POSITION/TITLE
X.Q. Deng Presidential Chair Professor of the School of Data Science, The Chinese University of Hong Kong, Shenzhen
Chief Scientist, Shenzhen Research Institute of Big Data
EDUCATION BACKGROUND
Ph.D. South China University of Technology, 1990
M.Sc. South China University of Technology, 1987
B.Sc. South China University of Technology, 1984
RESEARCH FIELD
Speech Information Processing, Natural Language Processing, Neuromorphic Computing, Human-Computer Interface
PERSONAL WEBSITE
haizhouli@cuhk.edu.cn
BIOGRAPHY
Professor Haizhou Li is the X.Q. Deng Presidential Chair Professor in the School of Data Science, The Chinese University of Hong Kong, Shenzhen, China. He is also an Adjunct Professor at the National University of Singapore, Singapore and a Bremen Excellence Chair Professor at the University of Bremen, Germany. Prior to joining CUHK (Shenzhen), Professor Li has taught at Nanyang Technological University and National University of Singapore (2006-2016) in Singapore, University of Eastern Finland (2009) in Finland, and University of New South Wales (2011-2016) in Australia. He was the Principal Scientist and Research Director at the Institute for Infocomm Research (2003-2016), the Agency for Science, Technology and Research, Singapore. Professor Li is an IEEE Fellow, and ISCA Fellow.
Professor Li has served as the Editor-in-Chief of IEEE-ACM Transactions on Audio Speech and Language Processing (2015-2018), Associate Editor of Computer Speech and Language (2012-2021), Springer International Journal of Social Robotics (2008-2021), and a Member of IEEE Speech and Language Processing Technical Committee (2013-2015), Awards Board (2021-2023), and Publications Board (2015-2018) of IEEE Signal Processing Society. He was the President of the International Speech Communication Association (ISCA, 2015-2017), the President of Asia Pacific Signal and Information Processing Association (APSIPA, 2015-2016), the President of the Asian Federation of Natural Language Processing (AFNLP, 2017-2018). He was the General Chair of major scientific conferences including ACL 2012, INTERSPEECH 2014, and ICASSP 2022.
Professor Li was known for his technical contributions to the theory and practice of speaker and language recognition, and to a number of award-winning speech products, such as Apple's Chinese Dictation Kits for Macintosh (1996) and Lernout & Hauspie's Speech-Pen-Keyboard Text Entry Solution for Asian languages (1999). He was the architect of a series of major technology deployments that include TELEFIQS voice-automated call centre service in Singapore Changi International Airport (2001), voiceprint engine for Lenovo A586 Smartphone (2012), and Baidu Music Search (2013).
ACADEMIC PUBLICATIONS
1. Chenglin Xu, Wei Rao, Eng Siong Chng and Haizhou Li, SpEx: Multi-Scale Time Domain Speaker Extraction Network, IEEE/ACM Transaction on Audio, Speech, and Language Processing, vol. 28, pp. 1370-1384, 2020.
2. Chong Zhang, Kay Chen Tan, Haizhou Li, Geok Soon Hong, A Cost-Sensitive Deep Belief Network for Imbalanced Classification, IEEE Transactions on Neural Networks and Learning Systems, vol 30, issue 1, pp. 109-122, 2019.
3. Tomi Kinnunen, Haizhou Li, “An overview of text-independent speaker recognition: From features to supervectors”, Speech Communication, Vol. 52, No. 1, pp. 12-40, 2010.
4. Haizhou Li, Bin Ma and Chin-Hui Lee, "A Vector Space Modeling Approach to Spoken Language Identification", IEEE Transactions on Audio, Speech and Language Processing, Vol 15, No. 1, 2007, pp. 271 – 284.
5. Haizhou Li, Kong Aik Lee, and Bin Ma, “Spoken Language Recognition: From Fundamentals to Practice”, Proceedings of the IEEE, vol. 101, no. 5, pp. 1136-1159, May 2013.
POSITION/TITLE
X.Q. Deng Presidential Chair Professor of the School of Data Science, The Chinese University of Hong Kong, Shenzhen
Chief Scientist, Shenzhen Research Institute of Big Data
EDUCATION BACKGROUND
Ph.D. South China University of Technology, 1990
M.Sc. South China University of Technology, 1987
B.Sc. South China University of Technology, 1984
RESEARCH FIELD
Speech Information Processing, Natural Language Processing, Neuromorphic Computing, Human-Computer Interface
PERSONAL WEBSITE
haizhouli@cuhk.edu.cn
BIOGRAPHY
Professor Haizhou Li is the X.Q. Deng Presidential Chair Professor in the School of Data Science, The Chinese University of Hong Kong, Shenzhen, China. He is also an Adjunct Professor at the National University of Singapore, Singapore and a Bremen Excellence Chair Professor at the University of Bremen, Germany. Prior to joining CUHK (Shenzhen), Professor Li has taught at Nanyang Technological University and National University of Singapore (2006-2016) in Singapore, University of Eastern Finland (2009) in Finland, and University of New South Wales (2011-2016) in Australia. He was the Principal Scientist and Research Director at the Institute for Infocomm Research (2003-2016), the Agency for Science, Technology and Research, Singapore. Professor Li is an IEEE Fellow, and ISCA Fellow.
Professor Li has served as the Editor-in-Chief of IEEE-ACM Transactions on Audio Speech and Language Processing (2015-2018), Associate Editor of Computer Speech and Language (2012-2021), Springer International Journal of Social Robotics (2008-2021), and a Member of IEEE Speech and Language Processing Technical Committee (2013-2015), Awards Board (2021-2023), and Publications Board (2015-2018) of IEEE Signal Processing Society. He was the President of the International Speech Communication Association (ISCA, 2015-2017), the President of Asia Pacific Signal and Information Processing Association (APSIPA, 2015-2016), the President of the Asian Federation of Natural Language Processing (AFNLP, 2017-2018). He was the General Chair of major scientific conferences including ACL 2012, INTERSPEECH 2014, and ICASSP 2022.
