This page is updated to Aug. 2025

Overview

• My full publication list can be seen here: [Google Scholar].

• Citations: 49941; H-index: 103

• Thompson-Reuters (Clarivate) highly cited researcher

Books and Special Issues:

• 1. Luo, Z.-Q, Pang, J.-S. and Ralph, D., Mathematical Programs with Equilibrium Constraints, Cambridge University Press, 400 pages, 1996.

• 2. Luo, Z.-Q. and Pang, J.-S. (Guest Editors), Error Bounds and Their Applications in Mathematical Programming, Mathematical Programming, Series B, 2000.

• 3. Chiang, M., Low, S., Luo, Z.-Q., Shroff, N. and Yu, W. (Guest Editors), Special issue of IEEE Journal of Selected Areas of Communications on ‘Nonlinear Optimization of Communication Systems’, 2006.

• 4. Luo, Z.-Q., Gastpar, M., Liu, J. and Swami, A., (Guest Editors), Special issue of IEEE Signal Processing Magazine on ‘Distributed Signal Processing for Sensor Networks’, 2006.

Recent Publications

Journal Publications:

• 1. Juntao Wang, Feng Yin, Tian Ding, Tsung-Hui Chang, Zhi-Quan Luo, Qi Yan, “ Learning to Gridize: Segment Physical World by Wireless Communication Channel,” in arXiv preprint arXiv:2507.15386, 2025.

• 2. Dmitry Rybin, Yushun Zhang, Zhi-Quan Luo, “ XX^t Can Be Faster,” in arXiv preprint arXiv:2505.09814, 2025.

• 3. Yushun Zhang, Dmitry Rybin, Zhi-Quan Luo, “ Finite horizon optimization: Framework and applications,” in arXiv preprint arXiv:2412.21068, 2024.

• 4. K. Li, Y. Li, L. Cheng and Z. -Q. Luo, “Enhancing Multi-Stream Beamforming Through CQIs for 5G NR FDD Massive MIMO Communications: A Tuning-Free Scheme,” in IEEE Transactions on Wireless Communications, vol. 23, no. 11, pp. 17508-17521, Nov. 2024.

• 5. S. Zhang, X. Ning, X. Zheng, Q. Shi, T. -H. Chang and Z. -Q. Luo, “A Physics-Based and Data-Driven Approach for Localized Statistical Channel Modeling,” in IEEE Transactions on Wireless Communications, vol. 23, no. 6, pp. 5409-5424, June 2024.

• 6. K. Li, Y. Li, L. Cheng, Q. Shi and Z. -Q. Luo, “Downlink Channel Covariance Matrix Reconstruction for FDD Massive MIMO Systems With Limited Feedback,” in IEEE Transactions on Signal Processing, vol. 72, pp. 1032-1048, 2024.

• 7. Qingqing Wu, Beixiong Zheng, Changsheng You, Lipeng Zhu, Kaiming Shen, Xiaodan Shao, Weidong Mei, Boya Di, Hongliang Zhang, Ertugrul Basar, Lingyang Song, Marco Di Renzo, Zhi-Quan Luo, Rui Zhang, “Intelligent Surfaces Empowered Wireless Network: Recent Advances and the Road to 6G,” in Proceedings of the IEEE, 2024.

• 8. X. Zhao, S. Lu, Q. Shi and Z. -Q. Luo, “Rethinking WMMSE: Can Its Complexity Scale Linearly With the Number of BS Antennas?” in IEEE Transactions on Signal Processing, vol. 71, pp. 433-446, 2023.

• 9. Y. -B. Zhao and Z. -Q. Luo, “Dynamic Orthogonal Matching Pursuit for Sparse Data Reconstruction,” in IEEE Open Journal of Signal Processing, vol. 4, pp. 242-256, 2023.

• 10. Zhao, Y., Luo, Z. Improved RIP-based bounds for guaranteed performance of two compressed sensing algorithms. Sci. China Math. 66, 1123–1140 (2023). (no PDF)

• 11. Zhi-Quan Luo, Xi Zheng, David López-Pérez, Qi Yan, Xin Chen, Nanbin Wang, Qingjiang Shi, Tsung-Hui Chang, Adrian Garcia-Rodriguez, “SRCON: A Data-Driven Network Performance Simulator for Real-World Wireless Networks,” in IEEE Communications Magazine, vol. 61, no. 6, pp. 96-102, June 2023.

• 12. W. Pu, Y. -F. Liu and Z. -Q. Luo, “Efficient Estimation of Sensor Biases for the 3-D Asynchronous Multi-Sensor System,” in IEEE Transactions on Signal Processing, vol. 71, pp. 2420-2433, 2023.

• 13. C. Chen, L. Shen, W. Liu and Z. -Q. Luo, “Efficient-Adam: Communication-Efficient Distributed Adam,” in IEEE Transactions on Signal Processing, vol. 71, pp. 3257-3266, 2023.

