Dr. Joshua Ologbonyo

Education

• Ph.D., Mathematics, The University of Alabama
• M.A., Mathematics, The University of Alabama
• M.Sc., Applied Mathematics with Climate Change Modelling, Heriot-Watt University, Scotland, UK
• M.Sc., Mathematical Sciences, African Institute for Mathematical Sciences (AIMS)
• B.Sc., Industrial Mathematics, Adekunle Ajasin University Akungba

Specialty

Applied and computational mathematics

Professional Interests

Dr. Ologbonyo’s research areas and interests include applied mathematics, statistical machine learning, computational biology, tensor and high-dimensional data analysis.

Recent Publications

• Ologbonyo, J., Budiardja, R. D., & Sidje, R. B. (2025, April). An Application of Machine Learning in Computational Astrophysics Using Pre-trained Models. In International Conference on Information Technology-New Generations (pp. 339-353). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-89063-5_29
• Ologbonyo, J., & Sidje, R. B. (2024, December). Predicting Next-Day Spread of Wildfires with Support Tensor Train Machine and Remote-Sensing Data. In International Conference on Computational Science and Computational Intelligence (pp. 67-81). Cham: Springer Nature Switzerland https://doi.org/10.1007/978-3-031-95130-5_6
• Ologbonyo, J., & Sidje, R. B. (2024, March). An Application of Support Vector Machine, Random Forest, and Related Machine Learning Algorithms on California Wildfire Data. In International Conference on Information Technology-New Generations (pp. 353-362). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-56599-1_46
• Ologbonyo, J., Adara, E. O., & Sidje, R. B. (2024, February). A Machine Learning Approach to Solving Biochemical Systems. In 2024 IEEE First International Conference on Artificial Intelligence for Medicine, Health and Care (AIMHC) (pp. 214-219). IEEE. https://doi.org/10.1109/AIMHC59811.2024.00046

Contact Dr. Joshua Ologbonyo

(478) 301-2815
ologbonyo_jj@mercer.edu
Office: Ware Hall, Room 216