Kenneth Church
(he/him/his)
Professor of the Practice
Research interests
- Natural language processing and information retrieval
- Artificial intelligence
- Machine learning
Education
- PhD in Computer Science, Massachusetts Institute of Technology
- MS in Computer Science, Massachusetts Institute of Technology
- BS in Computer Science, Massachusetts Institute of Technology
Biography
Kenneth Church is a professor of the practice in the Khoury College of Computer Sciences at Northeastern University, based in Silicon Valley. He is a senior principal research scientist at Northeastern's Institute for Experiential AI.
Church's research focuses on natural language processing and information retrieval, artificial intelligence, and machine learning. Before joining Northeastern in 2022, he worked as a scientist at Baidu, a researcher at IBM, and a scientist at Johns Hopkins University.
Church was recognized as a Baidu Fellow in 2018, an Association for Computational Linguistics (ACL) Fellow in 2015, and served as president of ACL in 2012. He has published in NeurIPS, ACL, EMNLP, NAACL, the Journal of Natural Language Engineering, and Frontiers Interspeech, among others.
Outside of academic research, Church enjoys chess and hiking. He is the great-grandson of the inventor of a method that is still used today to predict stream runoff from mountain ranges across the west, as well as floods and droughts.
Recent publications
-
Emerging trends: General fine-tuning (gft)
Citation: K. Church, X. Cai, Y. Ying, Z. Chen, G. Xun, Y. Bian. (2022). Emerging trends: General fine-tuning (gft). Natural Language Engineering, 28(4), 519-535. DOI: 10.1017/S1351324922000237 -
Word Association Norms, Mutual Information, and Lexicography
Citation: Kenneth Ward Church and Patrick Hanks. (1990). Word Association Norms, Mutual Information, and Lexicography. Computational Linguistics, 16(1):22–29. -
Emerging trends: SOTA-Chasing
Citation: K. Church & V. Kordoni. (2022). Emerging Trends: SOTA-Chasing. Natural Language Engineering, 28(2), 249-269. DOI: 10.1017/S1351324922000043