Ran Cheng (程然)

 

Name: Ran Cheng
Position: Associate Professor (Tenured)
Institution: Department of Computer Science and

Engineering, SUSTech

Research Area: Computational Intelligence, Deep Learning, Evolutionary Computation
Contact: ranchengcn@gmail.com
Google Scholar, Publons

程然博士现任南方科技大学计算机科学与工程系长聘副教授/研究员,博士生导师, 演化机器智能课题组(EMI Group)负责人;曾任英国伯明翰大学计算机科学系Research Fellow (2016-2018),德国本田欧洲研究院访问学者(2013-2016)。程然博士的研究领域为计算智能,近5年共发表论文50余篇(含JCR一区IEEE Transactions长文20篇),6篇ESI高被引论文,谷歌学术引用3500余次;将研究成果应用于混动车设计、深度学习模型优化、功能材料研发、电网故障检测等重要工程与科研领域。

程然博士担任IEEE演化计算技术委员会委员、《IEEE Transactions on Artificial Intelligence》及《IEEE Access》期刊副编辑、《Applied Soft Computing》及《Complex & Intelligent Systems》期刊编委;曾获IEEE计算智能学会杰出博士论文奖(该奖项面对全球范围内取得博士学位5年内的学者开放申请,每年全球仅1人获奖)、计算智能顶级期刊《IEEE Transactions on Evolutionary Computation》及《IEEE Computational Intelligence Magazine》杰出论文奖(当年全球分别仅1篇获奖)。

Dr. Ran Cheng is currently an Associate Professor (Tenured) with the Department of Computer Science and Engineering, Southern University of Science and Technology, China. Previously, he was a Research Fellow (2016-2018) with the School of Computer Science, University of Birmingham, U.K. He received the PhD degree in computer science from the University of Surrey, U.K His main research interest is Artificial/Computational Intelligence based learning, modeling and optimization. He serves as an Associated Editor for IEEE Transactions on Artificial Intelligence (2020-) and IEEE Access (2018-), and an Editorial Board Member for Applied Soft Computing (2018-) and Complex & Intelligent Systems (2017-). He is the recipient of the IEEE Transactions on Evolutionary Computation Outstanding Paper Award (2018), the IEEE CIS Outstanding PhD Dissertation Award (2019), the IEEE Computational Intelligence Magazine Outstanding Paper Award (2020), and the IEEE Transactions on Evolutionary Computation Outstanding Paper Award (2021).

Work Experiences

  • 2020 – present: Associate Professor (Tenured), Southern University of Science and Technology, China.
  • 2018 – 2020: Assistant Professor, Southern University of Science and Technology, China.
  • 2016 – 2018: Research Fellow, University of Birmingham, UK.
  • 2013 – 2016: Visiting Scholar, Honda Research Institute Europe, Germany.

Eduction Experiences

  • 2013 – 2016: PhD, University of Surrey, UK.
  • 2010 – 2012: Postgraduate, Zhejiang University, China.
  • 2006 – 2010: BEng, Northeastern University, China.

Academic Awards

  • 2021: IEEE Transactions on Evolutionary Computation Outstanding Paper Award, IEEE, USA.
  • 2020: IEEE Computational Intelligence Magazine Outstanding Paper Award, IEEE, USA. 
  • 2019: IEEE Computational Intelligence Society (CIS) Outstanding PhD Dissertation Award, IEEE, USA.
  • 2018: IEEE Transactions on Evolutionary Computation Outstanding Paper Award, IEEE, USA.
  • 2016: Chinese Government Award for Outstanding Self-financed Students Abroad, China.
  • 2015: Vice-Chancellor’s Award for PGR Research, University of Surrey, UK.

Research Grants

  • 2020 – 2024: Deep Learning Applied to Aerofoil Design, PI, 3,810,000 RMB, China.
  • 2020 – 2022: Evolutionary Computation Based Deep Neural Architecture Search for Microchips, PI, 1,280,000 RMB, China.
  • 2020 – 2023: Cell-Based Deep Neural Networks Architecture Search Using Evolutionary Multiobjective Optimization, PI, 230,000 RMB, National Science Foundation, China.
  • 2017 – 2022: Research and Development of Next-Generation Intelligent Logistics Platform, Co-PI, 20,000,000 RMB, Shenzhen Peacock Grant, China.
  • 2018 – 2023: Research and Development of Restructurable Brain-like Computing System, Co-PI, 20,000,000 RMB, Guangdong Innovation Grant, China.

