Fardina Alam

Fardina Alam is a computer scientist and data science educator whose work spans machine learning, computational biology, generative AI, and responsible AI in education. At the University of Maryland, her academic work bridges the Department of Computer Science and the Science Academy in CMNS, with a focus on interdisciplinary data science education.

Alam earned her Ph.D. in Computer Science from George Mason University, where her doctoral research focused on deep latent-variable models for learning representations of protein tertiary structures. Her research develops generative and representation-learning methods for modeling protein structure, characterizing structural relationships, and generating biologically plausible conformations. Her broader interests include structural bioinformatics, deep generative modeling, and AI-driven scientific discovery.

Her work also examines the integration of generative AI into data science and computing education, particularly its implications for student learning, AI literacy, academic integrity, and responsible adoption. In 2025 and 2026, she served as Administrative and Academic Lead for the Break Through Tech Instructional Hub at UMD, contributing to AI instruction and coordinating the academic implementation of Cornell Tech’s Break Through Tech AI program at UMD.