Pengkun Wang (王鹏焜)

    Associate Researcher (特任副研究员)

    Data Intelligence Laboratory (DILab)

    School of Software Engineering

    Suzhou Institute for Advanced Research

    University of Science and Technology of China (USTC)


    Address: A1302-2, Zhide Building, Suzhou Institute for Advanced Research, USTC, Suzhou, Jiangsu, China

    Email: pengkun@ustc.edu.cn


中国科学技术大学数据智能实验室(DILab)诚招特任副研究员及博士后

研究方向包括时空数据挖掘、开放机器学习与模型泛化、AI for Chemistry和面向先进科学仪器的谱图数据分析研究
如您对团队研究方向感兴趣，欢迎您直接与团队负责人汪炀老师联系!
同时团队面向中科大计算机学院、大数据学院、软件学院招收推免生与考研生（含软件学院特色化试点班）
详情参见实验室主页并欢迎与我联系！


招收对深度学习、AI4Science感兴趣且有较好数理基础的学生（中科大软件学院推免/考研/工程实践），可通过邮箱联系我，请附上个人简历。

News

  • [2024.04] One IJCAI paper is accepted!

  • [2024.04] One IEEE TITS paper is accepted!

  • [2024.04] One IEEE TVT paper is accepted!

  • [2024.01] One WWW 2024 paper is accepted!

  • [2024.01] One ICLR 2024 paper is accepted!

  • [2023.12] The guided project are awarded the Eaglet Fund of USTC!

  • [2023.12] Two AAAI 2024 papers are accepted!

  • [2023.12] Two ICASSP 2024 papers are accepted!

  • [2023.12] One CVM 2024 paper is accepted!

  • [2023.08] One IEEE TVT paper is accepted!

  • [2023.06] I will join School of Software Enginnering/Suzhou Institute for Advanced Research, USTC as the Associate Researcher!

  • [2023.05] Three KDD 2023 papers are accepted!

  • [2023.05] Pass Ph.D. oral defense!

  • [2023.03] One IEEE TITS paper is accepted!

  • [2023.02] One ICASSP 2023 paper is accepted!

  • [2023.01] One ICLR 2023 paper is accepted!

  • [2023.01] Two DASFAA 2023 papers are accepted!

  • [2022.12] One Acta Electronica Sinica (电子学报) paper is accepted!

  • [2022.10] One WSDM 2023 paper is accepted!

  • [2022.09] One ICDM 2022 paper is accepted!

  • [2022.05] One IEEE TKDE paper is accepted!

  • [2022.05] One IEEE TVT paper is accepted!

  • [2022.01] One Computer Science (计算机科学) paper is accepted!

  • [2021.06] One IEEE TKDE paper is accepted!

    • Biography

    I am an Associate Researcher at the School of Software Engineering/Suzhou Institute for Advanced Research, University of Science and Technology of China (USTC), and a member of the USTC-DILab. I received my Ph.D. in the School of Data Science, University of Science and Technology of China (USTC), supervised by Prof. Qi Liu and Prof. Yang Wang. Before starting my Ph.D. study, I received my Bachelor's degree from Jilin University (JLU) in 2017. I have published about 30 high-level papers on research journals and conferences, including some top level international journals and conferences, such as ICLR, KDD, AAAI, WWW, ICDM, and some IEEE Transactions, such as IEEE TKDE, IEEE TITS, and IEEE TVT. I am broadly interested in imbalanced/long-tailed learning, interpretable data augmentation, multi-objective optimization, open environment data mining, and generalized AI for science.