Professor Li was known for his technical contributions to the theory and practice of speaker and language recognition, and to a number of award-winning speech products, such as Apple's Chinese Dictation Kits for Macintosh (1996) and Lernout & Hauspie's Speech-Pen-Keyboard Text Entry Solution for Asian languages (1999). He was the architect of a series of major technology deployments that include TELEFIQS voice-automated call centre service in Singapore Changi International Airport (2001), voiceprint engine for Lenovo A586 Smartphone (2012), and Baidu Music Search (2013).
ACADEMIC PUBLICATIONS
1. Chenglin Xu, Wei Rao, Eng Siong Chng and Haizhou Li, SpEx: Multi-Scale Time Domain Speaker Extraction Network, IEEE/ACM Transaction on Audio, Speech, and Language Processing, vol. 28, pp. 1370-1384, 2020.
2. Chong Zhang, Kay Chen Tan, Haizhou Li, Geok Soon Hong, A Cost-Sensitive Deep Belief Network for Imbalanced Classification, IEEE Transactions on Neural Networks and Learning Systems, vol 30, issue 1, pp. 109-122, 2019.
3. Tomi Kinnunen, Haizhou Li, “An overview of text-independent speaker recognition: From features to supervectors”, Speech Communication, Vol. 52, No. 1, pp. 12-40, 2010.
4. Haizhou Li, Bin Ma and Chin-Hui Lee, "A Vector Space Modeling Approach to Spoken Language Identification", IEEE Transactions on Audio, Speech and Language Processing, Vol 15, No. 1, 2007, pp. 271 – 284.
5. Haizhou Li, Kong Aik Lee, and Bin Ma, “Spoken Language Recognition: From Fundamentals to Practice”, Proceedings of the IEEE, vol. 101, no. 5, pp. 1136-1159, May 2013.
POSITION/TITLE
Lab Director of SRIBD
Presidential Chair Professor of CUHKSZ
EDUCATION BACKGROUND
Ph.D. in Statistics, Texas A&M University
B.S. in Probability & Statistics, Minor in Economics, Peking University
RESEARCH FIELD
Spatial Statistics and its applications in Finance, Social Media, Epidemiology and other fields
BIOGRAPHY
Prof. Yongtao Guan is Presidential Chair Professor, Fellow of American Statistical Association. He was Leslie O. Barnes Professor and Chair of Management Science, University of Miami Herbert Business School, Director of Deloitte Institute for Research and Practice in Analytics (DIRPA).
ACADEMIC PUBLICATIONS
1. "Mean Corrected Generalized Estimating Equations for Longitudinal Binary Outcomes with Report Bias",Li, C., Shen, Y., Xiao, Q., Rathbun, S., Huang, H. and Guan, Y.,Biometrics,Submitted
2. "Optimal Frameworks for Detecting Anomalies in Sensor-Intensive Heterogeneous Networks",Moghaddassa, R. and Guan, Y.,INFORMS Journal on Computing,Submitted
3. "Semi-parametric Multi-nomial Logistic Regression for Multivariate Point Pattern Data",Hessellund, K., Xu, G., Guan, Y. andWaagepetersen, R.,Journal of the American Statistical Association, Theory and Methods,to appear
4. "Semi-Parametric Modeling of Structured Point Processes Using Multi-Level Log-Gaussian Cox Processes",Wang, W., Xu, G., Bian, J., Burch, B., Andrade, S., Huang, H., Zhang, J. and Guan, Y.,Journal of Machine Learning Research,21(192),1-39,2020
5. "Nonparametric Estimation of the Pair Correlation Function of Replicated Inhomogeneous Point Processes",Xu, G., Zhao, C., Jalilian, A., Waagepetersen, R., Zhang, J. and Guan, Y.,Electronic Journal of Statistics,14, 3730-3765,2020
POSITION/TITLE
Lab Director of SRIBD
Presidential Chair Professor of CUHKSZ
EDUCATION BACKGROUND
Ph.D. in Statistics, Texas A&M University
B.S. in Probability & Statistics, Minor in Economics, Peking University
RESEARCH FIELD
Spatial Statistics and its applications in Finance, Social Media, Epidemiology and other fields
BIOGRAPHY
Prof. Yongtao Guan is Presidential Chair Professor, Fellow of American Statistical Association. He was Leslie O. Barnes Professor and Chair of Management Science, University of Miami Herbert Business School, Director of Deloitte Institute for Research and Practice in Analytics (DIRPA).
