Yanyan SHEN (沈艳艳)

Associate Professor with Tenure
SEIEE Building #03-528
Data Driven Software Technology Lab
Shanghai Jiao Tong University
Email: shenyy AT sjtu DOT edu DOT cn



Bio

Yanyan is currently a tenured associate professor at the Department of Computer Science and Engineering, Shanghai Jiao Tong University (SJTU). She received her bachelor degree from Peking University (PKU), and obtained her doctoral degree from National University of Singapore (NUS). Her broad research interests include: databases, data mining and machine learning. She focuses on developing efficient and automated solutions to facilitate data analytics in various data-driven application domains including finance, e-commerce, etc. Yanyan has won a few awards, including VLDB 2022 best paper award, DASFAA 2019 best paper runner-Up, APWeb-WAIM 2018 best student paper award, 2020 ACM SIGMOD China Rising Star award, and 2020 Shanghai Technical Invention award. She has served as a PC member of top international conferences such as SIGMOD, VLDB, ICDE, KDD and been selected as VLDB 2019 Distinguished Reviewer, ICDE 2019 Outstanding Reviewer. She has been invited to serve as Associate Editor of IEEE TKDE and PVLDB 2023, Demo Co-chair of ICDE 2023.

Research Interests: complex data analytics, data-driven machine learning, AI for DB / DB for AI.

I am looking for self-motivated undergraduate and graduate students who are strongly committed to research. If you are interested in machine learning, data analytics and management, feel free to send me your CV.

What's New



Recent Publications [Google Scholar]

  • Shuming Kong, Yanyan Shen, et al. Resolving Training Biases via Influence-based Data Relabeling. In Proceedings of the 10th International Conference on Learning Representations (ICLR), 2022. (oral, accept rate = 54/3391)
  • Shuming Kong, Weiyu Cheng, Yanyan Shen, Linpeng Huang. AutoSrh: An Embedding Dimensionality Search Framework for Tabular Data Prediction. IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
  • Yanyan Shen, Lifan Zhao, et al. RESUS: Warm-Up Cold Users via Meta-Learning Residual User Preferences in CTR Prediction. ACM Transactions on Information Systems (TOIS), 2022.
  • Yiming Li, Yanyan Shen, et al. Camel: Managing Data for Efficient Stream Learning. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD), 2022.
  • Qiyu Liu, Yanyan Shen, et al. LHI: A Learned Hamming Space Index Framework for Efficient Similarity Search. In Proceedings of the 2022 International Conference on Management of Data (SIGMOD), 2022.
  • Jingzhi Fang, Yanyan Shen, et al. ETO: Accelerating Optimization of DNN Operators by High-Performance Tensor Program Reuse. In Proceedings of the VLDB Endowment (PVLDB), 2022.
  • Jingshu Peng, et al. Sancus: Staleness-Aware Communication-Avoiding Full-Graph Decentralized Training in Large-Scale Graph Neural Networks. In Proceedings of the VLDB Endowment (PVLDB), 2022.
  • Runjin Chen, Tong Li, Yanyan Shen, et al. GCF-RD: A Graph-based Contrastive Framework for Semi-Supervised Learning on Relational Databases. In Proceedings of the 31st ACM International Conference on Information and Knowledge Management (CIKM), 2022.
  • Xin Zhang, Yanyan Shen, et al. Feature-Oriented Sampling for Fast and Scalable GNN Learning. In Proceedings of the 2022 IEEE International Conference on Data Mining (ICDM), 2022. (accept rate = 85/870)
  • Zhikai Wang, Yanyan Shen. Time-aware Multi-interest Capsule Network for Sequential Recommendation. In Proceedings of the SIAM International Conference on Data Mining (SDM), 2022. (accept rate=83/298)
  • Yanyan Shen, Baoyuan Ou, Ranzhen Li. MBN: Towards Multi-behavior Sequence Modeling for Next Basket Recommendation. ACM Transactions on Knowledge Discovery from Data (TKDD), 2022.
  • Weiyu Cheng, Yanyan Shen, et al. Dual-Embedding based Deep Latent Factor Models for Recommendation. ACM Transactions on Knowledge Discovery from Data (TKDD), 2021.
  • Runjin Chen, Yanyan Shen, et al. GNEM: A Generic One-to-Set Neural Entity Matching Framework. In Proceedings of the Web Conference (TheWebConf), 2021.
  • Qiyu Liu, Yanyan Shen, et al. LHist: Towards Learning Multi-dimensional Histogram for Massive Spatial Data. In Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE), 2021.
  • Yiming Li, Yanyan Shen, et al. Palette: Towards Multi-source Model Selection and Ensemble for Reuse. In Proceedings of the 37th IEEE International Conference on Data Engineering (ICDE), 2021.
  • Jia Li, Shimin Di, Yanyan Shen, et al. FluxEV: A Fast and Effective Unsupervised Framework for Time-Series Anomaly Detection. In Proceedings of the 14th ACM International Conference on Web Search and Data Mining (WSDM), 2021. (accept rate=112/603)
  • Xujia Li, Yanyan Shen, et al. Mcore: Multi-Agent Collaborative Learning for Knowledge-Graph-Enhanced Recommendation. In Proceedings of the 2021 IEEE International Conference on Data Mining (ICDM), 2021. (accept rate = 98/990)
  • Jingshu Peng, Yanyan Shen, et al. GraphANGEL: Adaptive and Structure-Aware Sampling on Graph Neural Networks. In Proceedings of the 2021 IEEE International Conference on Data Mining (ICDM), 2021. (accept rate = 98/990)
  • Liujun Wang, Yanyan Shen. BOUNCE: An Efficient Selective Enumeration Approach for Nested Named Entity Recognition. In Proceedings of the 5th Asia Pacific Web (APWeb) and Web-Age Information Management (WAIM) Joint International Conference on Web and Big Data (APWeb-WAIM), 2021. (full, accept rate = 44/172)
  • Jingzhi Fang, Yanyan Shen, et al. Optimizing DNN Computation Graph using Graph Substitutions. In Proceedings of the VLDB Endowment (PVLDB), 2020.
  • Qiyu Liu, Libin Zheng, Yanyan Shen, et al. Stable Learned Bloom Filters for Data Streams. In Proceedings of the VLDB Endowment (PVLDB), 2020.
  • Weiyu Cheng, Yanyan Shen, et al. Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions. In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI), 2020. (accept rate=1591/7737)
  • Xian Zhou, Yanyan Shen, et al. FreqST: Exploiting Frequency Information in Spatiotemporal Modeling for Traffic Prediction. In Proceedings of the 2020 IEEE International Conference on Data Mining (ICDM), 2020. (accept rate = 19.7%)


