Kenneth Church: Home Page
VecML.com
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About VecML
Vectors, machine learning (ML) and approximate nearest neighbors (ANN)
are the technology behind much of the recent excitement in Artificial
Intelligence (AI). VecML has products that support search, machine
learning, chat, RAG and agentive systems. All of this is available in
the cloud or locally on your phone/laptop. Running locally has
advantages in terms of privacy as well as cost, bandwidth and latency.
If you want to search photos on your phone, do you really want to
upload your private pictures to who-knows-where? Please try Vecy out.
It is available on both
iPhone
and
Android.
Bio
Ken Church works on large language models (LLMs).
He was an early advocate of
empirical methods and a founder of the Conference on Empirical
Methods in Natural Language Processing (EMNLP).
EMNLP is the second top conference in Computational Linguistics, according to this ranking.
He received his PhD from MIT in 1983, and worked for 20 years at AT&T Bell Labs.
After that he worked at Microsoft, Hopkins, IBM, Baidu, Northeastern and VecML.
He has worked on many applications
of LLMs including web
search, academic search, spelling correction, word-sense disambiguation, terminology, translation, lexicography,
compression, optical character recognition and speech (recognition,
synthesis, and diarization).
CV
Honors
- President of the Association for Computational
Linguistics (ACL) in 2012
- President of ACL SIGDAT (the group that organizes
EMNLP) from 1993 until 2011
- AT&T Fellow (2001)
- ACL Fellow (2015)
- ACM Fellow (2023)
Teaching
- 2023-Fall: CS 6120
- 2024-Spring: CS 7290
- 2025-Spring: CS 7290
Publications
- Google Scholar (h-index: 72)
- Semantic Scholar (h-index: 56)
-
https://orcid.org/0000-0001-8378-6069
- JSALT-2023 Better Together (for me)
Demos
Recommendations for Academic Papers
Startup Company
VecML
Misc
Semantic Scholar Abstracts by Language
Recent Talks/Papers