ACADEMIC PUBLICATIONS
1. "Mean Corrected Generalized Estimating Equations for Longitudinal Binary Outcomes with Report Bias",Li, C., Shen, Y., Xiao, Q., Rathbun, S., Huang, H. and Guan, Y.,Biometrics,Submitted
2. "Optimal Frameworks for Detecting Anomalies in Sensor-Intensive Heterogeneous Networks",Moghaddassa, R. and Guan, Y.,INFORMS Journal on Computing,Submitted
3. "Semi-parametric Multi-nomial Logistic Regression for Multivariate Point Pattern Data",Hessellund, K., Xu, G., Guan, Y. andWaagepetersen, R.,Journal of the American Statistical Association, Theory and Methods,to appear
4. "Semi-Parametric Modeling of Structured Point Processes Using Multi-Level Log-Gaussian Cox Processes",Wang, W., Xu, G., Bian, J., Burch, B., Andrade, S., Huang, H., Zhang, J. and Guan, Y.,Journal of Machine Learning Research,21(192),1-39,2020
5. "Nonparametric Estimation of the Pair Correlation Function of Replicated Inhomogeneous Point Processes",Xu, G., Zhao, C., Jalilian, A., Waagepetersen, R., Zhang, J. and Guan, Y.,Electronic Journal of Statistics,14, 3730-3765,2020
X.Q. Deng Presidential Chair Professor
EDUCATION BACKGROUND
PhD, Stanford University
MEng, National University of Singapore
BEng, National University of Singapore
RESEARCH FIELD
Wireless Communications
rzhang@cuhk.edu.cn
BIOGRAPHY
Dr. Rui Zhang received the B.Eng. (First-Class Hons.) and M.Eng. degrees from National University of Singapore, and the Ph.D. degree from Stanford University, Stanford, CA USA, all in electrical engineering. From 2007 to 2009, he worked as a researcher at the Institute for Infocomm Research, ASTAR, Singapore. In 2010, he joined the Department of Electrical and Computer Engineering of National University of Singapore, where he was appointed as a Provost’s Chair Professor in 2020. Since 2022, he has joined the School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, as a Principal’s Diligence Chair Professor. His current research interests include UAV/satellite communication, wireless power transfer, intelligent reflecting surface and reconfigurable MIMO, optimization methods, etc.
He has published over 450 papers in the field of wireless communications, which have been cited more than 60,000 times, with the h-index over 120. He has been listed as a Highly Cited Researcher by Thomson Reuters / Clarivate Analytics since 2015. He was the recipient of the IEEE Communications Society Asia-Pacific Region Best Young Researcher Award in 2011, the Young Researcher Award of National University of Singapore in 2015, the Wireless Communications Technical Committee Recognition Award in 2020, and the IEEE Signal Processing and Computing for Communications (SPCC) Technical Recognition Award in 2021. He received 14 IEEE Best Paper Awards, including the IEEE Marconi Prize Paper Award in Wireless Communications in 2015 and 2020, the IEEE Signal Processing Society Best Paper Award in 2016, the IEEE Communications Society Heinrich Hertz Prize Paper Award in 2017, 2020 and 2022, the IEEE Communications Society Stephen O. Rice Prize in 2021, etc.
He served for over 30 international conferences as the TPC Co-Chair or an Organizing Committee Member, and as the guest editor for 3 special issues in IEEE Journal of Selected Topics in Signal Processing and IEEE Journal on Selected Areas in Communications. He served as an elected member of the IEEE Signal Processing Society SPCOM and SAM Technical Committees, and the Vice Chair of the IEEE Communications Society Asia-Pacific Board Technical Affairs Committee. He served as an editor for the IEEE Transactions on Wireless Communications, IEEE Journal on Selected Areas in Communications (Green Communications and Networking Series), IEEE Transactions on Signal Processing, and IEEE Transactions on Green Communications and Networking. He is now an editor for the IEEE Transactions on Communications. He served as a member of the Steering Committee of the IEEE Wireless Communications Letters, and a Distinguished Lecturer of IEEE Signal Processing Society and IEEE Communications Society. He is a Fellow of the IEEE and the Academy of Engineering, Singapore.
ACADEMIC PUBLICATIONS
1. R. Zhang and C. K. Ho, “MIMO broadcasting for simultaneous wireless information and power transfer,” IEEE Transactions on Wireless Communications, vol. 12, no. 5, pp. 1989-2001, May 2013.
2. H. Ju and R. Zhang, “Throughput maximization in wireless powered communication networks,” IEEE Transactions on Wireless Communications, vol. 13, no. 1, pp. 418-428, January, 2014.
3. Y. Zeng, R. Zhang, and T. J. Lim, “Wireless communications with unmanned aerial vehicles: opportunities and challenges,” IEEE Communications Magazine, vol. 54, no. 5, pp. 36-42, May 2016.
4. Y. Zeng and R. Zhang, “Energy-efficient UAV communication with trajectory optimization,” IEEE Transactions on Wireless Communications, vol. 16, no. 6, pp. 3747- 3760, June 2017.
5. Y. Zeng, B. Clerckx, and R. Zhang, “Communications and signals design for wireless power transmission,” IEEE Transactions on Communications, vol. 65, no. 5, pp. 2264-2290, May 2017.
6. Q. Wu and R. Zhang, “Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming,” IEEE Transactions on Wireless Communications, vol. 18, no. 11, pp. 5394-5409, November 2019.
7. Q. Wu and R. Zhang, “Towards smart and reconfigurable environment: intelligent reflecting surface aided wireless network,” IEEE Communications Magazine, vol. 58, no. 1, pp. 106-112, January 2020.
8. Q. Wu, S. Zhang, B. Zheng, C. You, and R. Zhang, “Intelligent reflecting surface aided wireless communications: a tutorial,” IEEE Transactions on Communications, vol. 69, no. 5, pp. 3313-3351, May 2021.
X.Q. Deng Presidential Chair Professor
EDUCATION BACKGROUND
PhD, Stanford University
MEng, National University of Singapore
BEng, National University of Singapore
RESEARCH FIELD
Wireless Communications
rzhang@cuhk.edu.cn
BIOGRAPHY
Dr. Rui Zhang received the B.Eng. (First-Class Hons.) and M.Eng. degrees from National University of Singapore, and the Ph.D. degree from Stanford University, Stanford, CA USA, all in electrical engineering. From 2007 to 2009, he worked as a researcher at the Institute for Infocomm Research, ASTAR, Singapore. In 2010, he joined the Department of Electrical and Computer Engineering of National University of Singapore, where he was appointed as a Provost’s Chair Professor in 2020. Since 2022, he has joined the School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, as a Principal’s Diligence Chair Professor. His current research interests include UAV/satellite communication, wireless power transfer, intelligent reflecting surface and reconfigurable MIMO, optimization methods, etc.
