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Peng Yang (杨 鹏)助理教授,博导
Assistant Professor, Ph.D Supervisor
Department of Statistics and Data Science
Department of Computer Science and Engineering
Southern University of Science and Technology
Office: Room 316, Business School
Address: 1088 Xueyuan Avenue, Shenzhen 518055, P.R. China
Email: yangp@sustech.edu.cn |

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Short Biography
个人简介
杨鹏博士,分别在2012年和2017年于中国科学技术大学计算机学院获得学士和博士学位。曾任华为云高级工程师,现任南方科技大学统计与数据科学系和计算机科学与工程系双聘助理教授、博导。长期研究面向复杂系统的决策智能基础理论与关键应用技术。已在国际顶级期刊和旗舰会议上发表学术论文30余篇,授权国家发明专利7项,获2017年中国科学院院长奖-特别奖,2018年中国人工智能学会优博提名奖。近五年承担国省市军企各类项目10余项,相关技术成果已成功在航空和金融等复杂系统场景下应用。提出多机协同可信智能运行技术,获2022年中国航空学会技术发明二等奖(第二完成人)。受资助主持创立了深圳证券信息有限公司-南方科技大学计算机系行情云联合创新实验室,受邀全程协助深圳证券交易所建设全国性行业基础设施--深证云行情系统,研发了多项专利技术并被实际应用,支撑实现了我国首例双云双活行业关键系统(受到《中国日报》《经济日报》《证券时报》《中国证券报》等媒体的广泛报导,获深证信重大优秀项目奖),获证监会批复参与制定行情服务上云的证券行业标准1项。当选IEEE senior member,担任中国计算机学会计算经济学组执委、中国仿真学会智能仿真优化与调度专委会首批委员,以及IEEE TEVC, NeurIPS, ICML, ICLR等顶级期刊会议的审稿人或程序委员。
Research Interests
My research interests focus on Artificial Intelligence + Securities Finance. Now I am working on
- Evolutionary Computation, e.g., Large-scale Global Optimization, and Cooperative Co-evolution
- Multi-agent Systems, e.g., Evolutionary Reinforcement Learning, and Human-AI Coordination
- Financial Simulation Intelligence, e.g., Limited Order Book synthesis, Abnormal Trading Behavior Detection, and Quantitative Trading
Openings: We are looking for self-motivated Master students, Ph.D. students, and Postdocs, working in the above research directions. If you are interested, please feel free to contact me via emails.
Office Hours: 16:00-18:00 every Wednesday, appointments needed.
Grants
- 可泛化的高速演化神经求解器关键技术研究, 国家自然科学基金面上项目, 2023-2026, 主持
- 证券金融市场可信关系网络建模, 国家自然科学基金外国资深学者研究基金团队试点项目课题, 2023-2025, 课题负责
- 大规模分布式演化算法及其在云计算资源管理中的应用, 国家自然科学基金青年项目, 2019-2021, 主持
- 面向xxxx的演化博弈技术, 国防xxxx技术领域基金, 2020-2022, 课题负责
- 基于云技术的行情SDK服务标准研究, 证监会标准委员会, 2022-2023, 课题负责
- 面向开放博弈场景的演化强化学习, 深圳市科创委稳定支持面上项目, 2020-2022, 主持
- 深圳证券信息有限公司-南方科技大学计算机系行情云联合创新实验室, 深交所集团, 2022-2024, 主持
- 基于云原生的高性能信息服务系统的关键技术研究, 深交所集团, 2020-2021, 主持
- 基于演化强化学习的Game AI策略多样性研究, 中国计算机学会-腾讯犀牛鸟基金项目, 2022-2023, 主持
- 面向xxxx的分布式演化计算关键技术, 中国航天科工集团, 2020-2022, 主持
- 手机端侧xx技术研究项目, OPPO公司, 2019.12-2020.6, 主持
- 演化知识图谱技术研究, 华为公司, 2020.11-2021.10, 课题负责
Awards
- Second Class Prize of the Technological Invention Award of CSAA (中国航空学会技术发明二等奖, 第二完成人), 2022
- Champion of 2022 Global AI Innovation Contest (中国人工智能学会-杭州全球人工智能技术创新大赛赛道冠军, 指导教师), 2022
- Shenzhen Pengcheng Peacock Programs Specially Appointed Positions (深圳市鹏城孔雀计划特聘岗位), 2022
- Runner-up of 2021 Global MAX Performance Cloud Computing Innovation Competition (中国信通院-全球高性能云计算创新大赛赛道亚军, 指导教师), 2021
- Major Programs Award of Shenzhen Securities Information Co., Ltd. (深圳证券信息有限公司重大优秀项目奖), 2021
- Nomination Award of Outstanding Doctoral Dissertation Award of CAAI (中国人工智能学会优博入围), 2018
- CAS Presidential Scholarship-Special Prize (中国科学院院长奖-特别奖), 2017
- Outstanding Ph.D Award of University of Science and Technology of China (中国科学技术大学优秀博士), 2017
- Outstanding Ph.D Award of Anhui Province (安徽省优秀博士), 2017
- Nomination Award of MSRA Fellowship (微软亚洲学者奖提名奖), 2015
Publications
Journal Article (* indicates that I am corresponding author)
- Shuai Wang, Aimin Zhou, Bingdong Li, Peng Yang. Differential evolution guided by approximated Pareto set for multiobjective optimization.
