RESEARCH
Dr. Hafeez is broadly interested in uncovering the underlying organizational principles of living systems by exploring the intersection of systems biology, computational neuroscience, and algorithmic information theory. His current work focuses on investigating simplicity bias in biological systems, applying computational techniques to decode how complexity in biological models—such as those describing cell cycles, signaling pathways, and gene regulatory systems—may conceal universal patterns of functional simplicity. He is particularly intrigued by the algorithmic architecture of biological models, using tools like Kolmogorov complexity and Block Decomposition Method to quantify information content and derive meaningful insights into evolutionary design mechanisms.

BIOGRAPHY
Hafeez Alani Agboola is a Postdoctoral Research Fellow at King Abdullah University of Science and Technology (KAUST), Saudi Arabia. He earned his Ph.D. in Chemical Engineering—with a strong focus on Biomedical applications—from the University of Lagos, Nigeria, where he developed computational models for epileptic seizure prediction based on EEG signal dynamics and unsupervised learning. He has presented his research at international conferences and authored publications on EEG-based seizure detection as well as wavelet scattering approaches for glaucoma detection. His work is characterized by a multidisciplinary approach that bridges engineering, biology, and data science. Prior to joining KAUST, he served as an Assistant Professor at Afe Babalola University, Ado-Ekiti, Nigeria and previously taught STEM subjects at high school level.