Heng Ji
Heng Ji is a computer scientist who works on information extraction and natural language processing. She is well known for her work on joined named entity recognition and relation extraction,[1] as well as for her work on cross-document event extraction.[2] She has been coordinating the popular NIST TAC Knowledge Base Population task since 2010.[3] She has been recognised as one of AI's 10 to watch by IEEE Intelligent Systems in 2013,[4] and has won multiple awards, including a NSF Career Award in 2009,[5] Google Research awards in 2009 and 2014,[6] and an IBM Watson Faculty Award in 2012.[7]
Heng Ji | |
|---|---|
| Born | China |
| Alma mater | New York University (PhD and MSc in Computer Science) Tsinghua University (M.A. and B.A. in Computational Linguistics) |
| Known for | Information Extraction Natural Language Processing |
| Scientific career | |
| Fields | Computer Science |
| Institutions | University of Illinois at Urbana-Champaign Amazon Rensselaer Polytechnic Institute City University of New York |
| Thesis | Improving Information Extraction and Translation Using Component Interactions (2008) |
| Doctoral advisor | Ralph Grishman |
| Website | Personal website |
Education edit
Heng Ji obtained a Bachelor's and master's degree in Computational Linguistics from Tsinghua University. She subsequently obtained a MSc, then PhD in Computer Science from New York University in 2008 under the supervision of Ralph Grishman. Her PhD thesis was on the topic of information extraction, with a particular focus on joint training of multiple components in the information extraction pipeline, as well as cross-lingual learning.[8]
Career edit
Upon graduating with a PhD from New York University, Ji took up a position as assistant professor at Queens College, City University of New York, where she founded the BLENDER Lab,[9] which focuses on research on cross-lingual, cross-documents, cross-media information extraction and fusion. In 2013, she joined Rensselaer Polytechnic Institute as an Edward P. Hamilton Development Chair and Tenured associate professor in Computer Science.[10] Since 2019, she has been a full professor at the University of Illinois at Urbana–Champaign,[11] as well as an Amazon Scholar.
Research edit
Heng Ji works in the area of natural language processing, machine learning and information extraction. She has published over 300 peer-reviewed research papers.[12] Her work is published in the proceedings of computer science conferences, including the Annual Meeting of the Association for Computational Linguistics, The Web Conference, and the ACM Conference on Knowledge Discovery and Data Mining (KDD). Ji is a leading researcher in information extraction, having coordinated the popular NIST TAC Knowledge Base Population shared task since 2010.[3] She is most recognised for her work on modelling interactions between subtasks in information extraction,[1] which was also the topic of her PhD thesis,[8] and for her work on event detection using cross-document signals.[2]
Selected honors and distinctions edit
- 2009 NSF Career Award[5]
- 2009 Google Research Award
- 2012 IBM Watson Faculty Award[7]
- 2013 IEEE AI's 10 to Watch[4]
- 2014 Google Research Award[6]
- 2016 World Economic Forum, 'Young Scientist'[13]
- 2017 World Economic Forum, 'Young Scientist'[14]
- 2020 Annual Meeting of the Association for Computational Linguistics, best demonstration paper[15]
References edit
- ^ a b Li, Qi; Ji, Heng (2014-06-01). "Incremental Joint Extraction of Entity Mentions and Relations". Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics (ACL2014). Annual Meeting of the Association for Computational Linguistics. Baltimore, Maryland: Association for Computational Linguistics. pp. 402–412.
- ^ a b Ji, Heng; Grishman, Ralph (2008-06-01). "Refining Event Extraction through Cross-Document Inference". Proceedings of ACL-08: HLT. Annual Meeting of the Association for Computational Linguistics. Columbus, Ohio: Association for Computational Linguistics. pp. 254–262.
- ^ a b Ji, Heng; Grishman, Ralph; Dang, Hoa Trang; Griffitt, Kira; Ellis, Joe (2010-01-01). "Overview of the TAC 2010 Knowledge Base Population Track". Proceedings of Third Text Analysis Conference (TAC). Text Analysis Conference. National Institute of Standards and Technology. CiteSeerX 10.1.1.357.1854.
- ^ a b Zeng, Daniel (2013-09-16). "AI's 10 to Watch". IEEE Intelligent Systems. 28 (3): 86–96. doi:10.1109/MIS.2013.57. S2CID 18869823.
- ^ a b "CAREER: Cross-Document Cross-Lingual Event Extraction and Tracking". National Science Foundation. March 1, 2010. Retrieved February 21, 2021.
- ^ a b "Google Faculty Research Awards -- February 2014" (PDF). Google. February 2014. Retrieved February 21, 2021.
- ^ a b "IBM Announces Student Winners of Watson Case Competition from Cornell University -- Faculty award winners from Nine Universities Also Announced; Professors to Receive $10,000 Grants for Watson Curriculums". IBM. October 23, 2012. Retrieved February 21, 2021.
- ^ a b Ji, Heng (2008). Improving Information Extraction and Translation Using Component Interactions (PDF) (PhD). University of Aberdeen.
- ^ "BLENDER Lab". Retrieved February 21, 2021.
- ^ "Natural Language Processing Expert Heng Ji Joins Rensselaer". Rensselaer Polytechnic Institute. 2013. Retrieved February 21, 2021.
- ^ "Illinois CS Adds Eight New Faculty, Broadening Expertise in NLP, Security, Robotics, and More". Rensselaer Polytechnic Institute. 2019. Retrieved February 21, 2021.
- ^ "Heng Ji - Google Scholar Citations". scholar.google.com. Retrieved 2021-02-21.
- ^ "Young Scientists" (PDF). World Economic Forum. 2016. Retrieved February 21, 2021.
- ^ "Young Scientists Community" (PDF). World Economic Forum. 2017. Retrieved February 21, 2021.
- ^ "Best Paper Awards at ACL 2020". ACL 2020. 2020-07-08. Retrieved February 21, 2021.