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Associate Professor
Huazhong University of Science and Technology (HUST)
chenghehust [at] gmail.com

Dr. Cheng He is currently an Associate Professor with the School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, China. His main research interests are Artificial/Computational Intelligence (includes evolutionary multi-objective optimization, model-based optimization, large-scale optimization, etc.) and its applications.

Publications
Journals

  1. Cheng He, Ran Cheng*, Ye Tian, Xingyi Zhang, Kay Chen Tan and Yaochu Jin, Paired Offspring Generation for Constrained Large-Scale Multiobjective Optimization, IEEE Transactions on Evolutionary Computation (TEVC), 25(3), 448-462, 2021. [matlab code].

  2. Cheng He, Ran Cheng*, and Danial Yazdani, Adaptive Offspring Generation for Evolutionary Large-Scale Multiobjective Optimization, IEEE Transactions on Systems, Man and Cybernetics: Systems (TMS), 52(2), 786-798, 2020. [matlab code / python code].

  3. Cheng He, Shihua Huang, Ran Cheng*, Kay Chen Tan, and Yaochu Jin, Evolutionary Multiobjective Optimization Driven by Generative Adversarial Networks (GANs), IEEE Transactions on Cybernetics (TCYB), 51 (6), 3129-3142, 2021. [python code / poster / PPT].

  4. Cheng He, Ran Cheng*, Chuanji Zhang, Ye Tian, Qin Chen, and Xin Yao, Evolutionary Large-Scale Multiobjective Optimization for Ratio Error Estimation of Voltage Transformers, IEEE Transactions on Evolutionary Computation (TEVC), 24(5), 868-881, 2020. [matlab code].

  5. Cheng He, Ye Tian, Handing Wang, and Yaochu Jin, A Repository of Real-World Datasets for Data-Driven Evolutionary Multiobjective Optimization, Complex & Intelligent Systems (CAIS), 6, 189-197, 2020. [python code].

  6. Cheng He, Hao Tan, Shihua Huang, Ran Cheng*, Efficient Evolutionary Neural Architecture Search by Modular Inheritable Crossover, Swarm and Evolutionary Computation (SWEVO), 64(2021), 100894, 2021.

  7. Changwu Huang, Lianghao Li, Cheng He*, Ran Cheng, and Xin Yao, Adaptive Multiobjective Evolutionary Algorithm for Large-Scale Transformer Ratio Error Estimation, Memetic Computing, 2022.

  8. Shihua Huang, Cheng He, Ran Cheng*, SoloGAN: Multi-domain Multimodal Unpaired Image-to-Image Translation via a Single Generative Adversarial Network, IEEE Transactions on Artificial Intelligence (TAI), 2022.

  9. Ye Tian, Xingyi Zhang, Cheng He, Tan Kay Chen, Yaochu Jin, Principled Design of Translation, Scale, and Rotation Invariant Variation Operators for Metaheuristics, Chinese Journal of Electronics (CJE), 2022.

  10. Shengran Hu, Ran Cheng, Cheng He, Zhichao Lu, Jing Wang, and Miao Zhang, Accelerating multi-objective neural architecture search by random-weight evaluation, Complex & Intelligent Systems (CAIS), 2021.

  11. Jing Wang, Cheng He, Runze Li, Haixin Chen, Chen Zhai, and Miao Zhang, Flow Field Prediction of Supercritical Airfoils via Variational Autoencoder based Deep Learning Framework, Physics of Fluids, 33(8): 086108, 2021.

  12. Ye Tian, Langchun Si, Xingyi Zhang*, Ran Cheng, Cheng He, Kay Chen Tan, and Yaochu Jin, Evolutionary Large-Scale Multi-Objective Optimization: A Survey, ACM Computing Surveys (ACM CSUR), 54(8), 1-34, 2022.

  13. Hao Tan, Ran Cheng*, Shihua Huang, Cheng He, Changxiao Qiu, Fan Yang, and Ping Luo, RelativeNAS: Relative Neural Architecture Search via Slow-Fast Learning, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.

  14. Shangshang Yang, Tian Ye, Cheng He, Xingyi Zhang, Tan Kay Chen, Yaochu Jin, A Gradient-Guided Evolutionary Approach to Training Deep Neural Networks, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.

  15. Lianghao Li, Cheng He*, Wenting Xu, and Linqiang Pan*, Pioneer Selection for Evolutionary Multiobjective Optimization with Discontinuous Feasible Region, Swarm and Evolutionary Computation (SWEVO), 65, 100932, 2021.

