王鹏焜

时间:2023-12-12


个人简介:

王鹏焜,中国科大软件学院特任副研究员,硕士生导师。2017年本科毕业于吉林大学软件学院,2023年博士毕业于中国科学技术大学大数据学院。主要研究方向为泛化深度学习、时空数据挖掘等,致力于提升深度学习模型的泛化性与鲁棒性,并应用于交叉学科(城市科学、化学材料)等开放场景,推动深度学习模型快速落地。近年来作为核心技术骨干参与了包括国家自然科学基金国家重大科研仪器研制项、中国科学院稳定支持基础研究领域青年团队计划等在内的多个项目。近五年来在包括人工智能领域的顶级国际学术会议/期刊IEEE TKDEIEEE TVTAAAI 等在内的高水平国际会议和期刊上发表论文20余篇,其中以第一/通讯作者身份发表8篇。多次担任NeurIPSICLRKDDAAAIWWW等在内的CCF-A类会议审稿人。


电子邮箱:

pengkun@ustc.edu.cn


联系地址:

江苏省苏州市工业园区若水路99号至德楼A1302-2


个人主页:

http://home.ustc.edu.cn/~pengkun/


主要研究方向

泛化深度学习理论(长尾学习、分布外泛化等)

开放环境下时空数据挖掘

面向交叉学科的泛化深度学习


主要学术论文及著作

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

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

  3. Zhe Zhao, Pengkun Wang*, Haibin Wen, Yudong Zhang, Binwu Wang, Yang Wang*, Graph Networks Stand Strong: Enhancing Robustness via Stability Constraints, IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023. (CCF-B)

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

  5. Xu Wang, Pengkun Wang, Binwu Wang, Yudong Zhang, Zhengyang Zhou, Lei Bai, Yang Wang*, Latent Gaussian Processes based Graph Learning for Urban Traffic Prediction, IEEE Transactions on Vehicular Technology (IEEE TVT), 2023. (SCI 2, TOP, IF=6.8)

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

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

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

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

  10. Kun Wang, Yuxuan Liang*, Pengkun Wang, Xu Wang, Pengfei Gu, Junfeng Fang, Yang Wang*, Searching Lottery Tickets in Graph Neural Networks: A Dual Perspective, International Conference on Learning Representations (ICLR), 2023. (机器学习领域顶级会议)

  11. Binwu Wang, Yudong Zhang, Jiahao Shi, Pengkun Wang, Xu Wang, Lei Bai*, Yang Wang*, Knowledge Expansion and Consolidation for Continual Traffic Prediction with Expanding Graphs, IEEE Transactions on Intelligent Transportation Systems (IEEE TITS), 2023. (CCF-B, SCI 1, TOP, IF=8.5)

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

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

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

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

  16. Pengkun Wang, Chaochao Zhu, Xu Wang, Zhengyang Zhou, Guang Wang, Yang Wang*, Inferring Intersection Traffic Patterns with Sparse Video Surveillance Information: An ST-GAN Method, IEEE Transactions on Vehicular Technology (IEEE TVT), 2022. (SCI 2, TOP, IF=6.8)

  17. Kun Wang, Zhengyang Zhou, Xu Wang, Pengkun Wang, Qi Fang, Yang Wang*, A2DJP: A Two Graph-based Component Fused Learning Framework for Urban Anomaly Distribution and Duration Joint-Prediction, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2022. (CCF-A, SCI 2 , IF=8.9)

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

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

  20. Pengkun Wang, Chuancai Ge, Zhengyang Zhou, Xu Wang, Yuantao Li, Yang Wang*, Joint Gated Co-attention Based Multi-modal Networks for Subregion House Price Prediction, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021. (CCF-A, SCI 2 , IF=8.9)

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

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