Jianling Wang

I am a 4th year Ph.D. student in the Department of Computer Science and Engineering at Texas A&M University, advised by Prof. James Caverlee. I received my Master's degree in Computer Science from Georgia Institute of Technology and my Bachelor's degree in Information Engineering from The Chinese University of Hong Kong. My research interests generally include data mining and machine learning, with a particular focus on recommendation systems and graph neural networks.

Publications

  • Sequential Recommendation for Cold-start Users with Meta Transitional Learning (Short Paper). [pdf] [code]
    Jianling Wang, Kaize Ding and James Caverlee.
    The 44rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2021.
  • Item Relationship Graph Neural Networks for E-Commerce. [pdf]
    Weiwen Liu, Yin Zhang, Jianling Wang, Yun He, James Caverlee, Patrick P. K. Chan, Daniel S. Yeung and Pheng-Ann Heng.
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.
  • Session-based Recommendation with Hypergraph Attention Networks. [pdf]
    Jianling Wang, Kaize Ding, Ziwei Zhu and James Caverlee.
    The 2021 SIAM International Conference on Data Mining (SDM), 2021.
  • Popularity-Opportunity Bias in Collaborative Filtering. [pdf]
    Ziwei Zhu, Yun He, Xing Zhao, Yin Zhang, Jianling Wang and James Caverlee.
    The 14th ACM International Conference on Web Search and Data Mining (WSDM), 2021.
  • Be More with Less: Hypergraph Attention Networks for Inductive Text Classification. [pdf] [code]
    Kaize Ding, Jianling Wang, Jundong Li, Dingcheng Li, and Huan Liu.
    The Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020.
  • Next-item Recommendation with Sequential Hypergraphs. [pdf] [code]
    Jianling Wang, Kaize Ding, Liangjie Hong, Huan Liu and James Caverlee.
    The 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020.
  • Measuring and Mitigating Item Under-Recommendation Bias in Personalized Ranking Systems. [pdf] [code]
    Ziwei Zhu, Jianling Wang and James Caverlee.
    The 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020.
  • ADORE: Aspect Dependent Online REview Labeling for Review Generation. [pdf] [code]
    Parisa Kaghazgaran, Jianling Wang, Ruihong Huang and James Caverlee.
    The 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2020.
  • Graph Prototypical Networks for Few-shot Learning on Attributed Networks. [pdf] [code]
    Kaize Ding, Jianling Wang, Jundong Li, Kai Shu, Chenghao Liu and Huan Liu.
    The 29th ACM International Conference on Information and Knowledge Management (CIKM), 2020.
  • Time to Shop for Valentine‚Äôs Day: Shopping Occasions and Sequential Recommendation in E-commerce. [pdf] [code]
    Jianling Wang, Raphael Louca, Diane Hu, Caitlin Cellier, James Caverlee and Liangjie Hong.
    The 13th ACM International Conference on Web Search and Data Mining (WSDM), 2020.
  • Key Opinon Leaders in Recommendation Systems: Opinion Elicitation and Diffusion. [pdf] [poster]
    Jianling Wang*, Kaize Ding*, Ziwei Zhu, Yin Zhang and James Caverlee. (*equal contribution)
    The 13th ACM International Conference on Web Search and Data Mining (WSDM), 2020.
  • User Recommendation in Content Curation Platforms. [pdf] [code]
    Jianling Wang, Ziwei Zhu and James Caverlee.
    The 13th ACM International Conference on Web Search and Data Mining (WSDM), 2020.
  • Recommending Music Curators: A Neural Style-Aware Approach. [pdf]
    Jianling Wang and James Caverlee.
    The 42th European Conference of Information Retrieval (ECIR), 2020.
  • Adaptive Hierarchical Translation-based Sequential Recommendation (short paper).
    Yin Zhang, Yun He, Jianling Wang and James Caverlee.
    The 31th International Conference on World Wide Web (WWW), 2020.
  • A Hierarchical Self-Attentive Model for Recommending User-Generated Item Lists. [pdf] [code]
    Yun He, Jianling Wang, Wei Niu and James Caverlee.
    The 28th ACM International Conference on Information and Knowledge Management (CIKM), 2019.
  • Improving Top-K Recommendation via Joint Collaborative Autoencoders (short paper). [pdf] [code]
    Ziwei Zhu, Jianling Wang and James Caverlee.
    The 30th International Conference on World Wide Web (WWW), 2019.
  • Recurrent Recommendation with Local Coherence. [pdf] [slides]
    Jianling Wang and James Caverlee.
    The 12th ACM International Conference on Web Search and Data Mining (WSDM), 2019.
  • Fairness-Aware Recommendation of Information Curators. [pdf]
    Ziwei Zhu, Jianling Wang, Yin Zhang and James Caverlee.
    The 2nd FATREC Workshop on Responsible Recommendation at RecSys, 2018.
  • Stockyard: A discrete event-based stock market exchange simulator. [pdf]
    Jianling Wang, Vivek George, Tucker Balch, and Maria Hybinette.
    Simulation Conference (WSC), 2017.

Industry Experience

  • Applied Scientist Intern, Prime Video, Amazon, Virtual, Aug 2020 - Nov 2020.
    Project: Two-tower Model with Metadata for Customer-title Relevance Prediction.
  • Data Science Intern, Data Science and Machine Learning, Etsy, Brooklyn, NY, June 2019 - Aug 2019.
    Project: Sequential Recommendation in E-commerce.
  • Research Summer Intern, OMXWare team, IBM Research, Almaden, CA, June 2018 - Aug 2018.
    Project: Exploring Gene Editing and CRISPR with OMXWare.
  • Research Summer Intern, Labbook team, IBM Research, Almaden, CA, May 2017 - Aug 2017.
    Project: Worked on text Analytics for context extraction and enrichment
  • Summer Research Engineer, Research Group, Airwatch VMWare, Atlanta, GA June 2016 - Aug 2016.
    Project: Worked on the research project for driver detection and enforcement and mainly focused on the scalable server and machine learning engine.

Teaching

Patents

  • Detecting driving and modifying access to a user device.
    U.S. Patent 9,979,814, issued May, 2018 & U.S. Patent 10,153,938, issued December, 2018.
    Chaoting Xuan, Ravish Chawla, Jianling Wang, and Kar Fai Tse

Professional Service

  • Program Committee: WSC 18, WSDM 22
  • Journal Reviewer: IEEE Intelligent Systems, TKDD, TKDE, TOIS
  • External Reviewer: WWW 18