I am currently a Professor at the School of Mathematical Sciences, Shenzhen University. My research focuses on large-scale optimization and optimal control problems, encompassing both the development of algorithms and complexity analysis. I have worked on sum-of-squares relaxations for polynomial optimization, inexact augmented Lagrangian methods, restarting techniques for Nesterov’s accelerated methods, randomized coordinate descent (serial, parallel, distributed, accelerated, and primal-dual variants), attenuation of the curse of dimensionality for solving Hamilton-Jacobi-Bellman equations, and nonlinear Perron-Frobenius theory.

New papers

• Zheng Qu, Defeng Sun and Jintao Xu. Progressive Bound Strengthening via Doubly Nonnegative Cutting Planes for Nonconvex Quadratic Programs, arXiv preprint arXiv:2510.02948, 2025. arXiv:2510.02948| code
• Kaja Gruntkowska, Yassine Maziane, Zheng Qu and Peter Richtárik. Drop-Muon: Update Less, Converge Faster, arXiv preprint arXiv:2510.02239, 2025. arXiv:2510.02239

Journal Publications

• Zheng Hua and Zheng Qu. Exactness and effective degree bound of Lasserre's relaxation for polynomial optimization over finite variety, Mathematics of Operations Research, 2025. DOI:10.1287/moor.2024.0483
• Jiawang Nie, Zheng Qu, Xindong Tang and Linghao Zhang. A characterization for tightness of the sparse Moment-SOS hierarchy, Mathematical Programming, 2025. DOI:10.1007/s10107-025-02223-2
• Zheng Qu, Tianyou Zeng and Yuchen Lou. Globally solving concave quadratic programs via doubly nonnegative relaxation, Mathematical Programming Computation 17, 451–503 2025. DOI:10.1007/s12532-025-00279-x
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• Zheng Qu and Xindong Tang. A correlatively sparse Lagrange multiplier expression relaxation for polynomial optimization, SIAM Journal on Optimization 34(1), 127-162, 2024. DOI:10.1137/22M1515689
• Marianne Akian, Stephane Gaubert, Zheng Qu and Omar Saadi. Multiply accelerated value iteration for non-symmetric affine fixed point problems and application to Markov decision processes, SIAM Journal on Matrix Analysis and Applications 43(1), 199-232, 2022. DOI:10.1137/20M1367192
• Fei Li, Zheng Qu. An inexact proximal augmented Lagrangian framework with arbitrary linearly convergent inner solver for composite convex optimization, Mathematical Programming Computation 13, 583-644, 2021. DOI:10.1007/s12532-021-00205-x| code
• Xun Qian, Zheng Qu and Peter Richtárik. L-SVRG and L-Katyusha with arbitrary sampling, Journal of Machine Learning Research, 22(112), 1-47, 2021.
• Olivier Fercoq, Zheng Qu. Restarting the accelerated coordinate descent method with a rough strong convexity estimate, Computational Optimization and Applications, 75:63-91, 2020. DOI:10.1007/s10589-019-00137-2
• Olivier Fercoq, Zheng Qu. Adaptive restart of accelerated gradient methods under local quadratic growth condition, IMA Journal of Numerical Analysis, 39(4):2069-2095, 2019. DOI:10.1093/imanum/drz007
• Yassamine Seladji, Zheng Qu. Polyhedron overapproximation for complexity reduction in static analysis, International Journal of Computer Mathematics: Computer Systems Theory, 2018. DOI:10.1080/23799927.2018.1535525
• Jakub Konečný, Zheng Qu and Peter Richtárik. S2CD: Semi-stochastic coordinate descent, Optimization Methods and Software, 32:993-1005, 2017. DOI:10.1080/10556788.2017.1298596
• Stephane Gaubert, Zheng Qu. Checking the strict positivity of Kraus maps is NP-hard, Information Processing Letters, 118:35-43, 2017. DOI:10.1016/j.ipl.2016.09.008
• Zheng Qu, Peter Richtárik. Coordinate descent with arbitrary sampling I: algorithms and complexity, Optimization Methods and Software, 31(5):829-857, 2016. DOI:10.1080/10556788.2016.1190360
• Zheng Qu, Peter Richtárik. Coordinate descent with arbitrary sampling II: expected separable overapproximation, Optimization Methods and Software,31(5):858-884, 2016. DOI:10.1080/10556788.2016.1190361
• Stephane Gaubert, Zheng Qu and Srinivas Sridharan. Maximizing concave piecewise affine functions on the unitary group, Optimization Letters, 10(4):655-665, 2016. DOI:10.1007/s11590-015-0951-y
• Stephane Gaubert, Zheng Qu. Dobrushin ergodicity coefficient for Markov operators on cones, Integral Equations and Operator Theory, 81(1):127-150, 2014. DOI:10.1007/s00020-014-2193-2
• Zheng Qu. Contraction of Riccati flows applied to the convergence analysis of a max-plus curse of dimensionality free method, SIAM Journal on Control and Optimization, 52(5):2677-2706, 2014. DOI:10.1137/130906702
• Stephane Gaubert, Zheng Qu. The contraction rate in Thompson metric of order-preserving flows on a cone - application to generalized Riccati equations, Journal of Differential Equations, 256(8):2902-2948, 2014. DOI:10.1016/j.jde.2014.01.024