    Education

  • Ph.D., Data Science, University of Science and Technology of China, 2018.09 - 2023.06 (Supervisor: Associate Professor Yang Wang (汪炀) and Professor Qi Liu (刘淇))

  • B.S., Software Engineering, Jilin University, 2013.09 - 2017.07.
    •

    Research Interests

  • Open Environment Data Mining and Model Generalization
    • Non-ideal Data Distribution: Imbalanced/Long-tailed Learning and Out-of-Distribution (OOD) Generalization
    • Dynamic Data Distribution: Continual Learning
    • Sparse Data Distribution: Interpretable Data Augmentation
    • Variable Learning Objective: Multi-objective Optimization
  • Generalized AI for Science
    • City and Transportation: Spatiotemporal Data Mining
    • Chemistry: Spectral-Effect Relationship Learning
    • Semiconductor: Intelligent Electronic Design Automation
    •

    Publications

    ( *, Corresponding author  )

    Preprints

    1. Delayed Bottlenecking: Alleviating Forgetting in Pre-trained Graph Neural Networks
      Zhe Zhao, Pengkun Wang*, Xu Wang, Haibin Wen, Xiaolong Xie, Qingfu Zhang, Yang Wang*
      arXiv preprint [PDF]
    1. RayE-Sub: Countering Subgraph Degradation via Perfect Reconstruction
      Kuo Yang, Zhengyang Zhou*, Xu Wang, Pengkun Wang, Limin Li, Yang Wang*
      Submitted [PDF]
    1. Graph-Free Learning in Graph-Structured Data: A More Efficient and Accurate Spatiotemporal Learning Perspective
      Xu Wang, Pengfei Gu, Pengkun Wang, Binwu Wang, Zhengyang Zhou, Lei Bai*, Yang Wang*
      arXiv preprint [PDF]

    Journal Papers

    1. Adaptive and Interactive Multi-level Spatio-Temporal Network for Traffic Forecasting
      Yudong Zhang, Pengkun Wang, Binwu Wang, Xu Wang, Zhe Zhao, Zhengyang Zhou, Lei Bai*, Yang Wang*
      IEEE TITS 2024 (IEEE Transactions on Intelligent Transportation Systems, CCF-B/JCR-Q1/Top, IF=8.5)
    2. Condition-Guided Urban Traffic Co-Prediction with Multiple Sparse Urban Data
      Binwu Wang, Pengkun Wang*, Yudong Zhang, Xu Wang, Zhengyang Zhou, Yang Wang*
      IEEE TVT 2024 (IEEE Transactions on Vehicular Technology, JCR-Q1/Top, IF=6.8)

    3. Latent Gaussian Processes based Graph Learning for Urban Traffic Prediction
      Xu Wang, Pengkun Wang, Binwu Wang, Yudong Zhang, Zhengyang Zhou, Lei Bai, Yang Wang*
      IEEE TVT 2023 (IEEE Transactions on Vehicular Technology, JCR-Q1/Top, IF=6.8) [PDF]

    4. Knowledge Expansion and Consolidation for Continual Traffic Prediction with Expanding Graphs
      Binwu Wang, Yudong Zhang, Jiahao Shi, Pengkun Wang, Xu Wang, Lei Bai*, Yang Wang*
      IEEE TITS 2023 (IEEE Transactions on Intelligent Transportation Systems, CCF-B/JCR-Q1/Top, IF=8.5) [PDF]

    5. 基于教师-学生时空半监督网络的城市事件预测方法
      周正阳, 刘浩, 王琨, 王鹏焜, 王旭, 汪炀*
      电子学报 2022 (CCF-A 中文) [PDF]

    6. A2DJP: A Two Graph-based Component Fused Learning Framework for Urban Anomaly Distribution and Duration Joint-Prediction
      Kun Wang, Zhengyang Zhou, Xu Wang, Pengkun Wang, Qi Fang, Yang Wang*
      IEEE TKDE 2022 (IEEE Transactions on Knowledge and Data Engineering, CCF-A/JCR-Q1, IF=8.9) [PDF]

