Dr Akindele Onifade is an applied mathematician whose mathematical and computational biology research focuses on data analysis and mathematical modelling for medical, biological and environmental applications. His expertise ranges from modelling complex dynamical systems to handling and analysing experimental data. He has made scientific contributions to mathematical epidemiology, evoluationary game theory, rule-based epidemic modeling, modeling diffusion, delayed and instantaneous processes and their mathematical analysis while working on a wide range of problems in mathematical biology.
 
He held postdoctoral position in University of Florida, United States of America in 2022, and joined Vaccine Impact Modeling Consortium (VIMC) at Imperial College London, UK in 2023 as a researcher (still a member till now) after he secured research grant with the consortium (Founders: Bills and Melinda Gates, Gavi, and Wellcome Trust). His task was to provide high quality estimates of the public health impact of vaccination, to inform and improve decision making. He was appointed as an epidemiologist and mathematical modeller in rule-based epidemic modeling at the University of Southampton, United Kingdom in 2025. He is also a research fellow in epidemiological models in Bats (ecology and evolution) at the School of Life Sciences, University of Sussex, United Kingdom (since July 2026). He was awarded the Simons grants (International Mathematical Union Simons Fellowship and European Mathematical Society Simons Fellowship) in 2022.
 
In the last few years, He became increasingly interested in integrating statistical, mathematical and computational approaches to solve a wide range of problems in biology, medicine and ecology & evolution. Since 2021, he has been working on mathematical models for multi-drug therapies to treat malaria, designing the best therapeutic strategy to eliminate malaria. Currently, his research lies on the interface of data science, rule-based epidemic modeling, game theory, and computational mathematics. In his research, he interprets research data, develops mathematical systems based on statistical analysis, develops computational techniques and plans numerical simulations to verify hypotheses arising from laboratory experiment.