  16. Zhenshou Song, Handing Wang, Cheng He, and Yaochu Jin, A Kriging-Assisted Two-Archive Evolutionary Algorithm for Expensive Many-Objective Optimization, IEEE Transactions on Evolutionary Computation (TEVC), 25(6), 1013-1027, 2021.

  17. Jianqing Lin, Cheng He, Ran Cheng*, Adaptive Dropout for High-dimensional Expensive Multiobjective Optimization, Complex & Intelligent Systems (CAIS), 8, 271-285, 2022.

  18. Linqiang Pan, Lianghao Li, Ran Cheng, Cheng He,and Kay Chen Tan, Manifold Learning Inspired Mating Restriction for Evolutionary Multi-Objective Optimization with Complicated Pareto Sets, IEEE Transactions on Cybernetics (TCYB), 51(6), 3325-3337, 2021.

  19. Linqiang Pan, Wenting Xu, Lianghao Li, Cheng He, and Ran Cheng*, Adaptive Simulated Binary Crossover for Rotated Multi-Objective Optimization, Swarm and Evolutionary Computation (SWEVO), 60, 100759, 2021.

  20. Jing Wang, Runze Li, Cheng He, Haixin Chen, Ran Cheng, Chen Zhai, and Miao Zhang, An Inverse Design Method for Supercritical Airfoil based on Conditional Generative Models, Chinese Journal of Aeronautics (CJA), 35(3), 62-74, 2021.

  21. Ye Tian, Xingyi Zhang*, Ran Cheng*, Cheng He, and Yaochu Jin, Guiding Evolutionary Multiobjective Optimization with Generic Front Modeling, IEEE Transactions on Cybernetics (TCYB), 50(3), 1106-1119, 2020.

  22. Danial Yazdani, Ran Cheng*, Cheng He, and Jurgen Branke, Adaptive Control of Sub-Populations in Evolutionary Dynamic Optimization, IEEE Transactions on Cybernetics (TCYB), 52(7), 6476-6489, 2022.

  23. Zhanglu Hou, Cheng He and Ran Cheng*, Reformulating Preferences into Constraints for Evolutionary Multi- and Many-Objective Optimization, Information Sciences, 51(6), 541, 1-15, 2020.

  24. Yanguo Kong*, Xiangyi Kong*, Cheng He, Changsong Liu, Liting Wang, Lijuan Su, Jun Gao, Qi Guo, and Ran Cheng*, Constructing an Automatic Diagnosis and Severity-Classification Model for Acromegaly Using Facial Photographs by Deep Learning, Journal of Hematology & Oncology, 13(1): 1-4, 2020.

  25. Cheng He, Lianghao Li, Ye Tian, Xingyi Zhang, Ran Cheng, Yaochu Jin, and Xin Yao, Accelerating Large-scale Multiobjective Optimization via Problem Reformulation, IEEE Transactions on Evolutionary Computation (TEVC), 23(6), 949-961, 2019. [matlab code / poster / python code].

  26. Cheng He, Zhixiong Zhang, Jie Ye, Jinbang Xu, and Linqiang Pan*, Switching Ripple Suppressor Design of the Grid-Connected Inverters: A Perspective of Many-Objective Optimization with Constraints Handling, Swarm and Evolutionary Computation (SWEVO), 44, 293-303, 2019. [matlab code].

  27. Linqiang Pan, Lianghao Li, Cheng He, and Kay Chen Tan, A Subregion Division-Based Evolutionary Algorithm with Effective Mating Selection for Many-Objective Optimization, IEEE Transactions on Cybernetics (TCYB), 50(8), 3477-3490, 2019.

  28. Ye Tian, Cheng He, Ran Cheng, and Xingyi Zhang, A Multi-Stage Evolutionary Algorithm for Better Diversity Preservation in Multi-Objective Optimization, IEEE Transactions on Systems, Man and Cybernetics: Systems (TSMC), 51(9), 5880-5894, 2021.

  29. Linqiang Pan, Cheng He, Ye Tian, Handing Wang, Xingyi Zhang, and Yaochu Jin*, A Classification-Based Surrogate-Assisted Evolutionary Algorithm for Expensive Many-Objective Optimization, IEEE Transactions on Evolutionary Computation (TEVC), 23(1), 74-88, 2018. [matlab code / python code / PPT].

  30. Ran Cheng*, Cheng He, Yaochu Jin, and Xin Yao, Model-based evolutionary algorithms: a short survey, Complex & Intelligent Systems (CAIS), 4(4), 283-292, 2018.

  31. Wenbo Dong, Kang Zhou, Huaqing Qi, Cheng He Jun Zhang*, A Tissue P System Based Evolutionary Algorithm for Multi-Objective VRPTW, Swarm and Evolutionary Computation (SWEVO), 39, 310-322, 2018.

