Professor Zhi-Quan (Tom) Luo received his BSc degree in Applied Mathematics from Peking University, China, in 1984. In the same year, he was selected by a joint AMS-SIAM committee and the Ministry of Education of China for graduate study in the United States (S.S. Chern Program). Following a 12-month intensive training in English and Mathematics, he enrolled in the Massachusetts Institute of Technology where he received a PhD degree in Operations Research in 1989. From 1989 to 2003, he was on the faculty in the Department of Electrical and Computer Engineering, McMaster University, Canada where he eventually served as the department head and was awarded a Canada Research Chair (Tier I) in Information Processing. From 2003 to 2014, Professor Luo has been a full professor at the Department of Electrical and Computer Engineering, University of Minnesota and held an endowed ADC Chair in digital technology. Currently, Professor Luo serves as the Vice President (Academic) of The Chinese University of Hong Kong, Shenzhen, and concurrently the Director of Shenzhen Research Institute of Big Data and also the Director of CUHK(SZ)-Tencent AI Lab Joint Laboratory on Machine Intelligence.
Professor Luo received the 2010 Farkas Prize from the INFORMS Optimization Society for outstanding contributions to the field of optimization. In 2018, he was awarded the prize of Paul Y. Tseng Memorial Lectureship in Continuous Optimization. He also received three Best Paper Awards from the IEEE Signal Processing Society in 2004, 2009 and 2011 respectively, and a 2011 Best Paper Award from the EURASIP. Professor Luo is a Fellow of the Institute of Electrical and Electronics Engineers (IEEE) and a Fellow of the Society for Industrial and Applied Mathematics (SIAM). In 2014, he was elected to the Royal Society of Canada, the highest honor a Canadian scholar can achieve in the Arts, Humanities and Sciences.
Professor Luo’s research mainly addresses mathematical issues in information sciences, with particular focus on the design, analysis and applications of optimization algorithms. Professor Luo consults regularly with industry on topics related to signal processing and digital communication. Professor Luo was the semi-plenary speaker for the International Symposium on Mathematical Programming in 2003 and IEEE CDC conference in 2011, the distinguished lecturer for the IEEE Sensor Array and Multichannel Signal Processing Workshop in 2006, the plenary speaker for the IEEE Signal Processing Advance for Wireless Communications (SPAWC) Workshop in 2013, and IEEE Signal Processing Theory and Methods Workshop in 2014. Professor Luo has served as the Chair of the IEEE Signal Processing Society Technical Committee on Signal Processing for Communications (SPCOM). He was the Editor in Chief for IEEE Transactions on Signal Processing from 2012 to 2014 and served as the Associate Editor for many internationally recognized journals, including Mathematics of Operations Research, Management Science, Mathematical Programming and others.
2018-present CUHK (SZ)-Tencent AI Lab Joint Laboratory on Machine Intelligence, Shenzhen, China
2015-present Shenzhen Research Institute of Big Data, Shenzhen, China
2014-present The Chinese University of Hong Kong, Shenzhen
Vice President (Academic), Presidential Chair Professor
2003-present Dept. of Electrical and Computer Engineering, University of Minnesota
Professor, on leave since 2014
2003-2013 Dept. of Electrical and Computer Engineering, University of Minnesota
Professor and ADC Chair in Digital Technology
2001-2004 Dept. of Electrical and Computer Engineering, McMaster University
Canada Research Chair (Tier I) in Information Processing
2000-2003 Dept. of Electrical and Computer Engineering, McMaster University
1998-2005 Dept. of Electrical and Computer Engineering, McMaster University
1992-2003 Dept. of Computing and Software, McMaster University
1993-1998 Dept. of Electrical and Computer Engineering, McMaster University
Tenured Associate Professor
1989-1993 Dept. of Electrical and Computer Engineering, McMaster University
Tenured Track Assistant Professor
1986-1989 Laboratory for Information and Decision Systems, MIT
1985 Center for Technology, Policy and Industrial Development, MIT
Prof. Luo Zhi-Quan heads a team engaged in the theory, design and analysis of efficient optimization algorithms with application to big data analytics, machine learning, digital communication and digital signal processing. His team has also worked with range of organizations including national governing bodies, IT companies and research institutes, allowing it to answer research questions from different angles.
Currently, we are recruiting postdocs and graduate students. Prof. Luo is looking for students who are creative, hard-working and insightful. If you are interested in getting involved, please contact us.
Current PhD students:
Zhang Jiawei, Mao Jingwei, Liang Hao, Tang Liping, Xiao Jianchong，Ren Shuyi, Zhang Tianjian，Wang Boyuan, Li Yingru, Liu Xiang, Chen Congliang, Wang Wenxuan
1. Wenqiang Pu, Ya-Feng Liu, Junkun Yan, Hongwei Liu, Zhi-Quan Luo, “Optimal estimation of sensor biases for asynchronous multi-sensor data fusion”, Math. Program. 170(1): 357-386 (2018).