He has published over 450 papers in the field of wireless communications, which have been cited more than 60,000 times, with the h-index over 120. He has been listed as a Highly Cited Researcher by Thomson Reuters / Clarivate Analytics since 2015. He was the recipient of the IEEE Communications Society Asia-Pacific Region Best Young Researcher Award in 2011, the Young Researcher Award of National University of Singapore in 2015, the Wireless Communications Technical Committee Recognition Award in 2020, and the IEEE Signal Processing and Computing for Communications (SPCC) Technical Recognition Award in 2021. He received 14 IEEE Best Paper Awards, including the IEEE Marconi Prize Paper Award in Wireless Communications in 2015 and 2020, the IEEE Signal Processing Society Best Paper Award in 2016, the IEEE Communications Society Heinrich Hertz Prize Paper Award in 2017, 2020 and 2022, the IEEE Communications Society Stephen O. Rice Prize in 2021, etc.
He served for over 30 international conferences as the TPC Co-Chair or an Organizing Committee Member, and as the guest editor for 3 special issues in IEEE Journal of Selected Topics in Signal Processing and IEEE Journal on Selected Areas in Communications. He served as an elected member of the IEEE Signal Processing Society SPCOM and SAM Technical Committees, and the Vice Chair of the IEEE Communications Society Asia-Pacific Board Technical Affairs Committee. He served as an editor for the IEEE Transactions on Wireless Communications, IEEE Journal on Selected Areas in Communications (Green Communications and Networking Series), IEEE Transactions on Signal Processing, and IEEE Transactions on Green Communications and Networking. He is now an editor for the IEEE Transactions on Communications. He served as a member of the Steering Committee of the IEEE Wireless Communications Letters, and a Distinguished Lecturer of IEEE Signal Processing Society and IEEE Communications Society. He is a Fellow of the IEEE and the Academy of Engineering, Singapore.
ACADEMIC PUBLICATIONS
1. R. Zhang and C. K. Ho, “MIMO broadcasting for simultaneous wireless information and power transfer,” IEEE Transactions on Wireless Communications, vol. 12, no. 5, pp. 1989-2001, May 2013.
2. H. Ju and R. Zhang, “Throughput maximization in wireless powered communication networks,” IEEE Transactions on Wireless Communications, vol. 13, no. 1, pp. 418-428, January, 2014.
3. Y. Zeng, R. Zhang, and T. J. Lim, “Wireless communications with unmanned aerial vehicles: opportunities and challenges,” IEEE Communications Magazine, vol. 54, no. 5, pp. 36-42, May 2016.
4. Y. Zeng and R. Zhang, “Energy-efficient UAV communication with trajectory optimization,” IEEE Transactions on Wireless Communications, vol. 16, no. 6, pp. 3747- 3760, June 2017.
5. Y. Zeng, B. Clerckx, and R. Zhang, “Communications and signals design for wireless power transmission,” IEEE Transactions on Communications, vol. 65, no. 5, pp. 2264-2290, May 2017.
6. Q. Wu and R. Zhang, “Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming,” IEEE Transactions on Wireless Communications, vol. 18, no. 11, pp. 5394-5409, November 2019.
7. Q. Wu and R. Zhang, “Towards smart and reconfigurable environment: intelligent reflecting surface aided wireless network,” IEEE Communications Magazine, vol. 58, no. 1, pp. 106-112, January 2020.
8. Q. Wu, S. Zhang, B. Zheng, C. You, and R. Zhang, “Intelligent reflecting surface aided wireless communications: a tutorial,” IEEE Transactions on Communications, vol. 69, no. 5, pp. 3313-3351, May 2021.
POSITION/TITLE
SRIBD Deputy Director, Research Scientist
RESEARCH FIELD
Economic Statistics, Applied Econometrics, Data Mining
shipei.zeng@sribd.cn
EDUCATION BACKGROUND
Ph.D. Economics, University of New South Wales, Australia
M.A. Economics, Renmin University of China, China
B.A. Economics, Renmin University of China, China
BIOGRAPHY
Dr. Shipei Zeng is a deputy director and research scientist at the Laboratory for Public and Commercial Big Data of SRIBD. He obtained his PhD in economics from the University of New South Wales and his master's and bachelor's degrees in economics from Renmin University of China. He has undertaken a number of government research co-operations as well as projects with large enterprises. His research interests include developing and applying economic statistical models to interdisciplinary fields. He has published his work in several reputable international journals, and won numerous awards in data competitions for his use of big data and machine learning techniques. He is also the developer of the R package "dfvad" approved by CRAN, which is designed for analyzing economic growth and productivity.
