John Olalere Ogunlola

John Olalere Ogunlola is a Nigerian Artificial Intelligence researcher applying machine learning to aviation safety, cybersecurity, and AI-enabled drug discovery.

In 2026, Ogunlola expanded his research footprint with several award-winning and internationally presented publications. His work in aviation focuses on predictive analytics to enhance safety and efficiency, including "Intelligent Air Route Optimisation for UK Domestic Aviation" (DOI: 10.1109/ICCSDFAI70505.2026.11647994) and "Algorithmic Aircraft Accident Analysis" (DOI: 10.1109/ICCSDFAI70505.2026.11647928). He also co-authored "AI-Driven Flight Delay Prediction," presented at the 9th International Conference on Networking, Intelligent Systems & Security (NISS26) in Málaga, Spain, to advance proactive air traffic management.

Beyond aviation, Ogunlola contributed to IoT cybersecurity as part of a six-member Nigerian team that won the Best Paper Award at ACSCON-2026 in Bengaluru, India. Their research, "Federated Learning with Differential Privacy for Adversarial Robustness in IoT Cybersecurity" (DOI: 10.17577/IJERTCONV14IS060160), combines federated learning and differential privacy to defend against data poisoning attacks.

His interdisciplinary efforts also extend to healthcare, co-authoring "Evaluating Artificial Intelligence for Predicting and Interpreting Molecular Toxicity from Chemical Structures" (DOI: 10.1109/ICCSDFAI70505.2026.11648038), which secured 3rd Place at ICCSDFAI 2026 in Istanbul, Türkiye, for using explainable AI to improve early drug screening.

Through these contributions, Ogunlola continues to develop responsible, practical AI solutions that translate academic innovation into high-impact, real-world value across critical global sectors.