Kavita Annapoorani Ganesan (also referred to as Kavita Gnesan) is a Malaysian-born author, data scientist, and AI consultant active from 2012 to the present, known for her research in the fields of artificial intelligence, machine learning, and natural language processing.^[1] She earned an M.S. in Computer Science from the University of Southern California and a Ph.D. in Computer Science from the University of Illinois Urbana-Champaign. She authored the book The Business Case for AI, founded the company Opinosis Analytics, maintains the website www.kavita-ganesan.com, and has had her works cited over 1,500 times according to Google Scholar.^[4,8,9,2]

Ganesan worked as a scientist for the software development platform GitHub.^[5,4] In 2017, she brought the first machine learning (ML) pipeline to GitHub with the launch of GitHub Topics.^[6] While working at GitHub, Ganesan founded the Utah-based AI and machine learning company Opinosis Analytics.^[4,8,9] In 2021, Ganesan was nominated for the Rising Star Award at VentureBeats Women in AI Awards.^[10]

In 2022, Ganesan published the book The Business Case for AI: A Leader’s Guide to AI Strategies, Best Practices & Real-World Applications.^[11] In 2023, her book The Business Case for AI was the runner up in the San Francisco Book Festival’s Technology category and also won Gold Medal in Business Life Category in the 2023 Global Book Awards.^[13,12] The book also won an award in the 2nd Quarter 2023 Firebird Book Awards.^[14]

Ganesan's background is in natural language processing (NLP), search technologies, and machine learning, and her work has been cited in over 1500 papers.^[15,1,16] She has researched applications for artificial intelligence in fields such as knowledge management and search engines.^[17,14] In addition to her research on artificial intelligence, Ganesan has also researched topics such as record linkage, data analysis for clinical notes and written opinions, and data mining for e-commerce.^[22,19,20] Furthermore, Ganesan holds patents for software systems and methods used for visualizing reputation ratings, activity-based recommendations, and search clustering.^[25,23,24]

K. Ganesan's publications include the 2022 book "The Business Case for AI: A Leader's Guide to AI Strategies, Best Practices & Real-World Applications", published in the United States by Opinosis Analytics Publishing (ISBN 9781544528717). In August 2010, Ganesan, C. Zhai, and J. Han presented "Opinosis: A graph based approach to abstractive summarization of highly redundant opinions" in the Proceedings of the 23rd international conference on computational linguistics (Coling 2010, pp. 340–348). Ganesan and Zhai later published the paper "Opinion-based entity ranking" in Information Retrieval in 2012 (Vol. 15, pp. 116–150). In April 2012, Ganesan, Zhai, and E. Viegas published "Micropinion generation: an unsupervised approach to generating ultra-concise summaries of opinions" in the Proceedings of the 21st International Conference on World Wide Web (pp. 869–878). Additionally, Ganesan authored the 2018 arXiv preprint "Rouge 2.0: Updated and improved measures for evaluation of summarization tasks" (arXiv:1803.01937).