Dr. Chau-Wai Wong, Assistant Professor @ NC State
Research Interests: Machine Learning, Multimedia Forensics, Signal and Image Processing, Data Analytics, Video Coding
Affiliations: Electrical and Computer Engineering, Forensic Sciences Cluster, and Secure Computing Institute
Address:2072 Engr Bldg II, Campus Box 7911
North Carolina State University
Raleigh, NC 27695-7911, USA
Telephone: +1 (919) 515-5202
E-mail: chauwai.wong at ncsu dot edu
Prospective Ph.D. student: My research group has a strong statistical flavor. To make a strong case, a solid undergrad first course in probability/statistics is required. I also assume that you have taken a machine learning/neural network course. In the first two years at NC State as a Ph.D. student, you will be required to take more stat/math courses, in addition to other ECE core courses such as random processes, image processing/computer vision, data science, and convex optimization. Email me your research ideas after reading my papers may increase your likelihood of getting an RA or TA offer. I cannot respond to all emails but it's likely that I'll respond to those emails from students with solid background and containing well-articulated research ideas.
Masters student at NC State: I take Masters students targeting at publishing a journal paper or journal-quality conference paper. If you are interested in, please email me.
Undergrad student at NC State: I take well-prepared, enthusiastic undergrad students for research. You want to be strategic and to take "correct" courses starting from your 2nd year. Make sure you are ahead of your classmates and aiming at building a solid foundation by taking such research-preparation courses as machine learning (online/at NC State), probability/statistics (400-level stat courses preferred, consult me), and linear algebra. The goal of your research will be to obtain solid results that can be published at a renowned international conference. If you are interested in, please email me your plan, resume, and transcript.
Biography
Chau-Wai Wong received his B.Eng. degree with first-class honors in 2008, and an M.Phil. degree in 2010, both in electronic and information engineering from The Hong Kong Polytechnic University, and his Ph.D. degree in electrical engineering from the University of Maryland, College Park, in 2017.
He is currently an Assistant Professor at the Department of Electrical and Computer Engineering, the Forensic Sciences Cluster, and the Secure Computing Institute, North Carolina State University. He was a data scientist at Origin Wireless, Inc., Maryland, USA. He was a Research Assistant with the Media And Security Team (MAST), Department of Electrical and Computer Engineering, University of Maryland, under the supervision of Prof. Min Wu. He was a Research Associate/Assistant with the Centre for Signal Processing, Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, under the supervision of Prof. Wan-Chi Siu. His research interests include machine learning, multimedia forensics, signal and image processing, data analytics, and video coding, with a recent focus on federated learning and generative models.
Dr. Wong was the recipient of multiple scholarships and awards, including an NSF CAREER award, Top-4 Student Paper Award, HSBC Scholarship, Hitachi Scholarship, Chinese Government Award for Outstanding Students Abroad, two-year and four-year merit-based full scholarships for M.Phil. and B.Eng. studies, respectively. He is a senior member of the IEEE and a member of the APSIPA, and he was the general secretary of the IEEE PolyU Student Branch from 2006 to 2007. He is an elected member of IEEE IFS TC (2024–26), IEEE MSA TC (2022–26) and APSIPA IVM TC (2020–24). He was an area chair for ICME’21–24, a workshop chair for MIPR’22, a tutorial chair for VCIP’20, and an area chair for MIPR’19. He has given tutorials at WIFS’21, CVPR’22, and ICASSP’23. He was involved in organizing the third edition of the IEEE Signal Processing Cup in 2016 on electric network frequency forensics. (Click links [1] and [2] for more information.)