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

Short Biography

Peng Yang received his B.Sc. and Ph.D. degrees in the Department of Computer Science and Technology from University of Science and Technology of China in 2012 and 2017, respectively. From 2017 to 2018, he was a Senior Engineer in Huawei and then he joined Southern University of Science and Technology (SUSTech). He is currently a tenure-track assistant professor jointly in the Department of Statistics and Data Science and the Department of Computer Science and Engineering at SUSTech. His research interests include Evolutionary Computation, Financial Time Series Analysis, and Multi-agent Simulation. He has published over 40 papers in top journals and conferences like TEVC, TCYB, JSAC, TNNLS, TKDE, TASE and NeurIPS. He has also been authorized with 13 invention patents by China, USA, and Germany. He has served as the reviewer for top-tier journals (TEVC, TNNLS, TIE) and the AC, SPC or PC of top AI conferences. He is the vice chair of IEEE CIS Evolutionary Learning Task Force, an executive member of CCF Computational Economics Committee and CCF AI Multi-agent System Committee, and a member of IEEE CIS Evolutionary Computation Technical Committee. He is an IEEE Senior Member.

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，广东省类脑智能计算重点实验室副主任，深圳证券信息公司-南方科技大学计算机系行情云联合实验室负责人。长期研究复杂系统仿真与决策相关的基础理论与应用技术，主持和参与包括国自然基金等国家级基础研究项目 6 项。已在国际顶级期刊和旗舰会议上发表学术论文 40 余篇，授权中、美、德发明专利 13 项，形成标准研究报告被“全国金融标准委员会”采纳，相关技术已多次应用于金融、航空等复杂系统领域，以横向项目等形式形成技术转化超千万元，已形成直接经济效益数千万元。全程参与研发的深证云行情SDK系统，重点解决我国证券行情服务高可用与运营成本问题，目前服务已覆盖全国主要机构和大部份投资者。获2024年深圳市科协优秀科技学术论文奖，2023年深圳人工智能奖-技术发明奖(第一完成人)，2022年中国航空学会科学技术奖-技术发明奖二等奖(第二完成人)，2022年深圳证券信息有限公司重大优秀项目奖(团队奖)，2017年中国科学院院长奖-特别奖。担任IEEE计算智能学会演化学习工作组副组长，IEEE计算智能学会演化计算技术委员会委员，中国计算机学会计算经济学组执委，中国计算机学会AI多智能体系统学组执委，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, IJCAI, IEEE CEC等旗舰期刊会议的审稿人、领域主席或高级程序委员。

Research Interests

My research interests focus on Artificial Intelligence + Securities Finance. Now I am working on building large simulation model of financial market. Related research areas are:

• Simulation-based Inference: inferring the parameters of a (generative) simulation model given the observed data
• Financial Market Data Analysis: financial market simulation and change-point detection
• Learning to Optimize: Leveraging learning methods for generalizing and amortizing the black-box optimization

招募: NICAL实验室常年统一招收博士研究生、硕士研究生，招生专业为计算机科学与技术（081200）；也开放研究助理教授、博士后、科研助理、访问学者、访问学生等职位，欢迎感兴趣的同学申请。申请时请将本人自述、成绩单、个人简历及相关能力/履历证明材料电子版同时发送至yangp@sustech.edu.cn及实验室公共邮箱recruiting@nical.ai，邮件主题及附件文件名标注为“申请人姓名+申请杨鹏老师xx职位/xxx年入学博士生/硕士生”。我们将统一评审申请材料并不定期邀请初审通过的申请人进行面试。

Grants

• xxxxx任务规划与决策，国家xxxx揭榜挂帅项目, 2025-2027, 联合揭榜单位项目负责人
• 基于多智能体协同学习的屏幕混合内容编码理论与方法, 国家自然科学基金重点项目, 2024-2028, 参与
• 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
• 基于演化计算的可信人工智能构建理论与方法, 国家自然科学基金外国资深学者研究基金团队试点项目, 2023-2025, 参与
• 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, 深圳证券交易所集团, 2022-2024, 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
• 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xxxx的演化博弈技术, xxxx领域基金, 2020-2022, 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
• 基于云原生的高性能信息服务系统的关键技术研究, 深圳证券交易所集团, 2020-2021, 主持
• 演化知识图谱技术研究, 华为公司, 2020.11-2021.10, 课题负责
• 面向xxxx的分布式演化计算关键技术, 中国xxxx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
• 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

Awards

Academic Awards

• The Selected 100 Academic Papers by Shenzhen Association for Science and Technology (深圳市科协百篇优秀科技学术论文), 2024
• The Technological Invention Award of Shenzhen AI Awards (深圳人工智能奖-技术发明奖, 第一完成人), 2023
• Second Class Prize of the Technological Invention Award of CSAA (中国航空学会科学技术奖-技术发明奖二等奖, 第二完成人), 2022
• 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
• CAS Presidential Scholarship-Special Prize (中国科学院院长奖-特别奖), 2017
• Microsoft Research Asia Nomination Award (微软亚洲学者奖-提名奖), 2015