    7. Inferring Intersection Traffic Patterns with Sparse Video Surveillance Information: An ST-GAN method
      Pengkun Wang, Chaochao Zhu, Xu Wang, Zhengyang Zhou, Guang Wang, Yang Wang*
      IEEE TVT 2022 (IEEE Transactions on Vehicular Technology, JCR-Q1/Top, IF=6.8) [PDF]

    8. 基于骨架模态的多级门控图卷积动作识别网络
      干创, 吴桂兴*, 詹庆原, 王鹏焜, 彭志磊
      计算机科学 2022 (CCF-B 中文) [PDF]

    9. Joint Gated Co-attention Based Multi-modal Networks for Subregion House Price Prediction
      Pengkun Wang, Chuancai Ge, Zhengyang Zhou, Xu Wang, Yuantao Li, Yang Wang*
      IEEE TKDE 2021 (IEEE Transactions on Knowledge and Data Engineering, CCF-A/JCR-Q1, IF=8.9) [PDF]

    Conference Papers

    1. Make Bricks With A Little Straw: Large-Scale Spatio-temporal Graph Learning with Restricted GPU-Memory Capacity
      Binwu Wang, Pengkun Wang*, Zhengyang Zhou, Zhe Zhao, Wei Xu, Yang Wang*
      IJCAI 2024 (International Joint Conference on Artificial Intelligence, CCF-A)

    2. When Imbalance Meets Imbalance: Structure-driven Learning for Imbalanced Graph Classification
      Wei Xu, Pengkun Wang*, Zhe Zhao, Binwu Wang, Xu Wang, Yang Wang*
      WWW 2024 (The Web Conference, CCF-A)

    3. Kill Two Birds with One Stone: Rethinking Data Augmentation for Deep Long-tailed Learning
      Binwu Wang, Pengkun Wang*, Wei Xu, Xu Wang, Yudong Zhang, Kun Wang, Yang Wang*
      ICLR 2024 (International Conference on Learning Representations, 清华-A) [PDF]

    4. A Twist for Graph Classification: Optimizing Causal Information Flow in Graph Neural Networks
      Zhe Zhao, Pengkun Wang*, HaiBin Wen, Yudong Zhang, Zhengyang Zhou, Yang Wang*
      AAAI 2024 (AAAI Conference on Artificial Intelligence, CCF-A) [PDF]

    5. Towards Dynamic Spatial-Temporal Graph Learning: A Decoupled Perspective
      Binwu Wang, Pengkun Wang*, Yudong Zhang, Xu Wang, Zhengyang Zhou, Lei Bai, Yang Wang*
      AAAI 2024 (AAAI Conference on Artificial Intelligence, CCF-A) [PDF]

    6. Graph Networks Stand Strong: Enhancing Robustness via Stability Constraints
      Zhe Zhao, Pengkun Wang*, Haibin Wen, Yudong Zhang, Binwu Wang, Yang Wang*
      ICASSP 2024 (IEEE International Conference on Acoustics, Speech and Signal Processing, CCF-B) [PDF]

    7. Gradient Reactivation Enhanced Causal Attention for Out-Of-Distribution Generalizable Graph Classification
      Xu Wang, Pengfei Gu, Yudong Zhang, Binwu Wang, Pengkun Wang, Yang Wang*
      ICASSP 2024 (IEEE International Conference on Acoustics, Speech and Signal Processing, CCF-B) [PDF]

    8. Face Anti-spoofing with Unknown Attacks: A Comprehensive Feature Extraction and Representation Perspective
      Xu Wang, Pengkun Wang, Yudong Zhang, Binwu Wang
      CVM 2024 (International conference on Computational Visual Media, CCF-C)

    9. An Observed Value Consistent Diffusion Model for Imputing Missing Values in Multivariate Time Series
      Xu Wang, Hongbo Zhang, Pengkun Wang, Yudong Zhang, Binwu Wang, Zhengyang Zhou, Yang Wang*
      KDD 2023 (ACM SIGKDD Conference on Knowledge Discovery and Data Mining, CCF-A) [PDF]

