About Me

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

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
  • pc member: 2023 SIGKDD