I work as an applied scientist in Amazon Product Graph Team from 2018.

I received my Ph.D. Degree in Computer Science from the University of Oklahoma 2022 advised by Dr. Christan Grant. Prior to that, I received M.S. in Computer Science from University of Oklahoma 2018, M.S. in Mathematics from University of Oklahoma 2013, and B.S. in Mathematics from Dalian University of Technology 大连理工大学 2011.

I work in areas of information extraction specially in event extraction and detection during my Ph.D. time at OU. During my Ph.D. time, I developed approaches for quick labeling data across different languages. I developed topic-aware event extraction methods to scale up event extraction on different domains, with high improvement on few-shot event types. I developed scalable container based pipeline for event extraction with Kalman filter adapted batchsize. We published the largest machine-coded political event dataset covering documents from 1979 to 2016 (2TB, 300 million documents), known as Terrier. Here is my dissertation: Scaling up Labeling, Mining, and Inferencing on Event Extraction.

Recent Publications

• Explainable and coherent complement recommendation based on large language models Zelong Li, Yan Liang, Ming Wang, Sungro Yoon, Jiaying Shi, Xin Shen, Xiang He, Chenwei Zhang, Wenyi Wu, Hanbo Wang, Jin Li, Jim Chan, Yongfeng Zhang (CIKM, 2024)

• Concept2Box: Joint Geometric Embeddings for Learning Two-View Knowledge Graphs Zijie Huang, Daheng Wang, Binxuan Huang, Chenwei Zhang, Jingbo Shang, Yan Liang, Zhengyang Wang, Xian Li, Christos Faloutsos, Yizhou Sun, Wei Wang (ACL, 2023)
• Ask-and-Verify: Span candidate generation and verification for attribute value extraction Yifan Ding, Yan Liang, Nasser Zalmout, Xian Li, Christan Grant, Tim Weninger (EMNLP, 2022)
• TAED: Topic-Aware Event Detection Yan Liang, Christan Grant (IEEE BigData, 2022)
• All You Need to Know to Build a Product Knowledge Graph Nasser Zalmout, Chenwei Zhang, Xian Li, Yan Liang, Xin Luna Dong (SIGKDD 2021 tutorial)
• AdaTag: Multi-Attribute Value Extraction from Product Profiles with Adaptive Decoding Jun Yan, Nasser Zalmout, Yan Liang, Christan Grant, Xiang Ren, Xin Luna Dong (ACL 2021)
• PAM: Understanding Product Images in Cross Product Category Attribute Extraction Rongmei Lin, Xiang He, Nasser Zalmout, Yan Liang, Li Xiong, Xin Luna Dong (SIGKDD 2021)
• AutoKnow: Self-Driving Knowledge Collection for Products of Thousands of Types Xin Luna Dong, Xiang He, Andrey Kan, Xian Li, Yan Liang, Jun Ma, Yifan Ethan Xu, Chenwei Zhang, Tong Zhao, Gabriel Blanco Saldana, Saurabh Deshpande, Alexandre Michetti Manduca, Jay Ren, Surender Pal Singh, Fan Xiao, Haw-Shiuan Chang, Giannis Karamanolakis, Yuning Mao, Yaqing Wang, Christos Faloutsos, Andrew McCallum, Jiawei Han (SIGKDD 2020)
• New Techniques for Coding Political Events across Languages Y Liang, K Jabr, C Grant, J Irvine, A Halterman (IEEE IRI 2018)
• Creating an automated event data system for arabic text A Halterman, J Irvine, Y Liang, C Grant, KT Jabr (ISA 2018)
• Adaptive scalable pipelines for political event data generation Y Liang, A Halterman, J Irvine, M Landis, P Jalla, C Grant, M Solaimani (IEEE BigData 2017)
• formalizing interruptible algorithms for human over-the-loop analytics Austin Graham, Yan Liang, Le Gruenwald, Christan Grant (IEEE BigData 2017)

External Services

• reviewer: 2018 IEEE IRI
• reviewer: 2020 IEEE BigData
• reviewer: 2021 IEEE ICMLA
• reviewer: 2022 ACM FAccT
• reviewer: 2022 ACM SIGIR
• reviewer: 2022 SIGKDD
• reviewer: 2022 CIKM
• pc member: 2023 SIGKDD
• pc member: 2024 SIGKDD
• pc member: 2024 CIKM
• pc member: 2025 PAKDD