Using Discriminative Graphical Models for Insurance Recommender Systems. - Teja Kanchinadam; Maleeha Qazi; Joseph Bockhorst; Mary Y. Morell; Katie J. Meissner; Glenn Fung (ICMLA, 2018)

Discovering Temporal Patterns from Insurance Interaction Data. - Maleeha Qazi; Srinivas Tunuguntla; Peng Lee; Teja Kanchinadam; Glenn Fung; Neeraj Arora (AAAI, 2019)

Task-Optimized Word Embeddings for Text Classification Representations. - Sukrat Gupta; Teja Kanchinadam; Devin Conathan; Glenn Fung (Frontiers Appl. Math. Stat., 2019)

Rationale-based Human-in-the-Loop via Supervised Attention. - Teja Kanchinadam; Keith Westpfahl; Qian You; Glenn Fung (DaSH@KDD, 2020)

Designing and deploying insurance recommender systems using machine learning. - Maleeha Qazi; Kaya Tollas; Teja Kanchinadam; Joseph Bockhorst; Glenn Fung (WIREs Data Mining Knowl. Discov., 2020)

Graph Neural Networks to Predict Customer Satisfaction Following Interactions with a Corporate Call Center. - Teja Kanchinadam; Zihang Meng; Joseph Bockhorst; Vikas Singh; Glenn Fung (CoRR, 2021)

A Simple yet Brisk and Efficient Active Learning Platform for Text Classification. - Teja Kanchinadam; Qian You; Keith Westpfahl; James Kim; Siva Gunda; Sebastian Seith; Glenn Fung (CoRR, 2021)

Predicting Clinical Events via Graph Neural Networks. - Teja Kanchinadam; Shaheen Gauher (ICMLA, 2022)

Large Language Models Encode the Practice of Medicine. - Teja Kanchinadam; Shaheen Gauher (NAACL (Industry Track), 2024)