Jianling Wang

This is Jianling Wang. I am a research scientist working at Google DeeMind, Mountain View. I obtained my Ph.D. degree from the Department of Computer Science and Engineering at Texas A&M University, advised by Prof. James Caverlee. Before that, 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.

Google Scholar

Github

Publication

Fresh Content Recommendation at Scale: A Multi-funnel Solution and the Potential of LLMs.
Jianling Wang, Haokai Lu and Minmin Chen.
The 17th ACM International Conference on Web Search and Data Mining (WSDM) Industry Day, 2024.
Federated Conversational Recommender Systems.
Allen Lin, Jianling Wang, Ziwei Zhu and James Caverlee.
The 46th European Conference of Information Retrieval (ECIR), 2024.
Countering Mainstream Bias via End-to-End Adaptive Local Learning.
Jinhao Pan, Ziwei Zhu, Jianling Wang, Allen Lin and James Caverlee.
The 46th European Conference of Information Retrieval (ECIR), 2024.
Fresh Content Needs More Attention: Multi-funnel Fresh Content Recommendation. [pdf]
Jianling Wang*, Haokai Lu*, Sai zhang, Bart Locanthi, Haoting Wang, Dylan Greaves, Benjamin Lipshitz, Sriraj Badam, Ed H. Chi, Cristos Goodrow, Su-Lin Wu, Lexi Baugher, Minmin Chen. (*equal contribution)
The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023
Robust Graph Meta-learning for Weakly-supervised Few-shot Node Classification.
Kaize Ding, Jianling Wang, Jundong Li, James Caverlee and Huan Liu.
CIKM 2022 Workshop on Trustworthy Learning on Graphs (TrustLOG), 2022.
Learning Strong Graph Neural Networks with Weak Information. [pdf]
Yixin Liu, Kaize Ding, Jianling Wang, Vincent Lee, Huan Liu, Shirui Pan.
The 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023
Enhancing User Personalization in Conversational Recommenders. [pdf]
Allen Lin, Ziwei Zhu, Jianling Wang, and James Caverlee.
The 34th International Conference on World Wide Web (WWW), 2023.
Closed-book Question Generation via Contrastive Learning. [pdf]
Xiangjue Dong, Jiaying Lu, Jianling Wang, and James Caverlee.
The 17th Annual Meeting of the European chapter of the Association for Computational Linguistics (EACL), 2023.
Learning to Augment for Casual User Recommendation. [pdf]
Jianling Wang, Ya Le, Bo Chang, Yuyan Wang, Ed Chi and Minmin Chen.
The 33th International Conference on World Wide Web (WWW), 2022.
Towards Fair Conversational Recommender Systems.
Allen Lin, Ziwei Zhu, Jianling Wang and James Caverlee.
The 5th FAccTRec Workshop on Responsible Recommendation at RecSys (FAccTRec), 2022.
Meta Propagation Networks for Graph Few-shot Semi-supervised Learning. [pdf][code]
Kaize Ding, Jianling Wang, James Caverlee and Huan Liu.
AAAI Conference on Artificial Intelligence (AAAI), 2022.
Quantifying and Mitigating Popularity Bias in Conversational Recommender Systems. [pdf]
Allen Lin, Jianling Wang, Ziwei Zhu and James Caverlee.
The 31th ACM International Conference on Information and Knowledge Management (CIKM), 2022.
Robust Graph Meta-learning for Weakly-supervised Few-shot Node Classification. [pdf] (Best Paper Award)
Kaize Ding, Jianling Wang, Jundong Li, James Caverlee and Huan Liu.
CIKM 2022 Workshop on Trustworthy Learning on Graphs (TrustLOG), 2022.
Exploring Heterogeneous Metadata for Video Recommendation With Two-Tower Model. [pdf]
Jianling Wang, Ainur Yessenalina and Alireza Roshan-Ghias
The Workshop on Context-Aware Recommendation Systems at RecSys (CARS), 2021.
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.
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.
Session-based Recommendation with Hypergraph Attention Networks. [pdf] [code]
Jianling Wang, Kaize Ding, Ziwei Zhu and James Caverlee.
The 2021 SIAM International Conference on Data Mining (SDM), 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.
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.
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.
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’s 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.
Recurrent Recommendation with Local Coherence. [pdf]
Jianling Wang and James Caverlee.
The 12th ACM International Conference on Web Search and Data Mining (WSDM), 2019.
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.
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.

Awards

EECS Rising Star, 2022
TAMU CSE Student Travel Award, 2022
SIGIR Travel Award, 2021
SDM Travel Award, 2021
ECIR Travel Award, 2020

Professional Service

Program Committee: WSC 18, WSC 21, WSDM 22, KDD 22, WSDM 23, AAAI 23, KDD 23, IJCAI 23, CIKM 23, WSDM 24, SDM 24
Conference Reviewer: NeurIPS 21 22 23, ICML 22, ICML 23, AAAI 24
Journal Reviewer: IEEE Intelligent Systems, TKDD, TKDE, TOIS

Industry Experience

Research Intern, Brain, Google, Virtual, June 2021 - Aug 2021.
Project: Meta Reinforcement Learning for Recommendation System.
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.
Research Assistant, Hong Kong Applied Science & Technology Research Institute, Hong Kong, May 2015 - June 2015.
Project: Designed and developed the trading strategy recommendation system
Research Assistant, Hong Kong Applied Science & Technology Research Institute, Hong Kong, May 2014 - Aug 2014.
Project: Developed a virtual whiteboard app in Android for an online course and training system

Patent

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