Mayowa Agbi is a distinguished Bioinformatician, Computational Scientist, and CApIC-ACE Scholar specializing in Cancer Genomics, Artificial Intelligence, and In-silico Pharmacology. He currently serves as a Bioinformatician at The GeneLab Bioscience, where he implements high-complexity clinical oncology pipelines, including Leukemia classification, pharmacogenomics, and onco-risk prediction, leveraging Oxford Nanopore Technologies (ONT). With over five years of multidisciplinary expertise, Mr. Agbi bridges advanced biological systems with engineering precision, a profile strengthened by an intensive two-year R&D residency in Mechatronics Engineering where he mastered embedded systems, automation, and Arduino (C++) programming.

His technical portfolio is marked by the full-cycle development of a biosensor-based immunosensor for Tuberculosis detection and the design of a 112kW solar farm system. At the intersection of deep learning and precision medicine, Mr. Agbi’s M.Sc. research involved designing a Deep Neural Network (DNN) architecture for Compound-Protein Interaction (CPI) prediction targeting prostate cancer biomarkers. He is a prolific researcher with several peer-reviewed publications and contributions to book chapters, covering high-impact areas such as machine learning for prostate cancer risk prediction in African ancestry and in-silico network pharmacology. His proficiency extends to Genome-Wide Association Studies (GWAS) and High-Throughput Analysis using Python, R, and Linux/Bash.

Mr. Agbi is a seasoned tutor, he has mentored senior researchers and professors in Computer-Aided Drug Design (CADD). He further utilizes Autodesk Inventor for high-fidelity mechanical design and device prototyping. Mr. Agbi holds an M.Sc. in Bioinformatics from Covenant University and a B.Sc. in Microbiology from Adekunle Ajasin University. His work is defined by a commitment to scientific rigor and the integration of diverse computational and engineering methodologies to drive global innovations in clinical diagnostics.