About

I am a Research Associate Professor (研究副教授) with the Department of Computer Science and Engineering, Southern University of Science and Technology (SUSTech, 南方科技大学) since 2025. Prior to this, I was a Postdoctoral Fellow and then Research Assistant Professor at SUSTech from 2019 to 2024. I obtained Ph.D. degree from a joint program with Beijing University of Technology, China, and The University of New South Wales, Australia, in 2019.

Research

My research interests lie at the intersection of machine learning, operations research, and robotics. Advances in AI and robotics create new problems in industrial engineering. I develop learning- and optimization-based methods, including self-supervised learning, reinforcement learning, large pre-trained models, and heuristics, to automate the formulation and solution of these problems.

My research has been published in top-tier journals and conferences, including the Journal of Machine Learning Research (JMLR), Transactions on Machine Learning Research (TMLR), International Conference on Machine Learning (ICML), Robotics: Science and Systems (RSS), and IEEE TCYB/TPDS/TEVC/TITS/TETCI.

As a Principal Investigator, I have secured competitive research grants from the National Natural Science Foundation of China, Guangdong Basic and Applied Basic Research Foundation, Shenzhen Municipal Human Resources and Social Security Bureau, as well as industry partners.

Application

My research has been applied in visual-tactile perception, autonomous planning and decision-making for intelligent robots. The resulting technologies are being commercialized through a seven-axis dual-arm mobile manipulation robot, a visual-tactile robotic demonstration and data collection system, and a molten-pool monitoring system for robotic welding.

Student Supervision

I supervise master’s students in Computer Science and Engineering. I provide hands-on guidance in research ideation, experimental design, and manuscript preparation, helping students develop into capable researchers or technical professionals. Every student I have supervised has published work in IEEE Transactions or other JCR Q1 journals. The group provides sustained support for academic travel, industry-academia collaboration, and career development.

Selected Publications

• Fast bi-level task assignment and routing for truck-drone collaborative delivery

  He Z, Yang J*, Zhao Q, Yang H, Chen X, Zhou X, Shi Y

  IEEE Transactions on Intelligent Transportation Systems (TITS), 2026, early access, doi: 10.1109/TITS.2026.3711461.

• AutoOpt: A general framework for automatically designing metaheuristic optimization algorithms with diverse structures

  Zhao Q, Yan B, Hu T, Chen X, Yang J, Cheng S, Shi Y*

  IEEE Transactions on Emerging Topics in Computational Intelligence (TETCI), 2025, 9(5): 3690-3703.

• Automated metaheuristic algorithm design with autoregressive learning

  Zhao Q, Liu T, Yan B, Duan Q, Yang J, Shi Y*

  IEEE Transactions on Evolutionary Computation (TEVC), 2025, 29(5): 2004-2018.

• Automated design of metaheuristic algorithms: A survey

  Zhao Q, Duan Q, Yan B, Cheng S, Shi Y*

  Transactions on Machine Learning Research (TMLR), 2024. https://openreview.net/forum?id=qhtHsvF5zj (Survey Certificate Award)

• PyPop7: A pure-python library for population-based black-box optimization

  Duan Q, Zhou G, Shao C, Wang Z, Feng M, Huang Y, Tan Y, Yang Y, Zhao Q, Shi Y*

  Journal of Machine Learning Research (JMLR), 2024, 25: 1-28.

• Gridless evolutionary approach for line spectral estimation with unknown model order

  Yan B, Zhao Q, Zhang J*, Zhang J A, Yao X

  IEEE Transactions on Cybernetics (TCYB), 2024, 54(2): 935-947.

• Distributed evolution strategies with multi-level learning for large-scale black-box optimization

  Duan Q, Shao C, Zhou G, Zhang M, Zhao Q, Shi Y*

  IEEE Transactions on Parallel and Distributed Systems (TPDS), 2024, 35(11): 2087-2101.

• Evolutionary robust clustering over time for temporal data

  Zhao Q, Yan B, Yang J, Shi Y*

  IEEE Transactions on Cybernetics (TCYB), 2023, 53(7): 4334-4346.

• Evolutionary dynamic multi-objective optimization via learning from historical search process

  Zhao Q, Yan B, Shi Y*, Middendorf M

  IEEE Transactions on Cybernetics (TCYB), 2022, 52(7): 6119-6130.

• Adaptive sorting-based evolutionary algorithm for many-objective optimization

  Liu C, Zhao Q*, Yan B, Elsayed S, Ray T, Sarker R

  IEEE Transactions on Evolutionary Computation (TEVC), 2019, 23(2): 247-257.

Last update: 07/2026