Academic Services

   Committee Services

   Editorial Services

  • 2020  present: Associate Editor, IEEE Transactions on Artificial Intelligence.
  • 2018 present: Associate Editor, IEEE Access.
  • 2018 present: Editorial Borad Member, Applied Soft Computing.
  • 2017present: Editorial Borad Member, Complex & Intelligent Systems.

   Conference Organizers

  • EMO 2021: Organizing Chair, 2021 International Conference on Evolutionary Multi-Criterion Optimization,  Shenzhen, China.
  • IEEE MBEA (2020, 2019, 2018, 2017, 2016): Founding Chair, IEEE Symposium on Model-Based Evolutionary Algorithms.

Publications

   Journal Papers

  1. Jinjin Xu, Wenli Du, Yaochu Jin, Wangli He, and Ran Cheng. Ternary Compression for Communication-Efficient Federated Learning. IEEE Transactions on Neural Networks and Learning Systems, in Press.
  2. Haoyu Zhang, Yaochu Jin, Ran Cheng, and Kuangrong Hao. Efficient Evolutionary Search of Attention Convolutional Networks via Sampled Training and Node Inheritance. IEEE Transactions on Evolutionary Computation, in Press.
  3. Danial Yazdani, Ran Cheng*, Cheng He, and Jurgen Branke. Adaptive Control of Sub-Populations in Evolutionary Dynamic Optimization. IEEE Transactions on Cybernetics, in Press.
  4. Danial Yazdani, Nabi Omidvar, Ran Cheng*, Juergen Branke, Trung Thanh Nguyen, and Xin Yao. Benchmarking Continuous Dynamic Optimization: Survey and Generalized Test Suite. IEEE Transactions on Cybernetics, in Press.
  5. Linqiang Pan, Wenting Xu, Lianghao Li, Cheng He*, and Ran Cheng*. Adaptive Simulated Binary Crossover for Rotated Multi-Objective Optimization. Swarm and Evolutionary Computation, 60: 100759, 2021.
  6. 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, Article Number: 882020.
  7. Cheng He, Ran Cheng*, and Danial Yazdani. Adaptive Offspring Generation for Evolutionary Large-Scale Multiobjective Optimization. IEEE Transactions on Systems, Man and Cybernetics: Systems, in Press.
  8. Zhanglu Hou, Cheng He, and Ran Cheng*. Reformulating Preferences into Constraints for Evolutionary Multi- and Many-Objective Optimization. Information Sciences, 541, 1-15, 2020.
  9. 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, in Press.
  10. 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, 24(5), 868-881, 2020.
  11. 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, in Press.
  12. 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, in Press.
  13. Huangke Chen, Ran Cheng*, Witold Pedrycz, and Yaochu Jin. Solving Many-Objective Optimization Problems via Multistage Evolutionary Search. IEEE Transactions on Systems, Man and Cybernetics: Systems, in Press.
  14. Ye Tian, Xingyi Zhang*, Ran Cheng*, Cheng He, and Yaochu Jin. Guiding Evolutionary Multiobjective Optimization with Generic Front Modeling. IEEE Transactions on Cybernetics, 50 (3), 1106-1119, 2020.
  15. Huangke Chen, Ran Cheng*, Jinming Wen, Haifeng Li, and Jian WengSolving Large-Scale Many-Objective Optimization Problems by Covariance Matrix Adaptation Evolution Strategy with Scalable Small SubpopulationsInformation Sciences, 509, 457-469, 2020.
  16. Ye Tian, Ran Cheng, Xingyi Zhang, Miqing Li, and Yaochu Jin. Diversity Assessment of Multi-Objective Evolutionary Algorithms: Performance Metric and Benchmark Problems [Research Frontier]IEEE Computational Intelligence Magazine, 14 (3), 61-74, 2019.
  17. Cheng He, Lianghao Li, Ye Tian, Xingyi Zhang, Ran Cheng*, Yaochu Jin, and Xin Yao. Accelerating Large-scale Multi-objective Optimization via Problem Reformulation. IEEE Transactions on Evolutionary Computation, 23 (6), 949-961, 2019.
  18. Murillo G Carneiro, Ran Cheng, Liang Zhao, and Yaochu Jin. Particle Swarm Optimization for Network-Based Data Classification. Neural Networks, 110:243-255, 2019.
  19. Ran Cheng, MN Omidvar, AH Gandomi, B Sendhoff, S Menzel, and Xin Yao. Solving Incremental Optimization Problems via Cooperative CoevolutionIEEE Transactions on Evolutionary Computation, 23 (5), 762-775, 2018.