ACADEMIC PUBLICATIONS
- Shipei Zeng. Frontier firms, inefficiency and productivity dynamics. 36th International Association for Research in Income and Wealth General Conference. Oslo, Norway (Online), from 2021-8-23 to 2021-8-27
- Shipei Zeng. Hedonic imputation with tree-based decision approaches. 36th International Association for Research in Income and Wealth General Conference. Oslo, Norway (Online), from 2021-8-23 to 2021-8-27
- Shipei Zeng; Zhan-Ming Chen; Ahmed Alsaedi; Tasawar Hayat. Price elasticity, block tariffs, and equity of natural gas demand in China: Investigation based on household-level survey data. Journal of Cleaner Production, 2018, 179: 441-449 (SCI, JCR Q1)
- Zhan-Ming Chen; Shipei Zeng; Leo Lester; Lin-Ting Zhang; Xiaohua Xia; Shiyun Xu; Ahmed Alsaedi; Tasawar Hayat. Economic cost of China’s oil import: Welfare estimation for 2001–2015. Resources, Conservation and Recycling, 2018, 132: 158-167 (SCI, JCR Q1)
- Shipei Zeng; Zhanming Chen. Impact of fossil fuel subsidy reform in China: Estimations of household welfare effects based on 2007–2012 data. Economic and Political Studies, 2016, 4: 299-318
POSITION/TITLE
Associate Director of the Data-driven Intelligent Information System Laboratory
Research Scientist
RESEARCH INTEREST
Edge Intelligence, Federated Learning, Integrated Communications and Sensing
gxzhu@sribd.cn
EDUCATION BACKGROUND
From 2015-9 to 2019-12, The University of Hong Kong, Electronic and Electrical Engineering, PhD, Supervisor: Kaibin Huang
From 2012-9 to 2015-3, Zhejiang University, Information and Electronic Engineering, Master, Supervisor: Caijun Zhong
From 2008-9 to 2012-6, Zhejiang University, Information and Electronic Engineering, bachelor
HONORS AND AWARDS
- Best paper award at 2013 International Conference on WCSP.
- Hong Kong Ph.D. Fellowship. (09/2015 - 08/2019)
- Outstanding Ph.D. Thesis Award at The University of Hong Kong
- Exemplary Reviewer at IEEE Transactions on Communications
- Shenzhen Overseas High-Caliber Personnel (Level C)
BIOGRAPHY
Dr. Guangxu Zhu is a research scientist at the Shenzhen research institute of big data. He received the Ph.D. degree in electrical and electronic engineering from The University of Hong Kong in 2019, and the BS and MS degrees in information and communication engineering from Zhejiang University in 2012 and 2015, respectively. His research interests include intelligent edge, federated learning, and integrated sensing and communications. He have published over 30 top-tier journal papers and more than 20 conference papers in his research area. He is currently hosting several national and provincial project including NSFC Youth Program, Guangdong Natural Science Foundation General Program, and the 6G open project of China Academy of Information and Communications Technology and participating the National Key Research and Development Program of China. He is a recipient of the Hong Kong Postgraduate Fellowship (HKPF), Outstanding Ph.D. Thesis Award from HKU, and Best Paper Award from WCSP 2013, Shenzhen Overseas High-Caliber Personnel (Level C). He was invited to be a co-chair for the “MAC and cross-layer design” track in IEEE PIMRC 2021.
SELECTED JOURNAL PUBLICATIONS
1.G. Zhu, D. Liu, Y, Du, C. You, J. Zhang, and K. Huang, "Toward an Intelligent Edge: Wireless Communication Meets Machine Learning", IEEE Commun. Mag., vol. 58, no. 1, pp. 19 - 25, Jan. 2020. ( ESI highly cited paper, ESI hot paper)
2. G. Zhu, Y. Wang K. Huang, "Broadband analog aggregation for low-latency federated edge learning", IEEE Trans. Wireless Commun., vol. 19, no. 1, pp. 491-506, Jan. 2020. ( ESI highly cited paper)
3. G. Zhu, Y. Du, D. Gunduz, K. Huang, "One-Bit Over-the-Air Aggregation for Communication-Efficient Federated Edge Learning: Design and Convergence Analysis", IEEE Trans. Wireless Commun., vol. 20, no. 3, Mar. 2021.
4. G. Zhu, K. Huang, V. K. N. Lau, B. Xia, X. Li and S. Zhang, "Hybrid beamforming via the Kronecker decomposition for the millimeter-wave massive MIMO systems", IEEE J. Sel Area Commun., Vol. 35, no. 9, pp. 2097–2114, Sep. 2017.
5.G. Zhu and K. Huang, "MIMO Over-the-Air Computation for High-Mobility Multi-Modal Sensing", IEEE IoT Journal, vol. 6, no. 4, pp. 6089 - 6103, Aug. 2019.
POSITION/TITLE
Research Scientist
Assistant Director
PROFESSIONAL EXPERIENCES
2020/10 to present, Shenzhen Research Institute of Big Data, Research Scientist, Position
2019/01 to 2020/09, CUHKSZ, Postdoc Researcher, Position
EDUCATION BACKGROUND
2013/09 to 2018/12, Xidian University, Signal and Information Processing, Ph.D
2009/09 to 2013/06, Xidian University, Electronic Information Engineering, Bachelor
wpu@sribd.cn
PERSONAL WEBSITE
https://wqpu.github.io
RESEARCH FIELD
Signal Processing, Optimization Methods，Machine Learning
BIOGRAPHY
Wenqiang Pu received the B.S. and Ph.D degrees from Xidian University, in 2013 and 2018, respectively. During Jan. 2015 to Sep. 2018, he was a visiting Ph.D student at the Chinese University of Hong Kong (Shenzhen). From Jan. 2019 to Sep. 2020, he was a postdoc researcher with CUHKSZ. He joined SRIBD since Oct. 2020. His research interests include large scale signal processing, resource allocation in sensor network, and optimization algorithms. He has published many papers in journals / conferences on signal processing, including 2 ESI highly cited papers. At present, he hosts the youth project of the National Natural Science Foundation of China.
ACADEMIC PUBLICATIONS
- Pu, W.*, Ibrahim, S., Fu, X., & Hong, M. (2022). Stochastic mirror descent for low-rank tensor decomposition under non-Euclidean losses. IEEE Transactions on Signal Processing, 70, 1803-1818.