• 14. Y. Zhang, K. Shen, S. Ren, X. Li, X. Chen and Z. -Q. Luo, “Configuring Intelligent Reflecting Surface With Performance Guarantees: Optimal Beamforming,” in IEEE Journal of Selected Topics in Signal Processing, vol. 16, no. 5, pp. 967-979, Aug. 2022.

• 15. J. Zhang and Z. -Q. Luo, “ A global dual error bound and its application to the analysis of linearly constrained nonconvex optimization,” in SIAM Journal on Optimization, vol. 32, no. 3, pp. 2319–2346, 2022.

• 16. M. Asgarian, G. Mirjalily and Z. -Q. Luo, “Embedding Multicast Service Function Chains in NFV-Enabled Networks,” in IEEE Communications Letters, vol. 25, no. 4, pp. 1264-1268, April 2021.

• 17. Yeqing Qiu, Chengpiao Huang, Ye Xue, Zhipeng Jiang, Qingjiang Shi, Dong Zhang and Zhi-Quan Luo, “Relaxation-Free Min-k-Partition for PCI Assignment in 5G Networks,” accepted by IEEE Transactions on Signal Processing, 2025.

Conference Papers:

• 1. Ziniu Li, Tian Xu, Yushun Zhang, Zhihang Lin, Yang Yu, Ruoyu Sun, Zhi-Quan Luo, “ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models,” Forty-first International Conference on Machine Learning, 2024.

• 2. Hao Liang, Zhiquan Luo Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:1774-1782, 2024.

• 3. Yingru Li, Zhiquan Luo Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:559-567, 2024.

• 4. Yingru Li, Jiawei Xu, Zhi-Quan Luo, “Efficient and scalable reinforcement learning via Hypermodel,” NeurIPS 2023 Workshop on Adaptive Experimental Design and Active Learning in the Real World, 2023.

• 5. Jiawei Yao, Fan Xu, Wenhai Lai, Kaiming Shen, Xin Li, Xin Chen, Zhi-Quan Luo, “Blind Beamforming for Multiple Intelligent Reflecting Surfaces,” ICC 2023 - IEEE International Conference on Communications, Rome, Italy, 2023, pp. 871-876.

• 6. Tian Xu, Ziniu Li, Yang Yu, Zhi-Quan Luo, “Provably Efficient Adversarial Imitation Learning with Unknown Transitions”, Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence, PMLR 216:2367-2378, 2023 (Oral).

• 7. Hao Liang, Zhi-Quan Luo Proceedings of the 40th International Conference on Machine Learning, PMLR 202:20677-20705, 2023.

• 8. W. -K. Chen, Y. -F. Liu, R. -J. Zhang, Y. -H. Dai and Z. -Q. Luo, “An Efficient Decomposition Algorithm for Large-Scale Network Slicing,” 2023 IEEE 24th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Shanghai, China, 2023, pp. 171-175.

• 9. Fan Xu, Jiawei Yao, Wenhai Lai, Kaiming Shen, Xin Li, Xin Chen, Zhi-Quan Luo, “Blind Beamforming for Multiple-IRS Assisted Wireless Transmission,” 2023 IEEE 24th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Shanghai, China, 2023, pp. 136-140.

• 10. K. Li, W. Pu and Z. -Q. Luo, “An Exploration-Estimation Beamforming Scheme For 5GNR FDD Massive MIMO Communications,” 2023 IEEE 24th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Shanghai, China, 2023, pp. 146-150.

• 11. K. Li, Y. Li, L. Cheng, Q. Shi and Z. -Q. Luo, “Pushing The Limit of Type I Codebook For FDD Massive MIMO Beamforming: A Channel Covariance Reconstruction Approach,” ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Toronto, ON, Canada, 2021, pp. 4785-4789.

• 12. Y. Li, K. Li, L. Cheng, Q. Shi and Z. -Q. Luo, “Digital Twin-Aided Learning to Enable Robust Beamforming: Limited Feedback Meets Deep Generative Models,” 2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Lucca, Italy, 2021, pp. 26-30.

• 13. K. Li, Y. Li, L. Cheng, Q. Shi and Z. -Q. Luo, “Learning Enhanced Beamforming Vector From CQIs in 5G NR FDD Massive MIMO Systems: A Tuning-free Approach,” 2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), Lucca, Italy, 2021, pp. 21-25.

• 14. Yeqing Qiu, Ye Xue, Akang Wang, Yiheng Wang, Qingjiang Shi, Zhi-Quan Luo, “ROS: A GNN-based Relax-Optimize-and-Sample Framework for Max-$k$-Cut Problems,” Proceedings of the 42nd International Conference on Machine Learning, PMLR, 2025.