Zhiyu's Blog

My name is Zhiyu Chen (陈知雨). Now I am working as an applied scientist at Amazon in Seattle, US. My first name “Zhiyu” comes from an ancient Chinese poem (好雨知时节), which means good rain knows the best time to fall. I received my PhD from Lehigh University at 2022 with Prof. Brian D. Davison. My research interests include data mining, machine learning, natural language processing and information retrieval(word clouds generated from my reading list here).

Education

Lehigh University, Bethlehem, PA, USA
- Ph.D in Computer Science (2015-2022)
- GPA: 3.97/4.0
Ecole Supérieure d’Ingénieurs Léonard de Vinci, Paris, France
- Exchange Program (2014-2015)
- GPA: 15.75/20
Nanjing University of Aeronautics and Astronautics, Nanjing, China
- B.E. in Computer Science (2011-2015)
- GPA: 4.2/5.0 (ranking: 1/94)

Past Experience

Amazon, Seattle, WA, US (remote)
- Position: Applied Sciensist Intern (05/2021-09/2021)
- Responsibility: Proposed a reinforcement learning method for conversational question answering (this work was accepted by EMNLP Industry Track 2022).
- Mentors/Managers: Jie Zhao, Anjie Fang, Besnik Fetahu, Oleg Rokhlenko, Shervin Malmasi
Zhuiyi Technology, Shenzhen, Guangdong, China
- Position: Machine Learning Intern (05/2019-09/2019)
- Responsibility: Solutions for tasks in SuperGLUE. (Our submission ranked 3rd at the time of submission, including the human baseline ranked 1st)
- Manager: Yinan Xu
Bloomberg, Princeton, NJ, USA
- Position: Data Science Intern (06/2016-08/2016)
- Responsibility: Analysis of Bloomberg Data Licence usage patterns.
- Manager: Michael Liebman

Publications

Z. Chen, J. Choi, B. Fetahu, O. Rokhlenko, S. Malmasi Generate-then-Retrieve: Intent-Aware FAQ Retrieval in Product Search, Accepted by Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023)

P. Faustini, Z. Chen, B. Fetahu, O. Rokhlenko, S. Malmasi Answering Unanswered Questions through Semantic Reformulations in Spoken QA. Accepted by Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL 2023)

D. Luo, L. Zou, Q. Ai, Z. Chen, D. Yin, B.D. Davison Model-based Unbiased Learning to Rank. In Proceedings of The 16th Annual ACM International Conference on Web Search and Data Mining, (WSDM 2023)

Z. Chen, J. Zhao, A. Fang, B. Fetahu, O. Rokhlenko, S. Malmasi Reinforced Question Rewriting for Conversational Question Answering. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022)

M. Trabelsi, Z. Chen, S. Zhang, J. Heflin, and B. D. Davison StruBERT: Structure-aware BERT for Table Search and Matching. In Proceedings of the 31st Web Conference, Online, April, 2022 (WWW 2022)

Z. Chen, M. Trabelsi, J. Heflin, D. Yin, and B. D. Davison. (2021) MGNETS: Multi-Graph Neural Networks for Table Search. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management, Online, November, 2021 (CIKM 2021).

M. Trabelsi, Z. Chen, J. Heflin and B.D. Davison. (2021) Neural Ranking Models for Document Retrieval, Information Retrieval Journal, October, 2021

Z. Chen, S. Zhang, and B. D. Davison. (2021) WTR: A Test Collection for Web Table Retrieval. In Proceedings of 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, July

M. Trabelsi, Z. Chen, J. Heflin and B.D. Davison. (2020) A Hybrid Deep Model for Learning to Rank Data Tables. In Proceedings of the 2020 IEEE International Conference on Big Data (IEEE BigData 2020), December.

M. Trabelsi*, Z. Chen*, B. D. Davison, and J. Heflin. Relational Graph Embeddings for Table Retrieval. In the Seventh International Workshop on High Performance Big Graph Data Management, Analysis, and Mining (BigGraphs 2020), held with IEEE BigData 2020, December.

Z. Chen*, M. Trabelsi*, B. D. Davison, and J. Heflin. (2020) Towards Knowledge Acquisition of Metadata on AI Progress. In Proceedings of the ISWC 2020 Demos and Industry Tracks: From Novel Ideas to Industrial Practice, co-located with the 19th International Semantic Web Conference (ISWC 2020), November.

Z. Chen, M. Trabelsi, J. Heflin, Y. Xu, and B. D. Davison. (2020) Table Search Using a Deep Contextualized Language Model. In Proceedings of 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 589-598, July.

H. Ye, Z. Chen, D.-H. Wang, and B. D. Davison. (2020) Pretrained Generalized Autoregressive Model with Adaptive Probabilistic Label Clusters for Extreme Multi-label Text Classification. In Proceedings of 37th International Conference on Machine Learning, PMLR 119, July.

Z. Chen, H. Jia, J. Heflin, and B. D. Davison. (2020) Leveraging Schema Labels to Enhance Dataset Search. In Proceedings of the 42nd European Conference on Information Retrieval (ECIR 2020), pages 267-280, April.

Z. Chen, H. Jia, J. Heflin and B. D. Davison. (2018) Generating Schema Labels through Dataset Content Analysis. In Companion Proceedings of the The Web Conference (WWW ’18), pages 1515-1522. Presented at the International Workshop on Profiling and Searching Data on the Web(Profiles & Data:Search’18, co-located with The Web Conference), Lyon, France, April. Best paper award.

Talks

Deep Text Matching and Applications （slides）
- Presentation at Graduate Research Seminar Series (GRSS) of my Depth Study at the Lehigh University, Bethlehem, USA, May 2019.

Challenges and Progress in Dataset Search （slides, paper）
- Presentation at the Eighth BCS-IRSG Symposium on Future Directions in Information Access (FDIA 2018), co-located with the 8th International Conference on the Theory of Information Retrieval (ICTIR 2018), Tianjin, China, September 2018.