NSF CAREER Award: CAREER: Multilingual Learning for Event Structures from Text (2023-2028, $582,177)
We develop novel multilingual datasets and transfer learning methods for information extraction in natural language processing.
IARPA HIATUS Program: Human Interpretable Attribution of Text using Underlying Structure (2022-2026, $583,776)
We develop novel representation learning methods for authorship attribution, privacy preservation, and model explainability.
Army Research Office (ARO): Boosting and Extending Event Extraction using Interaction Structures from Texts (2021-2024, $353,430)
We develop novel methods to induce text structures to improve the performance, robustness, and flexibility of event extraction systems.
• Adobe Research Gift Fund (2018-2022, $135,000)
• Adobe Data Annotation Fund (2019-2022, $186,500)
• Adobe Member for the NSF Center for Big Learning (2011-2022, $100,000)
Our research introduces effective methods, systems, and datasets for the business of Adobe.
NSF Industry-University Cooperative Research Centers Program (IUCRC): University of Oregon: Center for Big Learning (CBL), Phase I, (2018-2023, $749,998)
Our CBL consortium focuses on the development of large-scale deep learning algorithms (DL) and DL-enabled big data applications in a broad spectrum of disciplines (i.e., healthcare, science, security, and education).
IARPA BETTER Program: Better Extraction from Text Towards Enhanced Retrieval (2019-2023, $439,458)
We develop state-of-the-art multilingual methods for information extraction that can perform event extraction for multiple languages with increasing fine-grained event types and argument roles.