KavitaΒ Ganesan
Chief AI Strategist & Architect Founder
Salt Lake City, Utah, United States
Summary
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Top SchoolKavita Ganesan is a Chief AI Strategist, architect, and founder with nearly 20 years of applied AI experience, specializing in LLMs, NLP, and search technologies. She founded Opinosis Analytics to help organizations from midmarket firms to government agencies turn AI initiatives into measurable business outcomes through her HI-AI Discovery Framework and Jumpstart AI Approach. A PhD-trained practitioner who brought the first AI/ML pipeline to GitHub and shipped features used by millions, she blends rigorous research with production-grade engineering. Kavita is the author of the award-winning The Business Case for AI and frequently advises enterprises like eBay, 3M, McKesson, and the U.S. Department of Energy on strategy, architecture, and adoption. Known for rescuing underperforming AI projects, she focuses on pragmatic opportunity selection, scalable architectures, and company-wide enablement to raise AI success rates. Based in Salt Lake City, she combines academic depth with a track record of real-world impact across industries.
11 years of coding experience
14 years of employment as a software developer
M.S, Computer Science, M.S, Computer Science at University of Southern CaliforniaB.S, Computer Science, B.S, Computer Science at Universiti Teknologi MalaysiaDoctor of Philosophy - PhD, Computer Science - AI, Language Models, Machine Learning, Natural Language Processing, Doctor of Philosophy - PhD, Computer Science - AI, Language Models, Machine Learning, Natural Language Processing at University of Illinois Urbana-Champaign
Github Skills (36)
gensim10
preprocessing10
word2vec10
wordcloud10
tripadvisor10
text-summarization10
machine-learning10
stopwords10
pyspark10
text-classification10
rouge10
wordcount10
natural-language-processing10
text-mining10
logistic-regression10
Programming languages (3)
Github contributions (5)
kavgan/nlp-in-practice
Jan 2018 - Dec 2020
Starter code to solve real world text data problems. Includes: Gensim Word2Vec, phrase embeddings, Text Classification with Logistic Regression, word count with pyspark, simple text preprocessing, pre-trained embeddings and more.
Contributions:75 commits, 7 PRs, 100 pushes in 2 years 10 months
gensimlogistic-regressionpreprocessingpysparktext-classification
kavgan/OpinRank
Feb 2017 - Jan 2018
OpinRank Dataset. Dataset containing user reviews for entities namely cars and hotels. Full reviews from Tripadvisor (~259,000 reviews) and Edmunds (~42,230 reviews)
Contributions:1 release, 9 commits, 2 PRs in 11 months
tripadvisoropinionsdatasetentity-rankinguser-reviews
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