- Pu, W.*, Xiao, J., Zhang, T., & Luo, Z. Q. (2022). A Penalized Inequality-Constrained Approach for Robust Beamforming with DoF Limitation. Signal Processing, 108746.
- Sun, H., Pu, W., Fu, X., Chang, T. H., & Hong, M.* (2022). Learning to continuously optimize wireless resource in a dynamic environment: A bilevel optimization perspective. IEEE Transactions on Signal Processing, 70, 1900-1917.
- Yan, J., Pu, W.*, Liu, H.*, Jiu, B., & Bao, Z. (2018). Robust chance constrained power allocation scheme for multiple target localization in colocated MIMO radar system. IEEE Transactions on Signal Processing, 66(15), 3946-3957.
- Pu, W., Liu, Y. F., Yan, J., Liu, H., & Luo, Z. Q*. (2018). Optimal estimation of sensor biases for asynchronous multi-sensor data fusion. Mathematical Programming, 170(1), 357-386.
POSITION/TITLE
Research Scientist
RESEARCH FIELD
Radio Resource Management, Learning to Optimize, Large-Scale Optimization, Massive Random Access
liyang@sribd.cn
EDUCATION BACKGROUND
Ph.D. The University of Hong Kong
M.E Beihang University
B.E Beihang University
BIOGRAPHY
Dr. Yang Li received his B.E. and M.E. degrees in Electronic Information Engineering from Beihang University, Beijing, China, in 2012 and 2015, respectively, and his Ph.D. in Electrical and Electronic Engineering from The University of Hong Kong (HKU) in 2019. He has a long-standing commitment to research at the intersection of wireless communications, artificial intelligence, and large-scale optimization, with extensive experience and innovative results in areas such as massive MIMO signal processing, learning to optimize, and the design of distributed optimization algorithms. From 2019 to 2020, he served as a Senior Research Engineer at Huawei Noah's Ark Laboratory, where he conducted research on intelligent communication algorithms and achieved breakthrough results in the intelligent design of nested polar codes, earning him the Innovation Pioneer Award from Huawei Technologies Co., Ltd. Currently, he holds the position of Research Scientist at the Shenzhen Research Institute of Big Data, where in recent years he has led projects in large-scale wireless resource management, large-scale network optimization, and large-scale intelligent access. He has presided over the National Natural Science Foundation of China's (NSFC's) Youth Fund, the sub-project of the National Key R&D Program, and the open project of National Key Laboratory, and has participated as the principal investigator in the joint fund project of the NSFC. His research has resulted in the publication of over 30 high-level papers in top international journals in the fields of wireless communications and signal processing, such as IEEE Transactions on Wireless Communications and IEEE Transactions on Signal Processing, including over 20 as the first author or corresponding author.
ACADEMIC PUBLICATIONS
[1] Yang Li and Ya-Feng Liu, “HPE Transformer: Learning to Optimize Multi-Group Multicast Beamforming Under Nonconvex QoS Constraints,” IEEE Transactions on Communications, early access, Apr. 2024.
[2] Hao Zhang, Qingfeng Lin, Yang Li*, Lei Cheng, and Yik-Chung Wu, “Activity Detection for Massive Connectivity in Cell-free Networks with Unknown Large-scale Fading, Channel Statistics, Noise Variance, and Active Probability: A Bayesian Approach,” IEEE Transactions on Signal Processing, vol. 72, pp. 942-957, 2024.
[3] Yunqi Wang, Yang Li*, Qingjiang Shi, and Yik-Chung Wu, “ENGNN: A General Edge-Update Empowered GNN Architecture for Radio Resource Management in Wireless Networks,” IEEE Transactions on Wireless Communications, early access, Oct. 2023.
[4] Yang Li, Zhilin Chen, Yunqi Wang, Chenyang Yang, Bo Ai, and Yik-Chung Wu, “Heterogeneous Transformer: A Scale Adaptable Neural Network Architecture for Device Activity Detection,” IEEE Transactions on Wireless Communications, vol. 22, no. 5, pp. 3432-3446, May 2023.
[5] Yang Li, Qingfeng Lin, Ya-Feng Liu, Bo Ai, and Yik-Chung Wu, “Asynchronous Activity Detection for Cell-Free Massive MIMO: From Centralized to Distributed Algorithms,” IEEE Transactions on Wireless Communications, vol. 22, no. 4, pp. 2477-2492, Apr. 2023.
POSITION/TITLE
Research Scientist
RESEARCH FIELD
Radio Resource Management, Learning to Optimize, Large-Scale Optimization, Massive Random Access
liyang@sribd.cn
EDUCATION BACKGROUND
Ph.D. The University of Hong Kong
M.E Beihang University
B.E Beihang University
BIOGRAPHY
Dr. Yang Li received his B.E. and M.E. degrees in Electronic Information Engineering from Beihang University, Beijing, China, in 2012 and 2015, respectively, and his Ph.D. in Electrical and Electronic Engineering from The University of Hong Kong (HKU) in 2019. He has a long-standing commitment to research at the intersection of wireless communications, artificial intelligence, and large-scale optimization, with extensive experience and innovative results in areas such as massive MIMO signal processing, learning to optimize, and the design of distributed optimization algorithms. From 2019 to 2020, he served as a Senior Research Engineer at Huawei Noah's Ark Laboratory, where he conducted research on intelligent communication algorithms and achieved breakthrough results in the intelligent design of nested polar codes, earning him the Innovation Pioneer Award from Huawei Technologies Co., Ltd. Currently, he holds the position of Research Scientist at the Shenzhen Research Institute of Big Data, where in recent years he has led projects in large-scale wireless resource management, large-scale network optimization, and large-scale intelligent access. He has presided over the National Natural Science Foundation of China's (NSFC's) Youth Fund, the sub-project of the National Key R&D Program, and the open project of National Key Laboratory, and has participated as the principal investigator in the joint fund project of the NSFC. His research has resulted in the publication of over 30 high-level papers in top international journals in the fields of wireless communications and signal processing, such as IEEE Transactions on Wireless Communications and IEEE Transactions on Signal Processing, including over 20 as the first author or corresponding author.