Information Sciences, 630, pp.669–687, 2023.
- 许瑞, 妥亚方, 杨鹏*. 分类存储下的自动化立体仓库出入库任务调度与货位分配集成优化.
工业工程与管理, in press, 2023.
- Wenjing Hong, Guiying Li, Shengcai Liu, Peng Yang, and Ke Tang. Multi-Objective Evolutionary Optimization for Hardware-Aware Neural Network Pruning.
Fundamental Research, in press, 2022, doi:10.1016/j.fmre.2022.07.013.
- Guiying Li, Peng Yang, Richang Hong, and Ke Tang. Stage-wise Magnitude-based Pruning for Recurrent Neural Networks.
IEEE Transactions on Neural Networks and Learning Systems, 2022, doi:10.1109/TNNLS.2022.3184730.
- Wenjie Chen, Wenjing Hong, Hu Zhang, Peng Yang*, and Ke Tang. Multi-fidelity Simulation Modeling for Discrete Event Simulation: An Optimization Perspective.
IEEE Transactions on Automation Science and Engineering, 2022, doi: 10.1109/TASE.2022.3173296.
- Jinghui Zhong, Tiantian Cheng, Wei-Li Liu, Peng Yang*, Ying Lin, and Jun Zhang. An Evolutionary Guardrail Layout Design Framework for Crowd Control in Subway Station.
IEEE Transactions on Computational Social Systems, 2022, doi:10.1109/TCSS.2022.3140310.
- Shengcai Liu, Peng Yang, and Ke Tang. Approximately Optimal Construction of Parallel Algorithm Portfolios by Evolutionary Intelligence (in Chinese 近似最优并行算法组智能汇聚构造).
SCIENTIA SINICA Technologica (中国科学:技术科学), 2022, 52, doi:10.1360/SST-2021-0372.
- Wenxing Lan, Ziyuan Ye, Peijun Ruan, Jialin Liu, Peng Yang, and Xin Yao. Region-focused Memetic Algorithms with Smart Initialisation for Real-world Large-scaleWaste Collection Problems.
IEEE Transactions on Evolutionary Computation, Vol.26, Issue 4, pp. 704-718, 2022.
- Peng Yang, Hu Zhang, Yanglong Yu, Mingjia Li, and Ke Tang. Evolutionary Reinforcement Learning via Cooperative Coevolutionary Negatively Correlated Search.
Swarm and Evolutionary Computation. Vol.68, 100974, 2021.
- Ke Tang, Shengcai Liu, Peng Yang, and Xin Yao. Few-shots Parallel Algorithm Portfolio Construction via Co-evolution.
IEEE Transactions on Evolutionary Computation. Vol. 25, Issue. 3, pp. 595-607, 2021.
- Peng Yang, Qi Yang, Ke Tang, and Xin Yao. Parallel Exploration via Negatively Correlated Search.
Frontiers of Computer Science. Vol.15, Issue 5, pp.155333, 2021.
- Wenjing Hong, Peng Yang, and Ke Tang. Evolutionary Computation for Large-Scale Multi-Objective Optimization: A Decade of Progresses.