2. Wei-Cheng Liao, Zhi-Quan Luo, Ivo Merks, Mingyi Hong, Tao Zhang, "Hearing assistance device with beamformer optimized using a priori spatial information." U.S. Patent 9,949,041, issued 04/17, 2018.
3. Wenqiang Pu, Jinjun Xiao, Tao Zhang, Zhi-Quan Luo, “An optimization model for electroencephalography-assisted binaural beamforming”, The Journal of the Acoustical Society of America, vol. 143, issue 3, pp. 1744-1744, Mar. 2018.
4. Wei-Cheng Liao, Mingyi Hong, Hamidreza Farmanbar, Zhi-Quan Luo, “A Distributed Semi-Asynchronous Algorithm for Network Traffic Engineering”, IEEE Transactions on Signal and Information Processing over Networks, June 2017.
5. Fanhua Shang, James Cheng, Yuanyuan Liu, Zhi-Quan Luo, Zhouchen Lin, “Bilinear factor matrix norm minimization for robust pca: Algorithms and applications”, IEEE transactions on pattern analysis and machine intelligence, Sept. 2017.
6. Marco Locatelli, Zhi-Quan Luo, “On the Complexity of Optimal Power Allocation in a Multi-Tone Multiuser Communication System”, IEEE Transactions on Information Theory, vol. 63, no. 10, pp. 6622-6627, Aug. 2017.
7. Nan Zhang, Ya-Feng Liu, Hamid Farmanbar, Tsung-Hui Chang, Mingyi Hong, Zhi-Quan Luo, “Network slicing for service-oriented networks under resource constraints”, IEEE Journal on Selected Areas in Communications, vol. 35, no. 11, pp. 2512-2521, Nov. 2017.
8. Nan Zhang, Zhiqiang Yao, Yixian Liu, Stephen P. Boyd, Zhi-Quan Luo: Dynamic Resource Allocation for Energy Efficient Transmission in Digital Subscriber Lines. IEEE Trans. Signal Processing 65(16): 4353-4366 (2017).
9. Mingyi Hong and Zhi-Quan Luo*, “On the Linear Convergence of the Alternating Direction Method of Multipliers”, Vol. 162, No.1, pages 165–199, Mathematical Programming Series A, 2017.
10. Mingyi Hong, Xiangfeng Wang, Meisam Razaviyayn and Zhi-Quan Luo*, “Iterations Complexity Analysis of Block Coordinate Descent Method”, Vol. 163, No. 1, pages 85 - 114, Mathematical Programming Series A, 2017.
11. Yunbin Zhao and Zhi-Quan Luo*, “Constructing new weighted l1-algorithms for the sparsest points of polyhedral sets”. Mathematics of Operations Research, 42(1), 57-76, 2017.
12. M. Razaviyayn and Z.-Q. Luo*, “A Stochastic Successive Minimization Method for Nonsmooth Nonconvex Optimization with Applications to Transceiver Design in Wireless Communication Networks”, Mathematical Programming, vol. 157, no. 2, pp 515–545, June 2016.
13. M. Hong, Z.-Q. Luo* and M. Razaviyayn, “Convergence Analysis of Alternating Direction Method of Multipliers for A Family of Nonconvex Problems”, SIAM Journal on Optimization, vol. 26, no. 1, pp. 337-364, Jan 2016.
14. M. Hong, M. Razaviyayn, Z.-Q. Luo* and J.S. Pang, “A Unified Algorithmic Framework for Block-Structured Optimization Involving Big Data with Applications in Machine Learning and Signal Processing,” IEEE Signal Processing Magazine, Vol. 33, pp. 57-77, 2016.
15. R. Sun and Z. Q. Luo*, "Guaranteed Matrix Completion via Non-Convex Factorization," IEEE Transactions on Information Theory, vol. 62, no. 11, pp. 6535-6579, Nov. 2016.
16. Q. Shi, M. Razaviyayn, M. Hong and Z.-Q. Luo*, "SINR Constrained Beamforming for a MIMO Multi-User Downlink System: Algorithms and Convergence Analysis," in IEEE Transactions on Signal Processing, vol. 64, no. 11, pp. 2920-2933, June 2016.
17. Nan Zhang, Zhiqiang Yao, Yixian Liu, Stephen P. Boyd, Zhi-Quan Luo*, “Optimal Resource Allocation for Energy Efficient Transmission in DSL”. In proceeding of GLOBECOM 2016: 1-6.
18. Cui, Shuguang and Hero III, Alfred O. and Luo, Zhi-Quan* and Moura, José M. F. Big Data over Networks. Cambridge CB2 8BS, United Kingdom: Cambridge University Press, 2016.
19. R. Sun, M. Hong and Z.-Q. Luo*, “Joint Downlink Base Station Association and Power Control for Max-min Fairness: Computation and Complexity”, IEEE Journal on Selected Areas in Communications, Vol. 33, pp. 1040-1054, 2015.
