About me
I am currently a PhD candidate in Computer Science at City University of Hong Kong (CityUHK), under the supervision of Prof. Qingfu ZHANG. I received my B.Sc. and M.Sc. degrees in the School of Marine Science and Technology at Northwestern Polytechnical University (NPU), in 2017 and 2020, respectively, where I was supervised by Prof. Baowei SONG and Prof. Peng WANG. Additionally, from September 2023 to February 2024, I visited Prof. Chao QIAN’s research group at Nanjing University.
My research interests include multiobjective optimization, Bayesian optimization, and their applications in the design of underwater vehicles.
Email: liazhao5-c@my.cityu.edu.hk
News
- 2024.07: 🎉🎉 “Many-to-Few Decomposition: Linking R2-based and Decomposition-based Multiobjective Efficient Global Optimization Algorithms” has been accepted by IEEE Transactions on Evolutionary Computation.
- 2023.04: 🎉🎉 “Hypervolume-Guided Decomposition for Parallel Expensive Multiobjective Optimization” has been accepted by IEEE Transactions on Evolutionary Computation.
Selected Publications
IEEE Transactions on Evolutionary Computation
Hypervolume-Guided Decomposition for Parallel Expensive Multiobjective Optimization
[Accepted Version] [PDF] [code]
Liang Zhao and Qingfu Zhang.
IEEE Transactions on Evolutionary Computation
Many-to-Few Decomposition: Linking R2-based and Decomposition-based Multiobjective Efficient Global Optimization Algorithms
[Accepted Version] [PDF] [code]
Liang Zhao, Xiaobin Huang, Chao Qian, and Qingfu Zhang.
Educations
- 2020.09 - 2025, PhD, City University of Hong Kong (CityUHK)
- 2017.09 - 2020.06, Master, Northwestern Polytechnical University (NPU)
- 2013.09 - 2017.07, Undergraduate, Northwestern Polytechnical University (NPU)
Honors and Awards
- 2023 Outstanding Academic Performance Award for Research Degree Students, Awarded by CityUHK
- 2022 Outstanding Master’s Degree Thesis, Awarded by China Ordnance Society (COS)
- 2014, 2015, 2016, 2019 National Scholarship, Awarded by Ministry of Education of China
Publication List
Journal Papers
- Liang Zhao, Xiaobin Huang, Chao Qian, and Qingfu Zhang. "Many-to-Few Decomposition: Linking R2-based and Decomposition-based Multiobjective Efficient Global Optimization Algorithms". IEEE Transactions on Evolutionary Computation, 2024 (in press). [Accepted Version] [PDF] [Code]
- Liang Zhao and Qingfu Zhang. "Hypervolume-Guided Decomposition for Parallel Expensive Multiobjective Optimization". IEEE Transactions on Evolutionary Computation, 28(2): 432-444, 2024. [Accepted Version] [PDF] [Code]
- Liang Zhao, Peng Wang, Baowei Song, Xinjing Wang, and Huachao Dong. "An Efficient Kriging Modeling Method for High-dimensional Design Problems based on Maximal Information Coefficient". Structural and Multidisciplinary Optimization 61 (2020): 39-57. [PDF]
- Liang Zhao, Peng Wang, Chunya Sun, and Baowei Song. "Modeling and Motion Simulation for a Flying-wing Underwater Glider with a Symmetrical Airfoil". China Ocean Engineering 33 (2019): 322-332. [PDF]
- Chongbo Fu, Peng Wang, Liang Zhao, and Xinjing Wang. "A Distance Correlation-based Kriging Modeling Method for High-dimensional Problems". Knowledge-Based Systems 206 (2020): 106356. [PDF]
Conference Papers
- Liang Zhao, and Qingfu Zhang. "Exact Formulas for the Computation of Expected Tchebycheff Improvement". In Proceedings of the 2023 IEEE Congress on Evolutionary Computation (CEC'23), Chicago, IL, 2023, pp.1-8. [PDF] [Code]
- Xiaoyuan Zhang, Liang Zhao, Yingying Yu, Xi Lin, Zhenkun Wang, Han Zhao, and Qingfu Zhang. "LibMOON: A Gradient-based MultiObjective OptimizatioN Library in PyTorch". In Advances in Neural Information Processing Systems 37 (NeurIPS'24, Datasets and Benchmarks Track), Vancouver, Canada, 2024. [Preprint PDF] [Code]
- Keyao Fu, Peng Wang, Bin Sun, Liang Zhao, and Chuang Liu. "Design, Development and Testing of a New Solar-powered Bionic Underwater Glider with Multi-locomotion Modes". In OCEANS 2019-Marseille, pp. 1-7. IEEE, 2019. [PDF]
Journal Reviewers
IEEE Transactions on Evolutionary Computation, Transactions on Machine Learning Research, Swarm and Evolutionary Computation, SCIENCE CHINA Information Sciences, Memetic Computing