International Journal of Automation and Computing. 18, 155-169, 2021.
- Minshi Chen, Jianxun Chen, Peng Yang, Shengcai Liu, and Ke Tang. A heuristic repair method for dial-a-ride problem in intracity logistic based on neighborhood shrinking.
Multimedia Tools and Applications, 2020, DOI: 10.1007/s11042-020-08894-7.
- Dongbin Jiao, Peng Yang, Liqun Fu, Liangjun Ke, and Ke Tang. Optimal Energy-Delay Scheduling for Energy Harvesting WSNs with Interference Channel via Negatively Correlated Search.
IEEE Internet of Things Journal, Vol. 7, Issue 3, pp. 1690-1703, 2020.
- Peng Yang, Ke Tang and Xin Yao. A Parallel Divide-and-Conquer based Evolutionary Algorithm for Large-scale Optimization.
IEEE Access, vol. 7, pp. 163105-163118, 2019.
- Peng Yang, Ke Tang and Xin Yao. Turning High-dimensional Optimization into Computationally Expensive Optimization.
IEEE Transactions on Evolutionary Computation, Vol. 22, Issue 1, pp. 143-156, 2018.
- Jinhong Zhong, Peng Yang, Ke Tang. A Quality-Sensitive Method for Learning from Crowds.
IEEE Transactions on Knowledge and Data Engineering, Vol. 29, Issue 12, pp. 2643-2654, 2017.
- Ke Tang, Peng Yang* and Xin Yao. Negatively Correlated Search.
IEEE Journal on Selected Areas in Communications, Vol. 34, Issue 3, pp. 1-9, March 2016.
- Peng Yang, Ke Tang and Xiaofen Lu. Improving Estimation of Distribution Algorithm on Multi-modal Problems by Detecting Promising Areas.
IEEE Transactions on Cybernetics, Vol. 45, Issue 8, pp. 1438-1449, 2015.
- Peng Yang, Ke Tang, Jose A. Lozano and Xianbin Cao. Path Planning for Single Unmanned Aerial Vehicle by Separately Evolving Waypoints.
IEEE Transactions on Robotics, Vol. 31, Issue 5, pp. 1130-1146, 2015.
Conference Paper (* indicates that I am corresponding author)
- Peng Yang, Lang Fu, Jian Zhang, and Guiying Li. OCET: One-dimensional Convolution Embedding Transformer for Stock Trend Prediction.
In: Proceedings of the 17th International Conference on Bio-inspired Computing: Theories and Applications (BIC-TA 2022), 2022, in press.
- Jianqi Cao, Guiying Li, and Peng Yang. Reinforcement Learning Based Vertical Scaling for Hybrid Deployment in Cloud Computing.
In: Proceedings of the 17th International Conference on Bio-inspired Computing: Theories and Applications (BIC-TA 2022), 2022, in press.
- Lan Tang, Xiaxi Li, Jinyuan Zhang, Guiying Li, and Peng Yang*. Enabling surrogate-assisted evolutionary reinforcement learning via policy embedding.
In: Proceedings of the 17th International Conference on Bio-inspired Computing: Theories and Applications (BIC-TA 2022), 2022, in press.
- Haoquan Li, Laoming Zhang, Daoan Zhang, Lang Fu, Peng Yang and Jianguo Zhang. TransVLAD: Focusing on Locally Aggregated Descriptors for Few-Shot Learning.
In: Proceedings of 2022 European Conference on Computer Vision (ECCV 2022), vol 13680, pp. 524-540, 2022.
- Zhibin Miao, Jinghui Zhong, and Peng Yang. Implicit Neural Network for Implicit Data Regression Problems.
In: Proceedings of the 28th International Conference on Neural Information Processing (ICONIP 2021) , pp.187-195, Sanur, Bali, Indonesia; 12/2021.
- Qi Yang, Peng Yang, and Ke Tang. Parallel Random Embedding with Negatively Correlated Search.
In: Proceedings of the 12th International Conference on Swarm Intelligence (ICSI 2021), pp.339-351, Qingdao, China; 7/2021.
