Xiaoyu He

About me

I am currently an Associate Professor in the School of Software Engineering, Sun Yat-sen University. Previously, I was a Postdoctoral Researcher working at Nanyang Technological University and Sun Yat-sen University. I obtained my Ph.D. degree in Computer Science and Technology from Sun Yat-sen University in June 2019.

Research interests

• Intelligent optimization methods

  • Design and analysis of evolutionary algorithms

  • Real-world applications in black-box, multi-objective, and large-scale settings

• Methods for data mining and machine learning

  • Training methods based on information geometry

  • Parallel and distributed optimization methods

  • Multi-view clustering and feature selection

• Continuous methods for discrete optimization

  • Multi-agent path finding problems

  • Theoretic analysis based on Monte Carlo methods

  • Black-box policy search

Publications

• He X, Zheng Z*, Chen C, Zhou Y, Luo C, and Lin Q. Distributed Evolution Strategies for Black-Box Stochastic Optimization. IEEE Transactions on Parallel and Distributed Systems. In press.

• He X, Zheng Z*, Zhou Y, Chen C. QNG: A Quasi-Natural Gradient Method for Large-Scale Statistical Learning. SIAM Journal on Optimization. In press.

• He X, Zheng Z*, Chen Z, Zhou Y. Adaptive Evolution Strategies for Stochastic Zeroth-order Optimization. IEEE Transactions on Emerging Topics in Computational Intelligence. In press.

• Zhou Y, He X*, Chen Z, Jiang S*. Neighborhood Regression Optimization Algorithm for Computationally Expensive Optimization Problems. IEEE Transactions on Cybernetics. In press.

• Chen Z, Zhou Y*, He X, Zhang J. Learning Task Relationships in Evolutionary Multitasking for Multiobjective Continuous Optimization. IEEE Transactions on Cybernetics. In press.

• He X, Zheng Z*, Zhou Y. MMES: Mixture Model based Evolution Strategy for Large-Scale Optimization. IEEE Transactions on Evolutionary Computation, 2021, 25(2): 320–333.

• He X, Zhou Y*, Chen Z, Zhang J, Chen W. Large-Scale Evolution Strategy Based on Search Direction Adaptation. IEEE Transactions on Cybernetics, 2021, 51(3): 1651–1665.

• He X, Zhou Y*, Chen Z. An Evolution Strategy for Black-box Optimization on Matrix Manifold. Chinese Journal of Computers, 2020, 43(9). (In Chinese)

• He X, Zhou Y*, Chen Z, Jiang S. An evolutionary approach to black-box optimization on matrix manifolds. Applied Soft Computing, 2020, 97: 106773.

• He X, Zhou Y*, Chen Z, Zhang Q. Evolutionary Many-objective Optimization based on Dynamical Decomposition. IEEE Transactions on Evolutionary Computation, 2019, 23(3): 361–375.

• He X, Zhou Y*, Chen Z. Evolutionary Bilevel Optimization based on Covariance Matrix Adaptation. IEEE Transactions on Evolutionary Computation, 2019, 23(2): 258–272.

• He X, Zhou Y*, Chen Z. An Evolution Path-Based Reproduction Operator for Many-Objective Optimization. IEEE Transactions on Evolutionary Computation, 2019, 23(1): 29–43.

• He X, Zhou Y*. Enhancing the performance of differential evolution with covariance matrix self-adaptation. Applied Soft Computing, 2018, 64: 227–243.

• Zhou Y, Xiang Y*, He X*. Constrained Multi-objective Optimization: Test Problem Construction and Performance Evaluations. IEEE Transactions on Evolutionary Computation, 2021, 25(1): 172–186.

• Jiang S, He X*, Zhou Y. Many-objective evolutionary algorithm based on adaptive weighted decomposition. Applied Soft Computing, 2019, 84: 105731.

• Zhang G, Chen X, Zhou Y*, Wang C, Huang D, He X. Kernelized Multi-view Subspace Clustering via Auto-weighted Graph Learning. Applied Intelligence, 2022, 51: 716–731.

• Zhang G, Zhou Y*, Wang C, Huang D, He X. Joint representation learning for multi-view subspace clustering. Expert Systems with Applications, 2021, 166: 113913.

• Huang Z, Zhou Y*, Chen Z, He X, Lai X, Xia X. Running Time Analysis of MOEA/D on Pseudo-Boolean Functions. IEEE Transactions on Cybernetics, 2021, 51(10): 5130–5141.

• Zhang G, Zhou Y*, He X, Wang C, Huang D. One-step Kernel Multi-view Subspace Clustering. Knowledge-Based Systems, 2020, 189: 105126.

• Zhou Y*, He X, Xiang Y, Cai S. A set of new multi- and many-objective test problems for continuous optimization and a comprehensive experimental evaluation. Artificial Intelligence, 2019, 276: 105–129.

• Chen Z, Zhou Y*, He X. Handling expensive multi-objective optimization problems with a cluster-based neighborhood regression model. Applied Soft Computing, 2019, 80: 211–225.

• Chen Z, Zhou Y*, He X, Jiang S. A Restart-based Rank-1 Evolution Strategy for Reinforcement Learning. Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019, Macao, China: 2130–2136.

• Huang Z, Zhou Y*, Chen Z, He X. Running Time Analysis of MOEA/D with Crossover on Discrete Optimization Problem. Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019, Hawaii, USA.

Grants

• 2021-2023, National Natural Science Foundation of China

  • Covariance Matrix Adaptation Evolution Strategy for Large-Scale Black-Box Optimization, No. 62006252, PI

• 2021-2023, Guangdong Basic and Applied Basic Research Foundation

  • Information-Geometric Optimization for Federated Learning, No. 2021A1515011840, PI

• 2020-2021, Guangdong Basic and Applied Basic Research Foundation

  • Mixture Model based Large-Scale Evolution Strategies, No. 2019A1515111154, PI

• 2019-2021, China Postdoctoral Science Foundation

  • Evolutionary Multiobjective Optimization with Complex Decision Space, No. 2019M663234, PI

Service

Reviewer for IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, Applied Intelligence, Applied Soft Computing, and Swarm and Evolutionary Computation.

Contact

Email: hxyokokok@foxmail.com

ResearchGate: https://www.researchgate.net/profile/Xiaoyu-He-9

GitHub: https://github.com/hxyokokok