Harsha Kokel

Harsha Kokel is a Research Scientist in Auto AI department at IBM Research.

Harsha’s research focuses on efficient knowledge-guided learning in structured, relational domains. She is also interested in sequential decision-making problems and, specifically, exploring the combination of planning and reinforcement learning. Her research has been published in the following conferences: AAAI, ICAPS, NeurIPS, and ACS. Her work has been presented at various workshops at AAAI, NeurIPS, IJCNN, ICAPS, and RLDM. She has reviewed papers for various journals, conferences, and workshops, including AAAI, IJCAI, SDM, and DMKD. She is a co-organizer for the PRL workshop at ICAPS 2023. She serves as an assistant electronic publishing editor for JAIR.

She received a master’s degree in CS from The University of Texas at Dallas in 2021. She was a research intern at IBM T. J. Watson Research Center in the summer of 2021 and 2022. In the summer of 2018, she was a Machine Learning intern at Turvo Inc, CA. Before pursuing graduate school, Harsha provided content management solutions as a software engineer for four years; three years at Publicis Sapient Consulting and a year at Amadeus Software Labs. She received her bachelor’s degree in Information and Communication Technology (ICT) from Dhirubhai Ambani Institute of ICT, Gandhinagar, India in 2012. During her bachelor’s study, she was a research assistant with Prof. Prasenjit Majumder, working on Sandhan, a cross-lingual search engine for Indian languages. She co-organized a Morpheme Extraction Task at Forum for Information Retrieval and Extraction (FIRE) in 2012 and 2013. She also conducted a tutorial on Information Retrieval at Microsoft Research, India in 2013 as a part of Pre-FIRE Workshop.

A complete list of Harsha's publications is available at https://harshakokel.com