Professional Services

Journal Associate Editor

  • IEEE Transactions on Knowledge and Data Engineering (TKDE)

Journal Guest Editor

  • VLDB Journal (Special Issue on Data Science for Responsible Data Management 2021)
  • ACM/IMS Transactions on Data Science (Special Issue on Data Science for Next-generation Big Data 2021)
  • Data Science and Engineering (Special Issue on DASFAA 2020)

Journal Reviewer

  • IEEE Transactions on Knowledge and Data Engineering (TKDE)
  • ACM/IMS Transactions on Data Science (TDS)
  • IEEE Transactions on Computers (TC)
  • IEEE Transactions on Intelligent Transportation Systems (TITS)

Conference Program Committee

  • ACM International Conference on Management of Data (SIGMOD): 2021, 2023
  • PVLDB Review Board: 2019, 2020, 2022, 2023 (Associate Editor)
  • IEEE International Conference on Data Engineering (ICDE): 2018, 2019, 2020, 2022, 2023 (Demo Co-chair)
  • ACM International Conference on Knowledge Discovery and Data Mining (SIGKDD): 2019, 2020, 2021, 2022
  • International Joint Conference on Artificial Intelligence (IJCAI): 2018, 2019, 2020
  • AAAI Conference on Artificial Intelligence (AAAI): 2019, 2020, 2021, 2022
  • ACM Symposium on Cloud Computing (SOCC): 2020
  • ACM International Conference on Information and Knowledge Management (CIKM): 2019
  • SIAM International Conference on Data Mining (SDM): 2021
  • Database Systems for Advanced Applications (DASFAA): 2017, 2018, 2019, 2020, 2021


Teaching

  • [Spring] Computer Architecture (cs undergraduate students)
  • [Spring] English for Academic Purposes (cs doctoral students)
  • [Fall] Problem Solving and Programming Practice (cs undergraduate students)
  • Programming: Practice and Core Guidelines (2016/2017/2018)
  • Programming Language (2016/2017)


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