  20. Ran Cheng, Miqing Li, Ke Li, and Xin Yao. Evolutionary Multiobjective Optimization Based Multimodal Optimization: Fitness Landscape Approximation and Peak DetectionIEEE Transactions on Evolutionary Computation, 22 (5), 692-706, 2018.
  21. Ye Tian, Ran Cheng, Xingyi Zhang, Yansen Su, and Yaochu Jin. A Strengthened Dominance Relation Considering Convergence and Diversity for Evolutionary Many-objective Optimization. IEEE Transactions on Evolutionary Computation, 23 (2), 331-345, 2018.
  22. Ran Cheng*, Cheng He, Yaochu Jin, and Xin Yao. Model-Based Evolutionary Algorithms: A Short Survey. Complex & Intelligent Systems, 4 (4), 283-292, 2018.
  23. Xingyi Zhang, Xiutao ZhengRan Cheng*, Jianfeng Qiu, and Yaochu Jin. A competitive mechanism based multi-objective particle swarm optimizer with fast convergenceInformation Sciences, 427, 63-76, 2018.
  24. Fei Li, Ran Cheng*, Jianchang Liu, and Yaochu Jin. A Two-Stage R2 Indicator Based Evolutionary Algorithm for Many-Objective Optimization. Applied Soft Computing, 67, 245-260, 2018.
  25. Xia Zhang, Bei Ding, Ran Cheng*, Sebastian C. Dixon, and Yao Lu*Computational Intelligence‐Assisted Understanding of Nature‐Inspired Superhydrophobic BehaviorAdvanced Science, 5 (1), 1700520, 2018.
  26. Xingyi Zhang, Ye Tian, Ran Cheng*, and Yaochu Jin. A Decision Variable Clustering-Based Evolutionary Algorithm for Large-scale Many-objective OptimizationIEEE Transactions on Evolutionary Computation, 22 (1), 97-112, 2018.
  27. Shenkai Gu, Ran Cheng, and Yaochu Jin. Feature Selection for High-Dimensional Classification Using a Competitive Swarm OptimizerSoft Computing, 22 (3), 811-822, 2018
  28. Ye Tian, Ran Cheng, Xingyi Zhang, and Yaochu Jin. PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [educational forum]IEEE Computational Intelligence Magazine, 12 (4), 73-87, 2017
  29. Ran Cheng, Tobias Rodemann, Michael Fischer, Maikus Olhofer, and Yaochu Jin. Evolutionary Many-Objective Optimization of Hybrid Electric Vehicle Control: from General Optimization to Preference ArticulationIEEE Transactions on Emerging Topics in Computational Intelligence, 1 (2), 97-111, 2017.
  30. Chaoli Sun, Yaochu Jin, Ran Cheng, Jinliang Ding, and Jianchao Zeng. Surrogate-Assisted Cooperative Swarm Optimization of High-Dimensional Expensive ProblemsIEEE Transactions on Evolutionary Computation, 21 (4), 644-660, 2017.
  31. Ran Cheng, Miqing Li, Ye Tian, Xingyi Zhang, Shengxiang Yang, Y Jin, and X Yao. A Benchmark Test Suite for Evolutionary Many-Objective OptimizationComplex & Intelligent Systems3 (1), 67-81, 2017.
  32. Ye Tian, Ran Cheng, Xingyi Zhang, Fan Cheng, Yaochu Jin.  An indicator based multi-objective evolutionary algorithm with reference point adaptation for better versatilityIEEE Transactions on Evolutionary Computation, 22 (4), 609-622, 2017.
  33. Ran Cheng, Yaochu Jin, Markus Olhofer, and Bernhard Sendhoff. Test Problems for Large-Scale Multiobjective and Many-Objective OptimizationIEEE Transactions on Cybernetics, 47 (12), 4108-4121, 2017.
  34. Ran Cheng, Yaochu Jin, Markus Olhofer, Bernhard Sendhoff. A Reference Vector Guided Evolutionary Algorithm for Many-Objective OptimizationIEEE Transactions on Evolutionary Computation, 20 (5), 773-791, 2016.
  35. Ran Cheng, Yaochu Jin, Kaname Narukawa, and Bernhard Sendhoff.  A Multiobjective Evolutionary Algorithm using Gaussian Process based Inverse ModelingIEEE Transactions on Evolutionary Computation, 19 (6), 838 – 856, 2015.
  36. Ran Cheng, and Yaochu Jin. A Competitive Swarm Optimizer for Large Scale OptimizationIEEE Transactions on Cybernetics, 45 (2), 191-204, 2015.
  37. Ran Cheng, and Yaochu Jin. A Social Learning Particle Swarm Optimization Algorithm for Scalable Optimization. Information Sciences291, 43-60, 2015.
  38. Xingyi Zhang, Ye Tian, Ran Cheng, and Yaochu Jin. An Efficient Approach to Nondominated Sorting for Evolutionary Multiobjective OptimizationIEEE Transactions on Evolutionary Computation19 (2), 201-213, 2015.
  39. Shenkai Gu, Ran Cheng, and Yaochu Jin. Multi-Objective Ensemble GenerationWiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 5(5), 234-245, 2015.