- Wenjing Hong, Peng Yang, Yiwen Wang and Ke Tang. Multi-objective Magnitude-Based Pruning for Latency-Aware Deep Neural Network Compression.
In: Proceedings of the 2020 Conference of Parallel Problem Solving from Nature (PPSN 2020), pp.623-635, Leiden, The Netherlands, 09/2020.
- Yunwen Lei, Peng Yang, Ke Tang, and Ding-Xuan Zhou. Optimal Stochastic and Online Learning with Individual Iterates.
In: Proceedings of Conference and Workshop on Neural Information Processing Systems (NeurIPS 2019), pp.141-151, Vancouver, Canada; 12/2019.
- Er Zhuo, Yunjie Deng, Zhewei Su, Peng Yang, Bo Yuan, and Xin Yao. An Experimental Study of Large-scale Capacitated Vehicle Routing Problems.
In: Proceedings of the 2019 IEEE Congress on Evolutionary Computation (IEEE CEC 2019), pp.1195-1202, Wellington, New Zealand; 06/2019.
- Dongbing Jiao, Peng Yang, Liqun Fu, Liangjun Ke, and Ke Tang. Optimal Energy-Delay Scheduling for Energy Harvesting WSNs via Negatively Correlated Search.
In: Proceedings of the 2019 International Conference on Communications (ICC 2019), pp.1-7, Shanghai, China; 07/2019.
- Dongjun Qian, Peng Yang*, and Ke Tang. A Fast Heuristic Path Computation Algorithm for Batch Bandwidth Constrained Routing Problem in SDN.
In: Proceedings of the 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI 2018), pp. 490-502, Nanjing, China; 08/2018, Springer.
- Peng Yang, Guanzhou Lu, Ke Tang and Xin Yao. A Multi-Modal Optimization Approach to Single Path Planning for Unmanned Aerial Vehicle.
In: Proceedings of the 2016 IEEE Congress on Evolutionary Computation (CEC 2016), pp.1735-1742, Vancouver, Canada; 07/2016, IEEE.
- Peng Yang, Ke Tang, Lingxi Li and Kai Qin. Evolutionary Robust Optimization with Multiple Solutions.
In: Proceedings of The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES 2015), Nov., 2015, Singapore; pp.611-625, Springer.
- Wenjing Hong, Guanzhou Lu, Peng Yang, Yong Wang and Ke Tang. A New Evolutionary Multiobjective Algorithm for Convex Hull Maximization.
In: Proceedings of the 2015 IEEE Congress on Evolutionary Computation (CEC 2015), pp.931-938, Sendai, Japan; 05/2015, IEEE.
- Peng Yang, Ke Tang and Jose A. Lozano. Estimation of Distribution Algorithms based Unmanned Aerial Vehicle Path Planner Using a New Coordinate System.
In: Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC 2014), pp.1469-1476, Beijing, China; 07/2014, IEEE.
Professional Activities
- Academic Participation:
IEEE Senior Member (2022-)
中国计算机学会计算经济学组执委 (2023-)
中国仿真学会智能仿真优化与调度专委首批委员 (2018-)
- Special Session Chairs:
Co-chair of Special Session on "Evolutionary Optimization: Foundations and Its applications to Intelligent Data Analytics" at ICIC'18. (Together with Ke Tang)
- Invited Talks:
"Parallel Exploration based Evolutionary Reinforcement Learning", IEEE CIS Guangzhou Chapter; 12/2022.
"Parallel Exploration based Evolutionary Reinforcement Learning", the 3rd International Conference on Frontiers of Statistics and Data Science; 12/2022.
"Large-scale Distributed Evolutionary Computational Engine", Huawei Technologies CO., LTD., Shenzhen, China; 09/2019.
"Large-scale Distributed Evolutionary Computation", the 6th Chinese Workshop on Evolutionary Computation and Learning (ECOLE'2019), Xiangtan, China; 05/2019.
"Turning High-dimensional Optimization into Computationally Expensive Optimization", the 15th Pacific Rim International Conference on Artificial Intelligence (PRICAI'2018), Nanjing, China; 08/2018.
