Kazeem Adesina Dauda

Kazeem Adesina Dauda is a Research Fellow in the Department of Mathematics at the University of Bergen, affiliated with the Stochastic Biology Group—HyperEvol led by Prof. Iain Johnston. His research focuses on Bayesian statistical methods, genomic data analysis, and computational biology, particularly in modeling anti-microbial resistance (AMR) evolution and survival analysis for cancer genomics. He develops mathematical frameworks to predict disease progression pathways using machine learning and clustering techniques.

Key research areas include feature selection in high-dimensional data, flexible penalization in Bayesian survival models, and genome reduction dynamics in mitochondria and plastids. His work bridges statistical theory with applications in biomedical and evolutionary biology, emphasizing predictive modeling for AMR and disease outcomes.

Publications: Dr. Dauda has contributed to high-impact journals like Molecular Biology and Evolution and PLoS Computational Biology, focusing on AMR evolution modeling, Bayesian survival analysis, and genomic data clustering. Recent work includes HyperTraPS-CT algorithms for pathway inference and prediction.

Collaborations: Active in interdisciplinary teams at the University of Bergen and Warwick, collaborating on projects integrating computational tools with evolutionary and medical datasets.