  32. Cheng He, Ye Tian, Yaochu Jin, Xingyi Zhang, and Linqiang Pan*, A Radial Space Division Based Evolutionary Algorithm for Many-Objective Optimization, Applied Soft Computing (ASOC), 61, 603-621, 2017. [matlab code / python code / PPT].

  33. Linqiang Pan, Cheng He, Ye Tian, Yansen Su, and Xingyi Zhang*, A Region Division Based Diversity Maintaining Approach for Many-Objective Optimization, Integrated Computer-Aided Engineering, 24(3), 279-296, 2017.

  34. Zhihua Chen, Cheng He, Ying Zheng, Xiaolong Shi, and Tao Song*, A Novel Thermodynamic Model and Temperature Control Method of Laser Soldering Systems, Mathematical Problems in Engineering, 2015, 2015.

Conferences

  1. Cheng He, Lianghao Li, Ran Cheng, and Yaochu Jin, Efficient Sampling Based Offspring Generation for Large-scale Multiobjective Optimization, 4th International Conference on Data-driven Optimization of Complex Systems, 2022.

  2. Shihua Huang, Zhichao Lu, Ran Cheng, and Cheng He, FaPN: Feature-aligned Pyramid Network for Dense Image Prediction, Proceedings of the IEEE/CVF International Conference on Computer Vision, 2021: 864-873.

  3. Lianghao Li, Cheng He*, Ran Cheng, and Linqiang Pan*, Large-Scale Multiobjective Optimization via Problem Decomposition and Reformulation, IEEE Congress on Evolutionary Computation (CEC), 23(6): 949-961, 2021.

  4. Cheng He and Ran Cheng, Population Sizing of Evolutionary Large-Scale Multiobjective Optimization, Evolutionary Multi-Criterion Optimization (EMO), 2021: 41-52.

  5. Lianghao Li, Cheng He*, Ran Cheng, and Linqiang Pan Manifold Learning Inspired Mating Restriction for Evolutionary Constrained Multiobjective Optimization, Evolutionary Multi-Criterion Optimization (EMO), 2021: 296-307.

  6. Changwu Huang, Lianghao Li, Cheng He*, Ran Cheng, and Xin Yao, Operator-Adapted Evolutionary Large-Scale Multiobjective Optimization for Voltage Transformer Ratio Error Estimation, Evolutionary Multi-Criterion Optimization (EMO), 2021: 672-683.

  7. Jianqing Lin, Cheng He, and Ran Cheng* Dimension Dropout for Evolutionary High-Dimensional Expensive Multiobjective Optimization, Evolutionary Multi-Criterion Optimization (EMO), 2021: 567-579.

  8. Shengran Hu, Ran Cheng*, Cheng He, and Zhichao Lu, Multi-objective Neural Architecture Search with Almost No Training, Evolutionary Multi-Criterion Optimization (EMO), 2021: 492-503.

  9. Cheng He, Ran Cheng*, Ye Tian, and Xingyi Zhang, Iterated Problem Reformulation for Evolutionary Large-Scale Multiobjective Optimization, IEEE Congress on Evolutionary Computation (CEC), 2020, 2020: 1-8.

  10. Cheng He, Ran Cheng*, Yaochu Jin, and Xin Yao, Surrogate-Assisted Expensive Many-Objective Optimization by Model Fusion, IEEE Congress on Evolutionary Computation (CEC), 1672-1679, 2019.

  11. Yiming Chen, Tianci Pan, Cheng He*, and Ran Cheng* Efficient Evolutionary Deep Neural Architecture Search (NAS) by Noisy Network Morphism Mutation, International Conference on Bio-Inspired Computing: Theories and Applications, 2019: 761-769.

  12. Hao Tan, Cheng He*, Dexuan Tang, and Ran Cheng*, Efficient Evolutionary Neural Architecture Search (NAS) by Modular Inheritable Crossover, Evolutionary Multi-Criterion Optimization (EMO), 2019: 497-508.

  13. Kanzhen Wan, Cheng He, Auraham Camacho, Ke Shang, Ran Cheng, and Hisao Ishibuchi*, A Hybrid Surrogate-Assisted Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization, IEEE Congress on Evolutionary Computation (CEC), 2018-2025, 2019.

  14. Cheng He, Linqiang Pan*, Hang Xu, Ye Tian, and Xingyi Zhang, An Improved Reference Point Sampling Method on Pareto Optimal Front, IEEE Congress on Evolutionary Computation (CEC), 5230-5237, 2016.

© Copyright 2021, Cheng He, Southern University of Science and Technology.