Dissecting Moneyball: Improving Classification Model Interpretability in Baseball Pitch Prediction. - Kevin Hickey; Lina Zhou; Jie Tao (HICSS, 2020)

Stabilizing Adversarial Training for Generative Networks. - Walter Gerych; Kevin Hickey; Thomas Hartvigsen; Luke Buquicchio; Abdulaziz Alajaji; Kavin Chandrasekaran; Hamid Mansoor; Emmanuel Agu; Elke A. Rundensteiner (IEEE Big Data, 2023)

Debiasing Pretrained Generative Models by Uniformly Sampling Semantic Attributes. - Walter Gerych; Kevin Hickey; Luke Buquicchio; Kavin Chandrasekaran; Abdulaziz Alajaji; Elke A. Rundensteiner; Emmanuel Agu (NeurIPS, 2023)

Making sense of the black-boxes: Toward interpretable text classification using deep learning models. - Jie Tao; Lina Zhou; Kevin Hickey (J. Assoc. Inf. Sci. Technol., 2023)

Screening Students for Stress Using Fitbit Data. - Rebecca Lopez; Avantika Shrestha; Kevin Hickey; Xingtong Guo; M. L. Tlachac; Shichao Liu; Elke A. Rundensteiner (IEEE Big Data, 2024)

Multi-task Learning with Pre-trained Language Models for Mental Illness Screening. - Avantika Shrestha; M. L. Tlachac; Ricardo Flores; Kevin Hickey; Elke A. Rundensteiner (IEEE Big Data, 2024)