Justin graduated from the Honors College and has participated in several research activities, including the REU program at Johns Hopkins University during the summer of 2023. He is now working in the application of machine learning to understand and predict the overall effect of mixtures of antioxidants. Outcomes of this project can be applied into many different fields such as pharmaceuticals and aging.
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Publications with our lab
Machine Learning-Based Inference of Oxidative Stability of Vegetable Oils
Emmanuel Dike, Lucas Ayres, Justin Furgala, Jorge Barroso, Daniel Whitehead, and Carlos D. Garcia
Journal of Food Composition and Analysis 153 (2026) 109135
Authors acknowledge the support from the Open Access Publishing Fund. This paper also provides access to an oxidation predictor: https://github.com/uAC-Lab/Oxidative_stability
Deciphering Antioxidant Interactions via Data Mining and RDKit
Lucas B. Ayres, Justin T. Furgala, and Carlos D. Garcia
Scientific Reports 15 (2025) 670
Authors acknowledge the support from the Open Access Publishing Fund