   Conference Papers

  1. Cheng He and Ran Cheng*. Population Sizing of Evolutionary Large-Scale Multiobjective Optimization. International Conference Series on Evolutionary Multi-Criterion Optimization (EMO), 2021.
  2. Jianqing Lin, Cheng He, and Ran Cheng*. Dimension Dropout for Evolutionary High-Dimensional Expensive Multiobjective Optimization. International Conference Series on Evolutionary Multi-Criterion Optimization (EMO), 2021.
  3. Shengran Hu, Ran Cheng*, Cheng He, and Zhichao Lu. Multi-Objective Neural Architecture Search with Almost No Training. International Conference Series on Evolutionary Multi-Criterion Optimization (EMO), 2021.
  4. Lianghao Li, Cheng He*, Ran Cheng, and Linqiang Pan. Manifold Learning Inspired Mating Restriction for Evolutionary Constrained Multiobjective Optimization. International Conference Series on Evolutionary Multi-Criterion Optimization (EMO), 2021.
  5. Changwu Huang, Lianghao Li, Cheng He*, Ran Cheng, and Xin Yao. Operator-Adapted Evolutionary Large-Scale Multiobjective Optimization for Voltage Transformer Ratio Error Estimation. International Conference Series on Evolutionary Multi-Criterion Optimization (EMO), 2021.
  6. 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.
  7. Ye Tian, Ran Cheng, Xingyi Zhang, and Yaochu Jin. Techniques for Accelerating Multi-Objective Evolutionary Algorithms in PlatEMO. IEEE Congress on Evolutionary Computation (CEC), 2020.
  8. Yiming Chen, Tianci Pan, Cheng He, and Ran Cheng. Efficient Evolutionary Deep Neural Architecture Search (NAS) by Noisy Network Morphism Mutation. The 14th International Conference on Bio-inspired Computing: Theories and Applications (BIC-TA), 2019.
  9. Hao Tan, Cheng He*, Dexuan Tang, and Ran Cheng. Efficient Evolutionary Neural Architecture Search (NAS) by Modular Inheritable Crossover. The 14th International Conference on Bio-inspired Computing: Theories and Applications (BIC-TA), 2019.
  10. Kanzhen Wan, Cheng He, Auraham Camacho, Ke Shang, Ran Cheng, and Hisao Ishibuchi. A Hybrid Surrogate-Assisted Evolutionary Algorithm for Computationally Expensive Many-Objective OptimizationIEEE Congress on Evolutionary Computation (CEC), 2019.
  11. Cheng He, Ran Cheng, Yaochu Jin, and Xin Yao. Surrogate-Assisted Expensive Many-Objective Optimization by Model FusionIEEE Congress on Evolutionary Computation (CEC)2019.
  12. Ye Tian, Xiaoshu Xiang, Xingyi Zhang, Ran Cheng, and Yaochu Jin. Sampling Reference Points on the Pareto Fronts of Benchmark Multi-Objective Optimization Problems. 2018 IEEE Congress on Evolutionary Computation (CEC), 1-6, 2018.
