Evolutionary facial feature selection. - Aaron K. Baughman (GECCO (Companion), 2008)

Exploring an evolutionary medical analytic wallet. - Aaron K. Baughman; Mweene Monze; Christian Eggenberger; Peter Malkin; Neil Katz; Chris Dawson; Barry Graham (GECCO (Companion), 2009)

DeepQA Jeopardy! Gamification: A Machine-Learning Perspective. - Aaron K. Baughman; Wesley Chuang; Kevin R. Dixon; Zachary Benz; Justin Basilico (IEEE Trans. Comput. Intell. AI Games, 2014)

Disruptive Innovation: Large Scale Multimedia Data Mining. - Aaron K. Baughman; Jia-Yu Pan; Jiang John Gao; Valery A. Petrushin (Multimedia Data Mining and Analytics, 2015)

Large-Scale Biometric Multimedia Processing. - Stefan van der Stockt; Aaron K. Baughman; Michael Perlitz (Multimedia Data Mining and Analytics, 2015)

Predictive Cloud Computing with Big Data: Professional Golf and Tennis Forecasting [Application Notes]. - Aaron K. Baughman; Richard J. Bogdany; Cameron McAvoy; Richard A. Locke; Brian O'Connell; Clay Upton (IEEE Comput. Intell. Mag., 2015)

IBM Predicts Cloud Computing Demand for Sports Tournaments. - Aaron K. Baughman; Richard J. Bogdany; Benjie Harrison; Brian O'Connell; Herbert D. Pearthree; Brandon Frankel; Cameron McAvoy; Sandy Sun; Clay Upton (Interfaces, 2016)

Using language models for improving speech recognition for U.S. Open Tennis Championships. - Aaron K. Baughman; Steven Hammer; David Provan (IBM J. Res. Dev., 2017)

Detection of Tennis Events from Acoustic Data. - Aaron K. Baughman; Eduardo Morales; Gary Reiss; Nancy Greco; Stephen Hammer; Shiqiang Wang 001 (MMSports@MM, 2019)

Large Scale Diverse Combinatorial Optimization: ESPN Fantasy Football Player Trades. - Aaron K. Baughman; Daniel Bohm; Micah Forster; Eduardo Morales; Jeff Powell; Shaun McPartlin; Raja Hebbar; Kavitha Yogaraj; Yoshika Chhabra; Sudeep Ghosh; Rukhsan Ul Haq; Arjun Kashyap (CoRR, 2021)

Deep Artificial Intelligence for Fantasy Football Language Understanding. - Aaron K. Baughman; Micah Forester; Jeff Powell; Eduardo Morales; Shaun McPartlin; Daniel Bohm (CoRR, 2021)

Study of Feature Importance for Quantum Machine Learning Models. - Aaron K. Baughman; Kavitha Yogaraj; Raja Hebbar; Sudeep Ghosh; Rukhsan Ul Haq; Yoshika Chhabra (CoRR, 2022)

Large Scale Generative AI Text Applied to Sports and Music. - Aaron K. Baughman; Eduardo Morales; Rahul Agarwal; Gozde Akay; Rogério Feris; Tony Johnson; Stephen Hammer; Leonid Karlinsky (KDD, 2024)

Automated Meta Prompt Engineering for Alignment with the Theory of Mind. - Aaron K. Baughman; Rahul Agarwal; Eduardo Morales; Gozde Akay (CoRR, 2025)