Competition Awards

• Second Class Prize of 2023 CCF Computational Economics Quantitative Financial Analysis Competition (中国计算机学会计算经济学-博金量化模型挑战赛-二等奖), 2023. [Link]
• Third Class Prize of 2023 Alibaba Cloud Data Insights Innovation Challenge (阿里云数据洞察创新挑战赛-三等奖), 2023. [Link]
• Winning award of design of wireless AI system for requirements of online updating with limited dataset (OPPO广东移动通信有限公司 - 面向小样本条件场景自适应及在线更新需求的无线AI设计-优胜奖), 2023. [Link]
• Third Class Prize of 2023 Ant FinTech AI Challenge (中国计算机学会-阿里云天池竞赛基金趋势模拟预测三等奖), 2023. [Link]
• 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), 2022. [Link]
• Second Runner-Up of IEEE CEC 2022 Competition on Dynamic Optimization Problems Generated by Generalized Moving Peaks Benchmark (IEEE WCCI 2022年动态优化问题季军), 2022. [Link]
• 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), 2021. [Link]

Research Papers

Preprints (* indicates that I am the corresponding author).

1. Junjie Zhao, Chengxi Zhang, Min Qin, and Peng Yang*. QuantFactor REINFORCE: Mining Steady Formulaic Alpha Factors with Variance-bounded REINFORCE. Arxiv preprint arXiv:2409.05144
   
   
2. Yuanzhe Li, Yue Wu, Muyao Zhong, Shengcai Liu, and Peng Yang*. SimLOB: Learning Representations of Limited Order Book for Financial Market Simulation. Arxiv preprint arXiv:2406.19396.
   
   
3. Chenkai Wang, Junji Ren, and Peng Yang*. Alleviating Non-identifiability: a High-fidelity Calibration Objective for Financial Market Simulation with Multivariate Time Series Data. Arxiv preprint arXiv:2407.16566.
   
   
4. Muyao Zhong, Shengcai Liu, Bingdong Li, Haobo Fu, Ke Tang, and Peng Yang*. Pointer Networks Trained Better via Evolutionary Algorithms. Arxiv preprint arXiv:2405.08674.
   
   
5. Bingdong Li, Zixiang Di, Yanting Yang, Hong Qian, Peng Yang, Hao Hao, Ke Tang, and Aimin Zhou. It's Morphing Time: Unleashing the Potential of Multiple LLMs via Multi-objective Optimization. Arxiv preprint arXiv:2407.00487.
   
   
6. Yongfan Lu, Zixiang Di, Bingdong Li, Shengcai Liu, Hong Qian, Peng Yang, Ke Tang, and Aimin Zhou. Towards Geometry-Aware Pareto Set Learning for Neural Multi-Objective Combinatorial Optimization. Arxiv preprint arXiv:2405.08604.
   
   

Selected Publications (* indicates that I am the corresponding author).Full publications can be found here

1. Peng Yang, Junji Ren, Feng Wang, and Ke Tang. Towards Calibrating Financial Market Simulators with High-frequency Data.
   Complex System Modeling and Simulation, accepted, 2025.
   
   
2. Peng Yang*, Laoming Zhang, Haifeng Liu, and Guiying Li. Reducing Idleness in Financial Cloud Services via Multi-objective Evolutionary Reinforcement Learning based Load Balancer.
   SCIENCE CHINA Information Sciences, Vol.67, pp.120102, 2024.
   
   
3. 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, Vol.20, Issue 2, pp. 1156-1169, 2023.
   
   
4. 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, vol.10, issue 1, pp.297-310, 2023.
   
   
5. 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.
   
   
6. 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.
   
   
7. 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.
   
   
8. 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.
   
   
9. 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.
   
   
10. 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.
    
    

Professional Activities

• Academic Participation:

IEEE Senior Member (2022-)
IEEE CIS Evolutionary Learning Task Force Vice Chair (2023-)
IEEE CIS Shenzhen Chapter Chair of Young Professionals (2023-)
IEEE CIS Evolutionary Computation Technical Committee Memeber (2023-)
中国计算机学会计算经济学组执委 (2023-)
中国计算机学会AI多智能体系统学组执委 (2023-)
中国仿真学会智能仿真优化与调度专委首批委员 (2018-)


• Conference Chairs:

Chair of Special Session on "Evolutionary Learning and Learning to Optimize" at IEEE CEC'25.
Chair of Special Session on "Evolutionary Learning and Learning to Optimize" at IEEE WCCI'24.
Publicity Chair of 13th IFIP International Conference on Intelligent Information Processing, Shenzhen 2024.
Young Researchers Chair of 2023 IEEE CIS Shenzhen Summer School.
Chair of Special Session on "Evolutionary Optimization: Foundations and Its applications to Intelligent Data Analytics" at ICIC'18.


