Chuck Wooters
Senior Software Engineer at Displace
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolChuck Wooters is a senior software engineer and AI leader with 13+ years at the crossroads of linguistics, psychology, and computer science, holding a Ph.D. in speech recognition from UC Berkeley. He has led conversational AI efforts from research roles at ICSI and Semantic Machines to product and strategy roles at Microsoft, Apple, and as Head of AI at Displace, and he now co-founded Updaytr building phone-based AI agents. Chuck combines deep academic expertise—decades of published work and patents in multi-turn dialogue—with hands-on engineering, having implemented full stacks, voice front-ends, and backend infrastructure for startups and scale-ups. He’s an active open-source contributor (notably improving the Framenet corpus reader in NLTK for Python 3 and regex-based frame searches), demonstrating attention to tooling and reproducibility. Based in San Francisco, he focuses on making human-computer interaction feel like natural conversation and is drawn to the nuanced problems of voice-based communication. An engineer at heart, he blends research rigor with product-driven execution to ship AI systems that understand conversational nuance.
13 years of coding experience
30 years of employment as a software developer
Ph.D., Speech Recognition, Ph.D., Speech Recognition at University of California, Berkeley
English
Stackoverflow
1,384reputation
250kreached
9answers
1question
python
top-5%
Github Skills (16)
nltk10
python10
natural-language-processing10
nlp9
regular-expression9
pip6
algorithm6
twitter6
gis6
macos6
python-dataclasses6
documentation6
numpy6
semantics6
machine-learning5
Programming languages (11)
Github contributions (5)
nltk/nltk
Aug 2013 - Sep 2013
NLTK Source
Role in this project:
Back-end Developer
Back-end DeveloperContributions:15 commits, 2 comments in 25 days
Contributions summary:Chuck primarily contributed to the development and maintenance of the NLTK corpus reader for the Framenet dataset. Their work included refactoring code, fixing bugs in the demo function, and making updates for Python 3 compatibility. Furthermore, the user introduced features such as the ability to search for frames and lexical units based on regular expressions, demonstrating a focus on enhancing the functionality and usability of the Framenet corpus reader. The user also made PEP8 compliance changes.
nlppythonmachine-learningnltknatural-language-processing
wooters/dotfiles
Mar 2016 - Jul 2024
Contributions:105 pushes, 1 branch in 8 years 5 months
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