Bai Yan Research Assistant Professor Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology (SUSTech) Email: yanb@sustech.edu.cn Address: Room 442B, South Tower, COE Building, SUSTech, Shenzhen, China

Experience

• Research Assistant Professor, Research Institute of Trustworthy Autonomous Systems, SUSTech, 2021 till now

• Postdoctoral Fellow, Department of Computer Science and Engineering, SUSTech, 2019-2021 (Directed by A/Prof. Jin Zhang and Chair Prof. Xin Yao )

• Ph.D., Optical Engineering, Beijing University of Technology, 2015-2019 (Supervisor: Prof. Zhihai Wang)

• Joint Ph.D. Student, Computational and Communication Engineering, University of Technology Sydney, Australia, 2017-2018 (Supervisor: A/Prof. Andrew J. Zhang)

Research Interests

Computational intelligence, evolutionary multi-objective optimization, reinforcement learning, and their applications to signal processing (e.g., compressive sensing, array direction finding, and reconfigurable intelligent surface-aided communications).

Papers

Evolutionary multi-objective optimization for RIS-aided MU-MISO communication systems
Li M K, Yan B, and Zhang J
Soft Computing, accepted.

Fitness landscape analysis and niching genetic algorithm for hybrid beamforming in RIS-aided communications
Yan B, Zhao Q, Zhang J, Zhang J A, and Yao X
Applied Soft Computing, 131(1): 109725, 2022.

Gridless evolutionary approach for line spectral estimation with unknown model order
Yan B, Zhao Q, Zhang J, Zhang J A, and Yao X
IEEE Transactions on Cybernetics, 2022, early access, doi: 10.1109/TCYB.2022.3179378.

Bilevel evolutionary approach for off-grid direction-of-arrival estimation
Yan B, Zhao Q, Zhang J, Zhang J A, and Yao X
Applied Soft Computing, 2021, 113: 107954.

Multi-objective sparse reconstruction with transfer learning and localized regularization
Yan B, Zhao Q, Zhang J A, and Wang Z
IEEE Access, 2020, 8: 184920-184933.

Adaptive decomposition-based evolutionary approach for multiobjective sparse reconstruction
Yan B, Zhao Q, Wang Z, and Zhang J A
Information Sciences, 2018, 462: 141-159.

A hybrid evolutionary algorithm for multiobjective sparse reconstruction
Yan B, Zhao Q, Wang Z, and Zhao X
Signal, Image and Video Processing, 2017, 11(6): 993-1000.

AutoOpt: A methodological framework of automatically designing metaheuristics for optimization problems
Zhao Q, Yan B, and Shi Y
arXiv Preprint, 2022, https://arxiv.org/abs/2204.00998.

Evolutionary robust clustering over time for temporal data
Zhao Q, Yan B, Yang J, and Shi Y
IEEE Transactions on Cybernetics, 2022, early access, doi: 10.1109/TCYB.2022.3167711.

Evolutionary dynamic multi-objective optimization via learning from historical search process
Zhao Q, Yan B, Shi Y, and Middendorf M
IEEE Transactions on Cybernetics, 2021, early access, doi: 10.1109/TCYB.2021.3059252.

Adaptive sorting-based evolutionary algorithm for many-objective optimization
Liu C, Zhao Q, Yan B, Elsayed S, Ray T, and Sarker R
IEEE Transactions on Evolutionary Computation, 2019, 23(2): 247-257.

Transfer learning-assisted multi-objective evolutionary clustering framework with decomposition for high-dimensional data
Liu C, Zhao Q, Yan B, Elsayed S, and Sarker R
Information Sciences, 2019, 505: 440-456.

A new hypervolume-based differential evolution algorithm for many-objective optimization
Liu C, Zhao Q, Yan B, and Gao Y
RAIRO-Operations Research, 2017, 51(4): 1301-1315.