    10. Pattern Expansion and Consolidation on Evolving Graphs for Continual Traffic Prediction
      Binwu Wang, Yudong Zhang, Xu Wang, Pengkun Wang, Zhengyang Zhou, Lei Bai, Yang Wang*
      KDD 2023 (ACM SIGKDD Conference on Knowledge Discovery and Data Mining, CCF-A) [PDF]

    11. EXTRACT and REFINE: Finding A Support Subgraph Set for Graph Representation
      Kuo Yang, Zhengyang Zhou, Wei Sun, Pengkun Wang, Xu Wang, Yang Wang*
      KDD 2023 (ACM SIGKDD Conference on Knowledge Discovery and Data Mining, CCF-A) [PDF]

    12. Pondering about Task Spatial Misalignment: Classification-Localization Equilibrated Object Detection
      Yudong Zhang, Wei Lu, Xu Wang, Pengkun Wang*, Yang Wang*
      ICASSP 2023 (IEEE International Conference on Acoustics, Speech and Signal Processing, CCF-B) [PDF]

    13. Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective
      Kun Wang, Yuxuan Liang, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, Yang Wang*
      ICLR 2023 (International Conference on Learning Representations, 清华-A) [PDF]

    14. Long-tailed Time Series Classification via Feature Space Rebalancing
      Pengkun Wang, Xu Wang, Binwu Wang, Yudong Zhang, Lei Bai*, Yang Wang*
      DASFAA 2023 (International Conference on Database Systems for Advanced Applications, CCF-B) [PDF] [SLIDE]

    15. A Knowledge-Driven Memory System for Traffic Flow Prediction
      Binwu Wang, Yudong Zhang, Pengkun Wang, Xu Wang, Lei Bai*, Yang Wang*
      DASFAA 2023 (International Conference on Database Systems for Advanced Applications, CCF-B) [PDF]

    16. A Multi-graph Fusion Based Spatiotemporal Dynamic Learning Framework
      Xu Wang, Lianliang Chen, Hongbo Zhang, Pengkun Wang, Zhengyang Zhou, Yang Wang*
      WSDM 2023 (ACM International Conference on Web Search and Data Mining, CCF-B) [PDF]

    17. Countering Modal Redundancy and Heterogeneity: A Self-Correcting Multimodal Fusion
      Pengkun Wang, Xu Wang, Binwu Wang, Yudong Zhang, Lei Bai*, Yang Wang*
      ICDM 2022 (IEEE International Conference on Data Mining, CCF-B) [PDF] [SLIDE]

    18. Data-driven Vehicular Communications in Urban Vehicular Network
      Wen Zhang, Zhengyang Zhou, Chuancai Ge, Pengkun Wang
      ICCSN 2019 (International Conference on Communication Software and Networks) [PDF]

    19. Stack ResNet For Short-term Accident Risk Prediction Leveraging Cross-domain Data
      Zhengyang Zhou, Lianliang Chen, Chaochao Zhu, Pengkun Wang
      CAC 2019 (China Automation Congress) [PDF]

    Activities

    Journal Reviewer

    • Reviewer for Scientific Reports

    • Reviewer for Journal of Advanced Transportation

    • Reviewer for IEEE Open Journal of Signal Processing

    • Reviewer for Highlights of Vehicles

    • Reviewer for Journal of Artificial Intelligence and Big Data

    Conference Committee

    • Program Committee Member for ICML 2024

    • Program Committee Member for ICLR 2024

    • Program Committee Member for NeurIPS 2023

    • Program Committee Member for KDD 2022/2023/2024

    • Program Committee Member for IJCAI 2024

    • Program Committee Member for AAAI 2023/2024

    • Program Committee Member for WWW 2024

    • Program Committee Member for ECCV 2024

    • Program Committee Member for SDM 2024

    • Program Committee Member for ECAI 2023

    • Program Committee Member for ICME 2024

    • Program Committee Member for ICASSP 2024

    • Program Committee Member for IJCNN 2023/2024

    • Program Committee Member for CSAE 2022

    Industrial Experiences

    • Algorithm Engineer, Consumer BG Team. Huawei Technologies Co., Ltd. 2019.

