Man must explore


Why not change the world!

Research Interests


  • Machine Learning/ Deep Learning
    • Representation Learning
    • Graph Neural Networks
    • Memory Networks
  • Natural Language Processing
    • Question Answering
    • Text Generation
    • Text Representation
    • Topic Modelling

Publications


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Preprints

  1. Yu Chen, Lingfei Wu and Mohammed J. Zaki, Toward Subgraph Guided Knowledge Graph Question Generation with Graph Neural Networks.
  2. Shangqing Liu, Yu Chen, Xiaofei Xie, Jing Kai Siow and Yang Liu, Automatic Code Summarization via Multi-dimensional Semantic Fusing in GNN.

Conference Publications

  1. Yu Chen, Ananya Subburathinam, Ching-Hua Chen and Mohammed J. Zaki, Personalized Food Recommendation as Constrained Question Answering over a Large-scale Food Knowledge Graph. In Proceedings of the 14th International Conference on Web Search and Data Mining (WSDM 2021), Mar. 8-12, 2021. 
  2. Yu Chen, Lingfei Wu and Mohammed J. Zaki, Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings. In Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Dec. 6-12, 2020. [PDF][Code]
  3. Nidhi Rastogi, Oshani Seneviratne, Yu Chen, Jon Harris, Diya Li, Ananya Subburathinam, Ruisi Jian, Megan Goulet, Yuheng Zhou, Osama Minhas, Jared Okun, Aaron Hill, Ching-Hua Chen and Dan Gruen, Applying Learning and Semantics for Personalized Food Recommendations. In Proceedings of the 19th International Semantic Web Conference (ISWC 2020), Nov. 2-6, 2020. Demo Track paper. [PDF]
  4. Yu Chen, Ching-Hua Chen and Mohammed J. Zaki, Combining User Preferences and Health Needs in Personalized Food Recommendation. In Proceedings of the 2020 American Medical Informatics Association (AMIA) Virtual Annual Symposium (AMIA 2020), Nov. 14-18, 2020. [PDF]
  5. Yu Chen, Lingfei Wu and Mohammed J. Zaki, GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension. In Proceedings of the 29th International Joint Conference on Artificial Intelligence (IJCAI 2020), Yokohama, Japan, 2020. Acceptance rate=12.6% (592 out of 4717). [PDF][Code]
  6. Yu Chen, Lingfei Wu and Mohammed J. Zaki, Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation. In Proceedings of the 8th International Conference on Learning Representations (ICLR 2020), Apr. 26-30, 2020. [PDF][Code][Slides]
  7. Yu Chen, Lingfei Wu and Mohammed J. Zaki, Deep Iterative and Adaptive Learning for Graph Neural Networks. In AAAI 2020 Workshop on Deep Learning on Graphs: Methodologies and Applications (AAAI DLGMA 2020), New York, NY, USA, Feb. 7-12, 2020. (Best Student Paper Award). [PDF][Code][Slides]
  8. Yu Chen, Lingfei Wu and Mohammed J. Zaki, Natural Question Generation with Reinforcement Learning Based Graph-to-Sequence Model. In NeurIPS 2019 Workshop on Graph Representation Learning (NeurIPS GRL 2019), Vancouver, BC, Canada, Dec. 8-14, 2019. [PDF][Code]
  9. Steven Haussmann, Yu Chen, Oshani Seneviratne, Nidhi Rastogi, James Codella, Ching-Hua Chen, Deborah McGuinness, Mohammed J. Zaki, FoodKG Enabled Q&A Application. In Proceedings of the 18th International Semantic Web Conference (ISWC 2019), Auckland, New Zealand, Oct. 26-30, 2019. Demo Track paper. [PDF][Code]
  10. Steven Haussmann, Oshani Seneviratne, Yu Chen, Yarden Ne’eman, James Codella, Ching-Hua Chen, Deborah L. McGuinness and Mohammed J. Zaki, FoodKG: A Semantics-Driven Knowledge Graph for Food Recommendation. In Proceedings of the 18th International Semantic Web Conference (ISWC 2019), Auckland, New Zealand, Oct. 26-30, 2019. Resources Track Full Paper. [PDF][Website][Code]
  11. Yu Chen, Lingfei Wu and Mohammed J. Zaki, GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension. In ICML 2019 Workshop on Learning and Reasoning with Graph-Structured Representations (ICML LRG 2019), Long Beach, CA, USA, Jun. 9-15, 2019. [PDF][Code]
  12. Yu Chen, Lingfei Wu and Mohammed J. Zaki, Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases. In Proceedings of the 2019 Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL-HLT 2019), Minneapolis, MN, USA, Jun. 2-7, 2019. Long Oral Paper. [PDF][Code][Slides]
  13. Yu Chen, Rhaad M. Rabbani, Aparna Gupta and Mohammed J. Zaki, Comparative Text Analytics via Topic Modeling in Banking. In Proceedings of the 2017 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2017), Hawaii, USA, Nov. 27-Dec. 1, 2017. [PDF][Code]
  14.  Yu Chen and Mohammed J. Zaki, KATE: K-competitive Autoencoder for Text. In Proceedings of the 23rd International Conference on Knowledge Discovery and Data Mining (SIGKDD 2017), Halifax, NS, Canada, Aug. 13-17, 2017. Full Oral PaperAcceptance rate=8.6% (64 out of 748). [PDF][Code][Slides][Talk]
  15. Yu Chen, Hao Chen and Jie Shen, Fast Voxel-based Surface Propagation Method for Outlier Removal. In Proceedings of the 13th International CAD Conference (CAD 2016), Vancouver, BC, Canada, Jun. 27-29, 2016. [PDF][Code]

