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• Institute of Artificial Intelligence (IAI)
• Digital Future Institute

• Lawal, A., Yang, Y., Baisa, N. L., & He, H. (2026). Reservoir permeability prediction using Integrated Grey-Fuzzy Gaussian Process Regression: A comprehensive framework for uncertainty quantification and interpretability. Engineering Applications of Artificial Intelligence, 177, 114777.
• Pasbanigoloojeh, R., Lawal, A. [Asmau], Daneshvar, B., & Lawal, A. (2025). Anisotropic Perlin Noise: Directional and Radial Pattern Generation for Texture Synthesis. In 2025 IEEE 17th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 1284–1288). IEEE.
• Bilbis, A. L., Daneshvar, B., Lawal, A., & Pasbanigoloojeh, R. (2025). DCT vs. FFT Frequency Features for Compression-Robust Deepfake Detection: A Systematic Comparison. In 2025 IEEE 17th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 1681–1685). IEEE.
• Lawal, A., Daneshvar, B., Bilbis, A. L., & Pasbanigoloojeh, R. (2025). Grey-Fuzzy Enhanced Gaussian Process Regression for Concrete Strength Prediction and Reliability Assessment. In 2025 IEEE 17th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 2208–2212). IEEE.
• Lawal, A., Yang, Y., He, H., & Baisa, N. L. (2024). Machine Learning in Oil and Gas Exploration — A Review. IEEE Access.
• Lawal, A., Yang, Y., Baisa, N. L., & He, H. (2024). A novel framework for reservoir permeability prediction using GPR with grey relational grades and uncertainty quantification. In 2024 7th International Conference on Pattern Recognition and Artificial Intelligence (PRAI) (pp. 404–411). IEEE.
• Lawal, A., Yang, Y., Baisa, N. L., & He, H. (2024). A novel fuzzy logic framework for model reliability evaluation in permeability prediction using GPR. In 2024 IEEE 16th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 1196–1207). IEEE.
• Lawal, A., Yang, Y., Baisa, N. L., & He, H. (2024). Uncertainty-aware reservoir permeability prediction using Gaussian Processes Regression and NMR measurements. In Proceedings of the 2024 8th International Conference on Advances in Artificial Intelligence (pp. 54–60).
• Lawal, A., Yerima, S. Y., Olago, D. O., Amingo, P. O., Kariuki, C. W., Wang'ombe, W., Olaka, L., Obiero, L., & Wandiga, S. O. (2023). Evaluating machine learning models for rainfall prediction: A case study of Nyando in Kenya. In 2023 IEEE 15th International Conference on Computational Intelligence and Communication Networks (CICN) (pp. 264–271). IEEE.

• Trustworthy and Explainable AI
• AI for Cyber Security
• Uncertainty Quantification in Machine Learning
• Machine Learning for Engineering and the Geosciences
• AI for Climate and Environmental Applications

• Computer Science
• Software Engineering
• Data Analytics
• Applied Computing

PhD - Computer Science (Machine Learning)
Msc - Software Engineering
Bsc - Mathematics

Fellow of Higher Education Academy (FHEA)

ADRELO Project at Âéw¶¹´«Ã½, under Belmont Forum (Research Fellow)

IEEE CICN 2023, IEEE CICN 2024, PRAI 2024, ICAAI 2024, IEEE CICN 2025

0009-0004-4397-3045