人员简介

CHANG, Tsung-Hui

Biography

TITLE

Director of Center for Big Data Applications and Technologies, SRIBD

Senior Research Scientist, SRIBD

Associate Professor and the Assistant Dean (Education) of the School of Science and Engineering (SSE), The Chinese University of Hong Kong, Shenzhen

EDUCATION BACKGROUND

PhD (Communications Engineering, National Tsing Hua University, Taiwan)

BS (Electrical Engineering, National Tsing Hua University, Taiwan)

EMAIL

changtsunghui@cuhk.edu.cn

RESEARCH FIELD

Signal Processing; Wireless Communication; Optimization Methods; Smart Grid; Data Analysis

AWARDS

2021 IEEE Signal Processing Society Best Paper Award

2018 IEEE Signal Processing Society Best Paper Award

2015 IEEE Communication Society Asian-Pacific Outstanding Young Researcher Award

2021 Outstanding Faculty Research Awards of the School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen

2014 Young Scholar Research Award of National Taiwan University of Science and Technology

BIOGRAPHY

Tsung-Hui Chang received the B.S. degree in electrical engineering and the Ph.D. degree in communications engineering from the National Tsing Hua University (NTHU), Hsinchu, Taiwan, in 2003 and 2008, respectively. From 2012 to 2015, he was an Assistant Professor with the Department of Electronic and Computer Engineering, National Taiwan University of Science and Technology (NTUST), Taipei, Taiwan. In August 2015, Dr. Chang joined the School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China, as an Assistant Professor, and since August 2018, as an Associate Professor. Prior to being a faculty member, Dr. Chang held research positions with NTHU, from 2008 to 2011, and the University of California, Davis, CA, USA, from 2011 to 2012. During his PhD study, Dr. Chang was a visiting student and research assistant in the University of Minnesota, Minneapolis, MN, USA. His research interests include signal processing and optimization problems in data communications, machine learning and big data analysis.

Dr. Chang received the Young Scholar Research Award of NTUST in 2014, IEEE ComSoc Asian-Pacific Outstanding Young Researcher Award in 2015, and the IEEE Signal Processing Society (SPS) Best Paper Award in 2018 and 2021. He  is a Senior Member of IEEE, an Elected Member of IEEE SPS Signal Processing for Communications and Networking Technical Committee (SPCOM TC) (2020/01-), the Funding Chair of IEEE SPS Integrated Sensing and Communication Technical Working Group (ISAC TWG), and the elected Regional Director-at-Large of IEEE SPS for the Asian-Pacific Region (2022/01-).  He has served the editorial board for major SP journals, including an Associate Editor of IEEE TRANSACTIONS ON SIGNAL PROCESSING (2014/08-2018/12), IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS (2015/01-2018/12), IEEE OPEN JOURNAL OF SIGNAL PROCESSING (2020/01-present), and a Senior Area Editor of IEEE TRANSACTIONS ON SIGNAL PROCESSING (2021/02-present).

ACADEMIC Papers

T.-H. Chang, A. Nedich, and A. Scaglione, " Distributed constrained optimization by consensus-based primal-dual perturbation method," IEEE Trans. Automatic Control, Vol. 59, NO. 6, pp. 1524-1538, Jun. 2014.

K. -Y. Wang, A. M.-C. So, T. -H. Chang, W. -K. Ma and C. -Y. Chi, " Outage constrained robust transmit optimization for multiuser MISO downlinks: Tractable approximations by conic optimization," IEEE Trans. Signal Process. , vol. 62, no. 21, pp. 5690-5705, Nov. 2014. 

T.-H. Chang, M. Hong and X. Wang, " Multi-agent distributed optimization via inexact consensus ADMM," IEEE Trans. Signal Process., Vol. 63, NO. 2, pp. 482-497, Jan. 2015.

T.-H. Chang, M. Hong, W.-C. Liao, and X. Wang," Asynchronous Distributed ADMM for Large-Scale Optimization—Part I: Algorithm and Convergence Analysis," IEEE Trans. Signal Process. , Vol. 64, NO. 12, JUNE 15, 2016.

T.-H. Chang, M. Hong, H.-T. Wai, X. Zhang, S. Lu," Distributed Learning in the Nonconvex World: From batch data to streaming and beyond," IEEE Signal Processing Magazine, Vol. 37, Issue: 3, May 2020.