Journal Publications

  1. Hao Chen, Yu Chen, Xu Zhang, Baiyuan Li, Xiaoqiang Liu, Xuefei Shi and Jie Shen, A Fast Voxel-based Method for Outlier Removal in Laser Measurement. International Journal of Precision Engineering and Manufacturing (IJPEM), 2019. [PDF]

Patents

  1. Lingfei Wu, Yu Chen, Mohammed J. Zaki. Method and System for Subgraph Guided Knowledge Graph Question Generation. Filed, Jul. 2020.
  2. Lingfei Wu, Yu Chen, Mohammed J. Zaki. Method and System for Iterative Deep Graph Learning for Graph Neural Networks. Field, May 2020.
  3. Lingfei Wu, Yu Chen, Mohammed J. Zaki. Method and System for Natural Question Generation via Reinforcement Learning Based Graph-to-Sequence Model. Filed, Jan. 2020.
  4. Lingfei Wu, Yu Chen, Mohammed J. Zaki. Method and System for Conversational Machine Reading Comprehension via Graph Neural Networks. Filed, Aug. 2019.

Invited Talks

  • Dissertation talk entitled "Question Answering and Generation from Structured and Unstructured Data" at RPI, Jun. 24, 2020. [Slides]
  • Invited talk entitled "Natural Question Generation and Graph Structure Learning with Graph Neural Networks" at Tencent AI Lab America, Mar. 2020.
  • Invited talk entitled "Reinforcement Learning Based Graph-to-Sequence Model for Natural Question Generation" at Dataminr, Inc. and Amazon, Inc., Mar.-Apr. 2020.
  • Invited talk entitled "Automatic Graph Structure Learning for Graph Neural Networks" at IBM Research, Yorktown Heights, NY, USA, Nov. 18, 2019.
  • Invited talk entitled "Knowledge Base Question Answering and Its Potential Applications in Adaptive Education" at the 3rd International Conference on Artificial Intelligence + Adaptive Education (AIAED 2019), Beijing, China, May 24-25, 2019. [Slides]
  • Invited talk entitled "Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases" at IBM AI Horizons Seminar Series, May 2, 2019. [Talk]

Selected Awards

  • Best Student Paper Award of AAAI DLGMA 2020.
  • Student Travel Award of SIGKDD 2017.
  • 2nd Place at the 2016 Rensselaer Datathon, RPI.
  • The First-Class People’s Scholarship, UESTC, 2013, 2014.
  • National Scholarship, UESTC, 2012.

Old Projects

  • Evaluating countries and products in international trade. [PDF]
  • Empirical analysis of online social networks. [PDF]
  • Finding email correspondents in online social. [PDF]
  • Non-isolated and sharp featured surface outlier removal. [PDF]