ACADEMIC PUBLICATIONS
[1] Yang Li and Ya-Feng Liu, “HPE Transformer: Learning to Optimize Multi-Group Multicast Beamforming Under Nonconvex QoS Constraints,” IEEE Transactions on Communications, early access, Apr. 2024.
[2] Hao Zhang, Qingfeng Lin, Yang Li*, Lei Cheng, and Yik-Chung Wu, “Activity Detection for Massive Connectivity in Cell-free Networks with Unknown Large-scale Fading, Channel Statistics, Noise Variance, and Active Probability: A Bayesian Approach,” IEEE Transactions on Signal Processing, vol. 72, pp. 942-957, 2024.
[3] Yunqi Wang, Yang Li*, Qingjiang Shi, and Yik-Chung Wu, “ENGNN: A General Edge-Update Empowered GNN Architecture for Radio Resource Management in Wireless Networks,” IEEE Transactions on Wireless Communications, early access, Oct. 2023.
[4] Yang Li, Zhilin Chen, Yunqi Wang, Chenyang Yang, Bo Ai, and Yik-Chung Wu, “Heterogeneous Transformer: A Scale Adaptable Neural Network Architecture for Device Activity Detection,” IEEE Transactions on Wireless Communications, vol. 22, no. 5, pp. 3432-3446, May 2023.
[5] Yang Li, Qingfeng Lin, Ya-Feng Liu, Bo Ai, and Yik-Chung Wu, “Asynchronous Activity Detection for Cell-Free Massive MIMO: From Centralized to Distributed Algorithms,” IEEE Transactions on Wireless Communications, vol. 22, no. 4, pp. 2477-2492, Apr. 2023.
POSITION/TITLE
Research Scientist
RESEARCH FIELD
Machine learning, non-convex optimization, online learning, federated learning, applications of artificial intelligence in communication networks, digital twins, and other interdisciplinary fields intersecting machine learning and communication.
PERSONAL WEBSITE
https://yokoxue.github.io/
yokoxue@sribd.cn
EDUCATION BACKGROUND
The Hong Kong University of Science and Technology, PhD
Southeast University, Bachelor
BIOGRAPHY
Dr. Xue Ye obtained his Bachelor's degree in Communication Engineering from Southeast University in 2017 and his PhD degree from the School of Electronic and Computer Engineering at the Hong Kong University of Science and Technology in 2022. In the same year, he joined the Shenzhen Research Institute of Big Data as a research scientist. Dr. Xue has been engaged in research in the interdisciplinary fields of non-convex optimization, high-dimensional statistics, machine learning, and communication networks for many years. He has published over ten academic papers as the first author in high-level international journals and conferences in the fields of artificial intelligence and wireless communication, collaborating closely with numerous renowned scholars both domestically and internationally. Currently, he is actively involved as a key member in national key R&D projects.
ACADEMIC PUBLICATIONS
- Y. Xue and V. Lau, “Riemannian Low-Rank Model Compression for Federated Learning with Over-the-Air Aggregation” IEEE Transactions on Signal Processing, 2023
- Ye Xue; Vincent K. N. Lau ; Online Orthogonal Dictionary Learning Based on Frank-Wolfe Method, IEEE Transactions on Neural Networks and Learning Systems, 2021, 1-15
- Ye Xue; Vincent K. N. Lau; Songfu Cai ; Efficient Sparse Coding Using Hierarchical Riemannian Pursuit, IEEE Transactions on Signal Processing, 2021, 69: 4069-4084
- Ye Xue; Yifei Shen; Vincent K. N. Lau; Jun Zhang; Khaled B. Letaief ; Blind Data Detection in Massive MIMO via ℓ₃-Norm Maximization Over the Stiefel Manifold, IEEE Transactions on Wireless Communications, 2021, 20(2): 1411-1424
- Y. Xue*, Y. Shen, J. Zhang, K. Letaief, and V. Lau, “Complete dictionary learning via ℓp-norm maximization,” Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:280-289, 2020. （Co-first Author）
- Ye Xue; Liqun Su; Vincent K. N. Lau ; FedOComp: Two-Timescale Online Gradient Compression for Over-the-Air Federated Learning, IEEE Internet of Things Journal, 2022
POSITION/TITLE
Research Scientist
RESEARCH FIELD
Machine learning, non-convex optimization, online learning, federated learning, applications of artificial intelligence in communication networks, digital twins, and other interdisciplinary fields intersecting machine learning and communication.
PERSONAL WEBSITE
https://yokoxue.github.io/
yokoxue@sribd.cn
EDUCATION BACKGROUND
The Hong Kong University of Science and Technology, PhD
Southeast University, Bachelor
BIOGRAPHY
Dr. Xue Ye obtained his Bachelor's degree in Communication Engineering from Southeast University in 2017 and his PhD degree from the School of Electronic and Computer Engineering at the Hong Kong University of Science and Technology in 2022. In the same year, he joined the Shenzhen Research Institute of Big Data as a research scientist. Dr. Xue has been engaged in research in the interdisciplinary fields of non-convex optimization, high-dimensional statistics, machine learning, and communication networks for many years. He has published over ten academic papers as the first author in high-level international journals and conferences in the fields of artificial intelligence and wireless communication, collaborating closely with numerous renowned scholars both domestically and internationally. Currently, he is actively involved as a key member in national key R&D projects.