• Invited Talks:

"Generating Featured Tick Data and Factors with Financial Market Simulation", Shenzhen Securities Information Co., Ltd.; 11/2024.
"Challenges of Calibrating Financial Market Simulation on High-frequency Market Data", China National Computer Congress; 10/2023.
"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 Systems, Man and Cybernetics: Systems
IEEE Transactions on Neural Network and Learning Systems
IEEE Transactions on Computational Social Systems
IEEE Transactions on Industrial Electronics
IEEE Transactions on Emerging Topics in Computational Intelligence
IEEE Transactions on Learning Technologies
IEEE Transactions on Cognitive and Developmental Systems
IEEE Transactions on Artificial Intelligence
ACM Transactions on Intelligent Systems and Technology
SCIENCE CHINA Information Sciences
Machine Learning
Financial Innovation
Information Sciences
Swarm and Evolutionary Computation
Knowledge-based Systems
IEEE Computational Intelligence Magazine
Applied Soft Computing
Frontiers of Computer Science
Computers & Operations Research
Complex & Intelligent Systems
Chinese Journal of Electronics
Memetic Computing
Natural Computing
Journal of Systemics, Cybernetics, and Informatics

• Conference AC/SPC/PC Members:

  The Conference on Neural Information Processing Systems (NeurIPS'21'22'23'24'25)
  The International Conference on Learning Representations (ICLR'22'23'24'25)
  The International Conference on Machine Learning (ICML'20'24)
  The Association for the Advancement of Artificial Intelligence (AAAI'19'20'21'24'25)
  The International Joint Conferences on Artificial Intelligence (IJCAI'18'19'20'25-SPC)
  The IEEE Congress on Evolutionary Computation (IEEE CEC'19'20'24'25-AC)
  The International Conference on Simulated Evolution and Learning (SEAL'17)
  The IEEE Symposium Series on Computational Intelligence (SSCI'16'21)
  The International Conference on Evolutionary Multi-Criterion Optimization (EMO'21)
  The World Multi-Conference on Systemics, Cybernetics And Informatics (WMSCI'15'18)
  

Students

PhD Students

• 2025 - : Yanshun Ye 叶彦顺
• 2024 - : Peiguang Zhang 张沛光
• 2024 - : Zhenhua Yang 杨振华 (at Beijing AI College)
• 2023 - : Heping Fang 方和平
• 2021 - : Muyao Zhong 钟慕尧

Master Students

• 2025 - : Jimao Shi 史纪茂
• 2025 - : Shiying Hu 胡世颖
• 2025 - : Qiushi Li 李秋实
• 2024 - : Jinglin Wang 王靖林
• 2024 - : Zhixin Wang 王志新
• 2024 - : Junji Ren 任俊吉
• 2023 - : Yushi Lin 林雨诗
• 2023 - : Xiangbo Deng 邓祥波
• 2023 - : Boquan Jiang 姜博泉
• 2022 - 2024: Zhenhua Yang 杨振华 (Ph.D candidate at Beijing AI College)
• 2022 - 2024: Chenkai Wang 王晨凯 (at SUSTech)
• 2021 - 2024: Peilin Wu 吴培霖 (at Meituan)
• 2020 - 2023: Lang Fu 付浪 (at Alibaba)
• 2020 - 2023: Laomin Zhang 张烙铭 (at DiDi Global)
• 2020 - 2023: Jianqi Cao 曹建琦 (at Ningbo Bank)
• 2020 - 2023: Lan Tang 唐岚 (co-supervised with Prof. Ke Tang, at Nanshan District Publicity Department of Shenzhen Municipal Committee of the CPC)
• 2018 - 2020: Muyao Zhong 钟慕尧 (co-supervised with Prof. Ke Tang, Ph.D candidate at SUSTech)
• 2018 - 2020: Binjie Kang 康炳杰 (co-supervised with Prof. Xin Yao, at Huawei)
• 2018 - 2020: Di Hu 胡笛 (co-supervised with Prof. Xin Yao, at ByteDance)

Teaching

• STA321-Distributed Storage and Parallel Computing (for undergraduate students, 2022Fall, 2023Fall, 2024Fall)
• CS109-Introduction to Computer Programming (for undergraduate students, 2023Spring)
• CS203B-Data Structures and Algorithm Analysis B (for undergraduate students, 2024Spring, 2025Spring)
• 基于机器学习的中长跑运动表现预测与训练优化系统，广东省科技创新战略专项本科生项目, 2025-2026, 指导老师
• 行业需求牵引的大数据系统类课程改革，南方科技大学教学课程改革项目，2025-2026, 主持