Ke Chen，Doctor
Direct associate research fellow
Email：chenkezixf@zzu.edu.cn
Ke Chen received his Ph.D. degree in Engineering from the Robotics Research Center at Shandong University in June 2021. From November 2018 to November 2020, he was a joint Ph.D. student at Victoria University of Wellington in New Zealand, sponsored by the China Scholarship Council. He joined the School of Electrical Engineering at Zhengzhou University in September 2021.
He has been working in evolutionary computation, feature selection, machine learning, complex industrial system modeling, and numerical optimization. He has published more than 20 related papers in journals such as IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, Information Sciences, Knowledge-Based Systems, Expert Systems with Applications, Applied Soft Computing, Journal of Power Engineering, and Journal of Econometrics. He has applied for six invention patents, three of which have been granted. He has participated in one National Key R&D Program, one National Natural Science Foundation of China General Program, one National Natural Science Foundation of China Youth Program, one Shandong Natural Science Foundation, and one Shandong Major Agricultural Applied Technology Innovation Project. He serves as a special guest reviewer for more than 10 renowned international journals and conferences including IEEE Transactions on Evolutionary Computation, IEEE Transactions on Cybernetics, Applied Soft Computing, and Swarm and Evolutionary Computation.
Main published papers:
[1] Chen K, Xue B, Zhang M, Zhou F. An Evolutionary Multitasking-Based Feature Selection Method for High-Dimensional Classification. IEEE Transactions on Cybernetics, 2020. https://doi.org/10.1109/TCYB.2020.3042243
[2] Chen K, Xue B, Zhang M, Zhou F. Evolutionary Multitasking for Feature Selection in High-dimensional Classification via Particle Swarm Optimisation. IEEE Transactions on Evolutionary Computation. https//doi.org/10.1109/TEVC.2021.3100056
[3] Chen K, Zhou F, Yin L, et al. A Hybrid Particle Swarm Optimizer with Sine Cosine Acceleration Coefficients. Information Sciences, 2018, 422: 218-241.
[4] Chen K, Zhou F, Liu A. Chaotic Dynamic Weight Particle Swarm Optimization for Numerical Function Optimization. Knowledge-Based Systems, 2018, 139: 23-40.
[5] Chen K, Zhou F, Wang Y, et al. An Ameliorated Particle Swarm Optimizer for Solving Numerical Optimization Problems. Applied Soft Computing, 2018, 73: 482-496.
[6] Chen K, Xue B, Zhang M, Zhou F. Novel Chaotic Grouping Particle Swarm Optimization with A Dynamic Regrouping Strategy for Solving Numerical Optimization Tasks. Knowledge-Based Systems, 2020, p. 105568.
[7] Chen K, Zhou F, Yuan X. Hybrid Particle Swarm Optimization with Spiral-Shaped Mechanism for Feature Selection. Expert Systems with Applications, 2019, 128: 140-156.
[8] Niu P, Chen K*, Ma Y, et al. Model Turbine Heat Rate by Fast Learning Network with Tuning Based on Ameliorated Krill Herd Algorithm. Knowledge-Based Systems, 2017, 118: 80-92.
[9] Chen K, Zhou F, Xue B. Particle Swarm Optimization for Feature Selection with Adaptive Mechanism and New Updating Strategy. Australasian Joint Conference on Artificial Intelligence. Springer, Cham, 2018: 419-431.
[10] Chen K, Xue B, Zhang M, Zhou F. Hybridising Particle Swarm Optimisation with Differential Evolution for Feature Selection in Classification. IEEE Congress on Evolutionary Computation, 2020: 1-8.
[11] Liu M, Zhou F, Chen K, Zhao Y. Co-Attention Networks Based on Aspect and Context for Aspect-Level Sentiment Analysis. Knowledge-Based Systems, 2021, p. 106810.