  13. Murillo G. Carneiro, Thiago H. Cupertino, Ran Cheng, Yaochu Jin, and Liang Zhao. Nature-Inspired Graph Optimization for Dimensionality ReductionIEEE 29th International Conference Tools with Artificial Intelligence (ICTAI), 2017.
  14.  Liangli Zhen, Miqing Li, Ran Cheng, Dezhong Peng, and Xin Yao. Adjusting Parallel Coordinates for Investigating Multi-objective Search. Asia-Pacific Conference on Simulated Evolution and Learning, 224-235, 2017.
  15. Ran Cheng, Miqing Li, and Xin Yao. Parallel peaks: A Visualization Method for Benchmark Studies of Multimodal OptimizationIEEE Congress on Evolutionary Computation (CEC), 2017 , 263-270, 2017.
  16. Chengzhi Wang, Jinliang Ding, Ran Cheng, Changxin Liu, and Tianyou Chai. Data-Driven Surrogate-Assisted Multi-Objective Optimization of Complex Beneficiation Operational Process. World Congress of the International Federation of Automatic Control (IFAC),  2017.
  17. Ye Tian, Xingyi Zhang, Ran Cheng, and Yaochu Jin. Empirical Analysis of A Tree-Based Efficient Non-Dominated Sorting Approach for Many-Objective Optimization IEEE Symposium Series on Computational Intelligence (SSCI), 1-8, 2016.
  18. Ye Tian, Xiangyi Zhang, Ran Cheng, and Yaochu Jin. A Multi-Objective Evolutionary Algorithm Based on An Enhanced Inverted Generational Distance MetricIEEE Congress on Evolutionary Computation (CEC), 5222-5229, 2016.
  19. Murillo G. Carneiro, Liang Zhao, Ran Cheng, and Yaochu Jin. Network Structural Optimization Based on Swarm Intelligence for Highlevel ClassificationInternational Joint Conference on Neural Networks (IJCNN), 3737-3744, 2016.
  20. Ran Cheng, Markus Olhofer, and Yaochu Jin. Reference Vector Based A Posteriori Preference Articulation for Evolutionary Multiobjective OptimizationEvolutionary Computation (CEC), 2015 IEEE Congress on, 939-946, 2015.
  21. Ran Cheng, Yaochu Jin, and Kaname Narukawa. Adaptive Reference Vector Generation for Inverse Model Based Evolutionary Multiobjective Optimization with Degenerate and Disconnected Pareto FrontsEvolutionary Multi-Criterion Optimization, 2015.
  22. Ran Cheng, and Yaochu Jin. Demonstrator Selection in A Social Learning Particle Swarm OptimizerIEEE Congress on Evolutionary Computation (CEC)2014.
  23. Ran Cheng, and Yaochu Jin, Simulating Swarm Behaviuors for Optimisation by Learning from Neighbours. UK Workshop on Computational Intelligence (UKCI), Guildford, UK, 2013.
  24. Ran Cheng, Chaoli Sun, and Yaochu Jin. A Multi-Swarm Evolutionary Framework Based on A Feedback MechanismEvolutionary Computation (CEC), 2013 IEEE Congress on, 718-724, 2013.