Refereed Conference Proceeding Publications

• Marianne Akian, Stephane Gaubert, Zheng Qu and Omar Saadi. Solving ergodic Markov decision processes and perfect information Zero-sum stochastic games by variance reduced deflated value iteration, IEEE 58th Conference on Decision and Control (CDC), Nice, France, pp. 5963-5970, 2019.
• Xun Qian, Zheng Qu and Peter Richtárik. SAGA with arbitrary sampling, Proceedings of the 36th International Conference on Machine Learning (ICML), PMLR 97:5190-5199, 2019.
• Zeyuan Allen-Zhu, Zheng Qu, Peter Richtárik and Yang Yuan. Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling, Proceedings of the 33rd International Conference on Machine Learning (ICML), PMLR 48:1110-1119, 2016.
• Zheng Qu, Peter Richtárik, Martin Takáč and Olivier Fercoq. SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization, Proceedings of the 33rd International Conference on Machine Learning (ICML), PMLR 48:1823-1832, 2016.
• Dominik Csiba, Zheng Qu and Peter Richtárik. Stochastic Dual Coordinate Ascent with Adaptive Probabilities, Proceedings of the 32nd International Conference on Machine Learning (ICML), PMLR 37:674-683, 2015.
• Zheng Qu, Peter Richtárik and Tong Zhang. Randomized dual coordinate ascent with arbitrary sampling, Advances in Neural Information Processing Systems (NeurIPS) 28, pp. 865-873, 2015.
• Zheng Qu. A max-plus based randomized algorithm for solving a class of HJB PDEs, 53rd IEEE Conference on Decision and Control (CDC), Los Angeles, CA, 2014, pp. 1575-1580.
• Stephane Gaubert, Zheng Qu and Srinivas Sridharan. Bundle-based pruning in the max-plus curse of dimensionality free method, Proceedings of the 21st International Symposium on Mathematical Theory of Networks and Systems (MTNS), Groningen, 2014.
• Zheng Qu. Contraction of Riccati flows applied to the convergence analysis of the max-plus curse of dimensionality free method. Proceedings of the 12th biannual European Control Conference (ECC), pp.2226-2231, 2013.
• Stephane Gaubert, Zheng Qu. Markov operators on cones and non-commutative consensus. Proceedings of the 12th biannual European Control Conference (ECC), pp.2693-2700, 2013.
• Stephane Gaubert, William M. McEneaney and Zheng Qu. Curse of dimensionality reduction in max-plus based approximation methods: theoretical estimates and improved pruning algorithms, IEEE 50th Conference on Decision and Control and European Control Conference (CDC), pp.1054-1061, Orlando, 2011.