Ayanda Huate, born and raised in Mozambique, earned a Bachelor of Arts in One Health and Mathematical Data Science from Westminster College, graduating summa cum laude as a Mastercard Foundation Scholar.
Ayanda’s research interests lie at the intersection of biomedical data science, artificial intelligence, and global health. She conducted her senior thesis on bias in machine learning models for lung cancer survival prediction. As an intern at Washington University in St. Louis, Ayanda worked with Dr. Zachary Abrams on machine learning models for integrative multi-omic analyses of Amyotrophic Lateral Sclerosis (ALS) data. Her project focused on identifying shared molecular signatures among patients to support more targeted and effective treatment approaches.
Ayanda speaks Portuguese, English, French, and Spanish, and enjoys learning endangered African languages. In her free time, she also loves cooking, hiking, a history or art museum hunt, and playing board games.