20. R. Sun and Z.-Q. Luo*, “Interference Alignment Using Finite and Dependent Channel Ex- tensions: The Single Beam Case,” IEEE Transactions on Information Theory, Vol. 61, pp. 239-255, 2015.
21. Z. Xu, M. Hong and Z.-Q. Luo*, “Semidefinite Approximation for Mixed Binary Quadratically Constrained Quadratic Programs”, SIAM Journal on Optimization, Vol. 24, pp. 1265-1293, 2014.
22. H. Baligh, M. Hong, W.C. Liao, Z.-Q. Luo*, M. Razaviyayn, M. Sanjabi, R. Sun, “Cross- layer Provision of Future Cellular Networks: A WMMSE-based Approach,” IEEEE Signal Processing Magazine, Vol. 31, pp. 56-68, 2014.
23. W. C. Liao, M. Hong, Y.-F. Liu, Z.-Q. Luo*, “Base Station Activation and Linear Transceiver Design for Optimal Resource Management in Heterogeneous Networks,” IEEE Transactions on Signal Processing, Vol. 62, pp. 3939-3952, 2014.
24. M. Razaviyayn, M. Hong. and Z.-Q. Luo*, “Linear transceiver design for a MIMO interfering broadcast channel achieving maxCmin fairness,” Signal Processing, Vol. 93, pp. 3327-3340, 2014.
25. M. Razaviyayn, H. Baligh, A. Callard and Z.-Q. Luo*, “Joint User Grouping and Transceiver Design in a MIMO Interfering Broadcast Channel,” IEEE Transactions on Signal Processing, Vol. 62, pp. 85–94, 2014.
26. M. Sanjabi, M. Razaviyayn and Z.-Q. Luo*, “Optimal Joint Base Station Assignment and Beamforming for Heterogeneous Networks,” IEEE Transactions on Signal Processing, Vol. 62, pp. 1950-1961, 2014.
27. M. Hong, R. Sun, Z.-Q. Luo* and H. Baligh, “Joint Base Station Clustering and Beamformer Design for Partial Coordinated Transmission in Heterogeneous Networks,” IEEE Journal on Selected Areas in Communications - Special Issue on Large-Scale Multiple Antenna Wireless Systems, Vol. 31, pp. 225–240, 2013.
28. M. Hong, Z. Xu, M. Razaviyayn and Z.-Q. Luo*, “Joint User Grouping and Linear Vir- tual Beamforming: Complexity, Algorithms and Approximation Bounds,” IEEE Journal on Selected Areas in Communications Special Issue on Virtual MIMO, Vol. 30, pp. 2013–2027, 2013.
29. Q. Li, M. Hong, H. T. Wai, Y.-F. Liu, W. K. Ma and Z.-Q. Luo*, “Transmit Solutions for MIMO Wiretap Channels Using Alternating Optimization,” IEEE Journal on Selected Areas in Communications, Vol. 31 (9), pp. 1714-1727, 2013.
30. M. Razaviyayn, M. Hong. and Z.-Q. Luo*, “Linear Transceiver Design for a MIMO Inter- fering Broadcast Channel Achieving Max-Min Fairness,” Signal Processing, Vol. 93 (12), pp. 3327–3340, 2013.
31. M. Hong and Z.-Q. Luo*, “Distributed Linear Precoder Optimization and Base Station Selection for an Uplink Heterogeneous Network”, IEEE Transactions on Signal Processing, Vol. 61, pp. 3214–3228, June 2013.
32. A. Razavi, W. Zhang and Z.-Q. Luo*, “Distributed Optimization in an Energy-constrained Network: Analog Versus Digital Communication Schemes,” IEEE Transactions on Information Theory 59 (3) pp. 1803-1817, 2013.
33. H. Zhang, J. Jiang and Z.-Q. Luo*,” On the Linear Convergence of a Proximal Gradient Method for a Class of Nonsmooth Convex Minimization Problems,” Journal of Operations Research Society of China, Vol. 1, pp. 163–186, June 2013.
34. M. Razaviyayn, M. Hong. and Z.-Q. Luo*, “A Unified Convergence Analysis of Block Succes- sive Minimization Methods for Nonsmooth Optimization,” SIAM Journal on Optimization 23 (2) pp. 1126-1153, 2013.
35. M. Razaviyayn, G. Lyubeznik, and Z.-Q. Luo*, “On the Degrees of Freedom Achievable Through Interference Alignment in a MIMO Interference Channel,” IEEE Transactions on Signal Processing, Vol. 60, pp. 812–821, February 2012.
36. E. Song, Q. Shi, M. Sanjabi, R. Y. Sun and Z.-Q. Luo*, “Robust SINR-Constrained MISO Downlink Beamforming: When is Semidefinite Programming Relaxation Tight?” EURASIP Journal on Wireless Communications and Networking, August 2012.