    • Android Development Engineer, MeMe Live Team. FunPlus. 2017.

    Teaching

  • 大数据分析, 研究生课程 (软件学院), 2024.02 - 2024.05.

  • 数据仓库与数据挖掘, 研究生课程 (软件学院), 2023.09 - 2023.12.

  • Teaching Assistant, NVIDIA GTC CHINA 2019.

  • Teaching Assistant, NVIDIA GTC CHINA 2018.

    • Awards

  • First-class Scholarship for Outstanding Students, USTC, 2020, 2021, 2022.

  • Second-class Scholarship for Outstanding Students, USTC, 2019.

  • Award of USTC-GUSU Lab Scholarship, 2021.

  • Guanghua Scholarship, USTC, 2021.

  • Individual Scholarship, JLU, 2017.

  • Third-class Scholarship for Outstanding Students, JLU, 2016.

  • Outstanding Student Cadre, JLU, 2014.

    • Research Grants

  • 2021.01 - 2024.12, the Natural Science Foundation of China (NSFC), Technical Personnel.

  • 2019.07 - 2022.06, Anhui Science Foundation for Distinguished Youth Scholars, Technical Personnel.

    • Competitions

  • Bronze, 2022 Global Chinese University Students Data Application Innovation Competition.

  • Second Place, 2022 “Innovation Huihu” Outstanding Student Innovation & Entrepreneurship Project.

  • First Place, 2021 “Innovation Huihu” Outstanding Student Innovation & Entrepreneurship Project.

  • Honorable Mention, 3/100, 2021 Suzhou National Hi-Tech District Innovation & Entrepreneurship Competition.

  • Second Place, 2021 Global USTCer Innovation & Entrepreneurship Competition - Suzhou Division.

  • First Place, 1/500, 2021 "Win in Suzhou, Win the Futures" Suzhou Youth Elite Venture Contest.

  • Silver, 96/6351, IEEE-CIS Fraud Detection, Kaggle.

  • Silver, 205/8751, Santander Customer Transaction Prediction, Kaggle.

  • Bronze, 93/1571, Google QUEST Q&A Labeling, Kaggle.

  • Bronze, 268/3614, ASHRAE - Great Energy Predictor III, Kaggle.

  • Top 0.3%, 9/2985, BEKE "Real Estate Industry Chat Q&A Matching", 2020 CCF Big Data & Computing Intelligence Contest.

  • Top 1%, 29/2543, SIEMENS "Prediction of Workpiece Quality Conformance Rate in Discrete Manufacturing", 2019 CCF Big Data & Computing Intelligence Contest.

  • Top 1%, 28/1696, Baidu "Context-Aware Multi-Modal Transportation Recommendation", KDD Cup 2019.

  • Second Place, Wireless Intelligent Propagation Model, 2019 "Huawei Cup" China Post-Graduate Mathematical Contest in Modeling.

  • Second Place, Comprehensive Assessment of Water Shortage Risk, 2016 China Undergraduate Mathematical Contest in Modeling.

    • Related Links

  • Prof. Yang Wang (USTC)

  • Prof. Qi Liu (USTC)

  • Prof. Zhen Yang (ZJU)

  • Prof. Lanzhe Guo (USTC)

  • Prof. Guang Wang (FSU)

  • Prof. Lei Bai (Shanghai AI Lab)

  • Prof. Zhengyang Zhou (USTC)

  • Prof. Xu Wang (USTC)

  • Dr. Yudong Zhang (USTC)
    • Designed By Pengkun Wang © 2024 | Data Intelligence @ USTC