Yanyan SHEN (沈艳艳)

Tenure-track Associate Professor

SEIEE Building #03-528
Data Driven Software Technology (DDST) Laboratory
Department of Computer Science and Engineering
Shanghai Jiao Tong University
Email: shenyy AT sjtu DOT edu DOT cn

Welcome to visit our DDST lab website!




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About Me

I am a tenure-track associate professor in the Department of Computer Science and Engineering at Shanghai Jiao Tong University (SJTU). Prior to joining SJTU, I received my bachelor degree from Peking University in 2010, and got my doctoral degree from National University of Singapore in 2015. I worked as a research intern at AT&T Shannon Lab (during summer 2011/2012) and Microsoft Research (June-September 2013).

Research Interests

  • Complex data analytics and processing
  • Data-driven machine learning

I am looking for self-motivated Undergraduate, Master and PhD 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.



Selected Publications [Google Scholar]

Journal Papers

  • W. Cheng et al. Dual-Embedding based Latent Factor Models for Recommendation. TKDD, to appear.
  • Xian Zhou, Yanyan Shen, Linpeng Huang, Tianzi Zang, Yanmin Zhu. Multi-level Attention Networks for Multi-step Citywide Passenger Demands Prediction. TKDE, 2020.
  • Kaixing Dong, Bowen Zhang, Yanyan Shen, Yanmin Zhu, Jiadi Yu. GAT: A Unified GPU-accelerated Framework for Processing Batch Trajectory Queries. TKDE, 2019.
  • Luciano Barbosa, Valter Crescenzi, Xin Luna Dong, Paolo Merialdo, Federico Piai, Disheng Qiu, Yanyan Shen, Divesh Srivastava. Big Data Integration for Product Specifications. IEEE Data Eng. Bull. 41(2): 71-81, 2018.
  • Wei Lu, Yanyan Shen, Tongtong Wang, Meihui Zhang, H. V. Jagadish, Xiaoyong Du. Fast Failure Recovery in Vertex-centric Distributed Graph Processing Systems. TKDE, 2018.
  • Yanan Xu, Yanmin Zhu, Yanyan Shen, Jiadi Yu. Leveraging App Usage Contexts for App Recommendation: A Neural Approach. WWW, 2018.
  • Kaixin Huang, Jie Zhou, Sumin Li, Linpeng Huang, Yanyan Shen. NVHT: An Efficient Key-Value Storage Library for Non-Volatile Memory. Journal of Parallel and Distributed Computing (JPDC), 2018.
  • Hao Liu, Linpeng Huang, Yanmin Zhu, Shengan Zheng, Yanyan Shen. HMFS: A Hybrid In-memory File System with Version Consistency. JPDC, 2018.
  • Shengan Zheng, Hao Liu, Linpeng Huang, Yanyan Shen, Yanmin Zhu. HMVFS: A Versioning File System on DRAM/NVM Hybrid Memory. JPDC, 2017.
  • Hao Liu, Linpeng Huang, Yanmin Zhu, Yanyan Shen. LibreKV: A Persistent In-Memory Key-Value Store. IEEE Transactions on Emerging Topics in Computing, 2017. (IF=3.826)
  • Yanyan Shen, Qingchao Cai, Wei Lu, Dalie Sun, Zhongle Xie. epiCG: A GraphUnit Based Graph Processing Engine on epiC. Big Data Research 4: 59-69, 2016. [PDF]