- Journal Reviewers:
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Industrial Electronics
IEEE Transactions on Emerging Topics in Computational Intelligence
IEEE Transactions on Cognitive and Developmental Systems
ACM Transactions on Intelligent Sstems and Technology
Machine Learning
Information Sciences
Swarm and Evolutionary Computation
IEEE Computational Intelligence Magazine
Applied Soft Computing
Frontiers of Computer Science
Computers & Operations Research
Complex & Intelligent Systems
Memetic Computing
Natural Computing
SCIENCE CHINA Information Sciences
Journal of Systemics, Cybernetics, and Informatics
- Conference PC Members:
The Conference on Neural Information Processing Systems (NeurIPS'21, NeurIPS'22)
The International Conference on Learning Representations (ICLR'22, ICLR'23)
The International Conference on Machine Learning (ICML'20)
The Association for the Advancement of Artificial Intelligence (AAAI'19, AAAI'20, AAAI'21)
The International Joint Conferences on Artificial Intelligence (IJCAI’18, IJCAI'19, IJCAI'20)
The IEEE Congress on Evolutionary Computation (IEEE CEC'19, CEC'20)
The International Conference on Simulated Evolution and Learning (SEAL'17)
The IEEE Symposium Series on Computational Intelligence (SSCI’16, SSCI'21)
The International Conference on Evolutionary Multi-Criterion Optimization (EMO’21)
The World Multi-Conference on Systemics, Cybernetics And Informatics (WMSCI’15, WMSCI'18)
Students
PhD Students
- 2023 - : Heping Fang 方和平
- 2021 - : Muyao Zhong 钟慕尧
Master Students
- 2023 - : Yushi Lin 林雨诗
- 2023 - : Xiangbo Deng 邓祥波
- 2022 - : Zhenhua Yang 杨振华
- 2022 - : Chenkai Wang 王晨凯
- 2021 - : Peilin Wu 吴培霖
- 2020 - : Lang Fu 付浪 (Champion of 2022 Global AI Innovation Contest; Runner-up of 2021 Global MAX Performance Cloud Computing Innovation Competition)
- 2020 - : Laomin Zhang 张烙铭 (Champion of 2022 Global AI Innovation Contest; Runner-up of 2021 Global MAX Performance Cloud Computing Innovation Competition)
- 2020 - : Jianqi Cao 曹建琦
- 2020 - : Lan Tang 唐岚
- 2018 - 2020: Muyao Zhong 钟慕尧 (now pursuing Ph.D degree at SUSTech)
- 2018 - 2020: Binjie Kang 康炳杰 (now working at Huawei)
- 2018 - 2020: Di Hu 胡笛 (now working at ByteDance)
Undergraduate Students
- 2021 - 2025: Gengshang Dong 董更上
- 2021 - 2025: Yibo Li 李艺博
- 2021 - 2025: Wen Pan 潘闻
- 2021 - 2025: Youxin Zhu 朱佑鑫
- 2021 - 2025: Pinzhao Li 李品昭
- 2021 - 2025: Weishuo Zhang 张未硕
- 2021 - 2025: Yuhang Deng 邓宇航
- 2020 - 2024: Teng Pan 潘腾
- 2020 - 2024: Yilai Chen 陈驿来
- 2020 - 2024: Keyun Yang 杨可芸
- 2020 - 2024: Mohan Yang 杨默涵
- 2020 - 2024: Qian Tang 唐骞
- 2020 - 2024: Junji Ren 任俊吉
- 2020 - 2024: Zhixin Wang 王志新
- 2020 - 2024: Yitao Sun 孙祎涛
- 2018 - 2022: Xiangru He 何相汝 (now pursing Master degree at University of Southampton)
- 2018 - 2022: Gengxian Wu 吴耿贤 (now working at Huawei)
- 2018 - 2022: Hailong Kou 寇海龙 (now working at Tencent)
- 2016 - 2020: Er Zhuo 卓尔 (Excellent Graduate Student of DCSE of SUSTech, received Master degree from University of California San Diego, now working at Bloomberg)
- 2016 - 2020: Yunjie Deng 邓韵杰 (Excellent Graduate Student of DCSE of SUSTech, pursing Master degree at SUSTech)
- 2016 - 2020: Zhewei Su 苏哲威 (pursing Master degree at Rice University)
Teaching
- Distributed Storage and Parallel Computing (for undergraduate students, Fall, 2022)