Chau-Wai Wong

Assistant Professor
 919-515-5202
  chauwai.wong@ncsu.edu
 Engineering Building II (EB2) 2072
 Campus Box 7911
 Website

Biography

Chau-Wai Wong received the B.Eng. degree with first class honors in 2008, and M.Phil. degree in 2010, both in electronic and information engineering from The Hong Kong Polytechnic University, and the 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 and the Forensic Sciences Cluster, North Carolina State University. He was a data scientist at Origin Wireless, Inc., Greenbelt, Maryland. He was a Research Assistant with the Department of Electrical and Computer Engineering, University of Maryland. He was a Research Associate/Assistant with the Department of Electronic and Information Engineering, Hong Kong Polytechnic University. His research interests include multimedia forensics, signal and image processing, machine learning, data analytics, and video coding.

Dr. Wong was the recipient of multiple scholarships and awards, including Top-4 Student Paper Award, Future Faculty Fellowship, HSBC Scholarship, and Hitachi Scholarship. He is a member of the IEEE and the APSIPA, and he was the general secretary of the IEEE PolyU Student Branch from 2006 to 2007. He was involved in organizing the third edition of the IEEE Signal Processing Cup in 2016 on electric network frequency forensics.

Education

  • Ph.D. 2017
    Electrical Engineering
    University of Maryland, College Park
  • Master's 2010
    Electronic and Information Engineering
    The Hong Kong Polytechnic University, Hong Kong
  • Bachelor's 2008
    Electronic and Information Engineering
    The Hong Kong Polytechnic University, Hong Kong

Recent News

Chau-Wai Wong granted U.S. patent for Method to Detect Counterfeiting

Posted on September 20, 2021 | Filed Under: Research

Chau-Wai Wong was granted an award from University of Maryland and a U.S. patent for an innovative approach to detecting counterfeiting at a microscopic level.

 

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