Conference Papers

  • R. Chen et al. GNEM: A Generic One-to-Set Neural Entity Matching Framework. In WWW, 2021.
  • Q. Liu et al. LHist: Towards Learning Multi-dimensional Histogram for Massive Spatial Data. In ICDE, 2021.
  • Y. Li et al. Palette: Towards Multi-source Model Selection and Ensemble for Reuse. In ICDE, 2021.
  • J. Fang et al. Optimizing DNN Computation Graph using Graph Substitutions. In PVLDB, 2020.
  • Q. Liu et al. Stable Learned Bloom Filters for Data Streams. In PVLDB, 2020.
  • Z. Liu et al. Intent Preference Decoupling for User Representation on Online Recommender System. In IJCAI, 2020.
  • W. Cheng, Y. Shen, L. Huang. Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions. In AAAI, 2020.
  • X. Zhou, Y. Shen, L. Huang. Exploiting Frequency Information in Spatiotemporal Modeling for Traffic Prediction. In ICDM, 2020.
  • Yi Zhao, Yanyan Shen, Junjie Yao. Recurrent Neural Network for Text Classification with Hierarchical Multiscale Dense Connections. In IJCAI, 2019.
  • Yanan Xu, Yanmin Zhu, Yanyan Shen, Jiadi Yu. Learning Shared Vertex Representation in Heterogeneous Graphs with Convolutional Networks for Recommendation. In IJCAI, 2019.
  • Weiyu Cheng, Yanyan Shen, Linpeng Huang, Yanmin Zhu. Incorporating Interpretability into Latent Factor Models via Fast Infuence Analysis. In KDD, 2019. (research track, oral) [PDF]
  • Shimin Di, Yanyan Shen, Lei Chen. Relation Extraction via Domain-aware Transfer Learning. In KDD, 2019. (research track, oral) [PPT]
  • Yi Zhao, Yanyan Shen, Yanmin Zhu, Junjie Yao. Forecasting Wavelet Transformed Time Series with Attentive Neural Networks. In ICDM, 2018. [PPT]
  • Ranzhen Li, Yanyan Shen, Yanmin Zhu. Next Point-of-Interest Recommendation with Temporal and Multi-level Context Attention. In ICDM, 2018. [PPT]
  • Weiyu Cheng, Yanyan Shen, Yanmin Zhu, Linpeng Huang. DELF: A Dual-Embedding based Deep Latent Factor Model for Recommendation. In IJCAI, 2018.
  • Yanyan Shen, Jinyang Gao. Refine or Represent: Residual Networks with Explicit Channel-wise Configuration. In IJCAI, 2018.
  • Jinyang Gao, Beng Chin Ooi, Yanyan Shen, Wang-Chien Lee. Cuckoo Feature Hashing: Dynamic Weight Sharing for Sparse Analytics. In IJCAI, 2018.
  • Zhaoyang Liu, Yanyan Shen, Yanmin Zhu. Where Will Dockless Shared Bikes be Stacked? -- Parking Hotspots Detection in a New City. In KDD, 2018. (oral)
  • Shimin Di, Jingshu Peng, Yanyan Shen, Lei Chen. Transfer Learning via Feature Isomorphism Discovery. In KDD, 2018.
  • Bowen Zhang, Yanyan Shen, Yanmin Zhu, Jiadi Yu. A GPU-accelerated Framework for Processing Trajectory Queries. In ICDE, 2018. [PPT]
  • Xian Zhou, Yanyan Shen, Yanmin Zhu, Linpeng Huang. Predicting Multi-step Citywide Passenger Demands using Attention-based Neural Networks. In WSDM, pages 736-744, 2018.
  • Zhaoyang Liu, Yanyan Shen, Yanmin Zhu. Inferring Dockless Shared Bike Distribution in New Cities. In WSDM, pages 378-386, 2018.
  • Weiyu Cheng, Yanyan Shen, Yanmin Zhu, Linpeng Huang. A Neural Attention Model for Urban Air Quality Inference: Learning the Weights of Monitoring Stations. In AAAI, 2018. [PDF]
  • Shengan Zheng, Hong Mei, Linpeng Huang, Yanyan Shen, Yanmin Zhu. Adaptive Prefetching for Accelerating Read and Write in NVM-based File Systems. In ICCD, 2017.
  • Disheng Qiu, Luciano Barbosa, Xin Luna Dong, Yanyan Shen, Divesh Srivastava. DEXTER: Large-Scale Discovery and Extraction of Product Specifications on the Web. VLDB 2016, pages 2194-2205. [PDF]
  • Yanyan Shen, Gang Chen, H. V. Jagadish, Wei Lu, Beng Chin Ooi, Bogdan Marius Tudor. Fast Failure Recovery in Distributed Graph Processing Systems. VLDB 2015, pages 437-448. [PDF] [PPT]
  • Yanyan Shen, Kaushik Chakrabarti, Surajit Chaudhuri, Bolin Ding, Lev Novik. Discovering Queries based on Example Tuples. SIGMOD 2014, pages 493-504. [PDF] [PPT]
  • Wei Lu, Yanyan Shen, Su Chen, Beng Chin Ooi. Efficient Processing of k-Nearest Neighbor Joins using MapReduce. PVLDB 5(10): 1016-1027 (2012). [PDF]
  • Xuan Liu, Meiyu Lu, Beng Chin Ooi, Yanyan Shen, Sai Wu, Meihui Zhang. CDAS: a Crowdsourcing Data Analytics System. PVLDB 5(10): 1040-1051 (2012). [PDF]


Professional Services

Program Committee Member: SIGMOD 2021, VLDB 2019/2020/2022, ICDE 2018/2019/2020, KDD 2019/2020/2021, SOCC 2020, IJCAI 2018/2019/2020, AAAI 2019/2020/2021, CIKM 2019, SDM 2021, DASFAA 2017-2021, WISE 2017/2018
Journal Reviewer: IEEE TKDE, IEEE TPDS, IEEE TDS
Talks: (NDBC'17) Tips for Writing Technical Papers.



Teaching

[Spring 2021] Computer Architecture (cs undergraduate students)

[Spring 2021] English for Academic Purposes (cs doctoral students)

[Fall 2020] Problem Solving and Programming Practice (cs undergraduate students)

Programming: Practice and Core Guidelines (2016/2017/2018)

Programming Language (2016/2017)



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