Beijing University of Chemical Technology in 2013 and 2010 respectively. Prior to joining CUHK-Shenzhen, he was a postdoc associate at Cornell University. He held research positions at The University of Wisconsin-Madison and The University of Hong Kong in 2018 and 2015 respectively.

Professor Fan's research interests are Artificial Intelligence and Machine Learning. Particularly, he has done a lot of work on matrix/tensor methods, clustering algorithms, anomaly/outlier/fault detection, deep learning, and recommendation system. His research has been published on prestigious journals and conferences such as IEEE TSP/TNNLS/TII, KDD, NeurIPS, CVPR, ICLR, and AAAI. He is a senior member of IEEE and is serving as an associate editor for the journal Neural Processing Letters.

ACADEMIC PUBLICATIONS

[1] Jicong Fan, Lijun Ding, Chengrun Yang, Zhao Zhang, Madeleine Udell. Euclidean-Norm-Induced Schatten-p Quasi-Norm Regularization for Low-Rank Tensor Completion and Tensor Robust Principal Component Analysis. Transactions on Machine Learning Research. 2023.01. 

[2] Jicong Fan, Yiheng Tu, Zhao Zhang, Mingbo Zhao, Haijun Zhang. A Simple Approach to Automated Spectral Clustering. NeurIPS 2022. (acceptance rate=25.6%)

[3] Jinyu Cai, Jicong Fan*. Perturbation Learning Based Anomaly Detection. NeurIPS 2022.

[4] Jicong Fan. Multi-Mode Deep Matrix and Tensor Factorization. ICLR 2022. (acceptance rate=32.3%)

[5] Jicong Fan. Large-Scale Subspace Clustering via k-Factorization. KDD 2021.  (acceptance rate=15.4%)

[6] Jicong Fan, Chengrun Yang, Madeleine Udell. Robust Non-Linear Matrix Factorization for Dictionary Learning, Denoising, and Clustering. IEEE Transactions on Signal Processing, 2021(69): 1755-1770.

[7] Jicong Fan, Lijun Ding, Yudong Chen, Madeleine Udell. Factor group sparse regularization for efficient low-rank matrix recovery. NeurIPS 2019. (acceptance rate=21.1%)

[8] Jicong Fan, Madeleine Udell. Online high-rank matrix completion. CVPR 2019. Oral Presentation. (acceptance rate=5.6%)