ACADEMIC PUBLICATIONS
- Y. Xue and V. Lau, “Riemannian Low-Rank Model Compression for Federated Learning with Over-the-Air Aggregation” IEEE Transactions on Signal Processing, 2023
- Ye Xue; Vincent K. N. Lau ; Online Orthogonal Dictionary Learning Based on Frank-Wolfe Method, IEEE Transactions on Neural Networks and Learning Systems, 2021, 1-15
- Ye Xue; Vincent K. N. Lau; Songfu Cai ; Efficient Sparse Coding Using Hierarchical Riemannian Pursuit, IEEE Transactions on Signal Processing, 2021, 69: 4069-4084
- Ye Xue; Yifei Shen; Vincent K. N. Lau; Jun Zhang; Khaled B. Letaief ; Blind Data Detection in Massive MIMO via ℓ₃-Norm Maximization Over the Stiefel Manifold, IEEE Transactions on Wireless Communications, 2021, 20(2): 1411-1424
- Y. Xue*, Y. Shen, J. Zhang, K. Letaief, and V. Lau, “Complete dictionary learning via ℓp-norm maximization,” Proceedings of the 36th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 124:280-289, 2020. （Co-first Author）
- Ye Xue; Liqun Su; Vincent K. N. Lau ; FedOComp: Two-Timescale Online Gradient Compression for Over-the-Air Federated Learning, IEEE Internet of Things Journal, 2022
POSITION/TITLE
Research Scientist
EDUCATION BACKGROUND
Hongkong University of Science and Technology Electronic and Computer Engineering Ph.D.
Xi’an Jiaotong University Information Engineering Bachelor's degree
schai@sribd.cn
RESEARCH FIELD
Wireless communication and networks, Reinforcement learning, UAV communication
MAJOR ACHIEVEMENTS/HONORS
2014-Hongkong Ph.D. Fellowship
BIOGRAPHY
Shuqi Chai received the B.Eng. degree in electronic and information engineering from Xi’an Jiaotong University, and she received the Ph.D. degree in electronic and computer engineering from Hongkong University of Science and Technology in Jan 2022. She is currently a Research Scientist with the Shenzhen Research Institute of Big Data. Her research interests include MDP, dynamic programming, reinforcement learning in wireless communication systems, UAV trajectory and communication design.
ACADEMIC PUBLICATIONS
1.Shuqi Chai, Vincent Lau, "Joint Rate and Power Optimization for Multimedia Streaming in Wireless Fading Channels via Parametric Policy Gradient", IEEE Transactions on Signal Processing, accepted.
2.Shuqi Chai, Vincent Lau "Online Trajectory and Radio Resource Optimization of Cached-Enabled UAV Wireless Networks with Content and Energy Recharging", IEEE Transactions on Signal Processing, accepted.
3.Shuqi Chai, Vincent Lau "Multi-UAV Trajectory and Power Optimization for Cached UAV Wireless Networks with Energy and Content Recharging - Demand Driven Deep Learning Approach" , IEEE JSAC SI-UAV-B5G 2021, accepted.
4.Shuqi Chai, Vincent Lau "Mixed-Timescale Request-Driven User Association, Trajectory and Radio Resource Control for Cache-Enabled Multi-UAV Networks", IEEE Transactions on Signal Processing, accepted.
5.Shuqi Chai, Vincent Lau "Online Trajectory and Radio Resource Optimization for Cache-enabled Multi-UAV Networks", IEEE ICC'21, accepted.
POSITION/TITLE
Research Scientist
EDUCATION BACKGROUND
Hongkong University of Science and Technology Electronic and Computer Engineering Ph.D.
Xi’an Jiaotong University Information Engineering Bachelor's degree
schai@sribd.cn
RESEARCH FIELD
Wireless communication and networks, Reinforcement learning, UAV communication
MAJOR ACHIEVEMENTS/HONORS
2014-Hongkong Ph.D. Fellowship
BIOGRAPHY
Shuqi Chai received the B.Eng. degree in electronic and information engineering from Xi’an Jiaotong University, and she received the Ph.D. degree in electronic and computer engineering from Hongkong University of Science and Technology in Jan 2022. She is currently a Research Scientist with the Shenzhen Research Institute of Big Data. Her research interests include MDP, dynamic programming, reinforcement learning in wireless communication systems, UAV trajectory and communication design.
ACADEMIC PUBLICATIONS
1.Shuqi Chai, Vincent Lau, "Joint Rate and Power Optimization for Multimedia Streaming in Wireless Fading Channels via Parametric Policy Gradient", IEEE Transactions on Signal Processing, accepted.
2.Shuqi Chai, Vincent Lau "Online Trajectory and Radio Resource Optimization of Cached-Enabled UAV Wireless Networks with Content and Energy Recharging", IEEE Transactions on Signal Processing, accepted.
3.Shuqi Chai, Vincent Lau "Multi-UAV Trajectory and Power Optimization for Cached UAV Wireless Networks with Energy and Content Recharging - Demand Driven Deep Learning Approach" , IEEE JSAC SI-UAV-B5G 2021, accepted.
4.Shuqi Chai, Vincent Lau "Mixed-Timescale Request-Driven User Association, Trajectory and Radio Resource Control for Cache-Enabled Multi-UAV Networks", IEEE Transactions on Signal Processing, accepted.
5.Shuqi Chai, Vincent Lau "Online Trajectory and Radio Resource Optimization for Cache-enabled Multi-UAV Networks", IEEE ICC'21, accepted.
