Advisor: Prof. Akwum Onwunta. Dissertation: PDEs and Machine Learning with Applications in Medical Imaging.
About
I'm a fourth-year PhD candidate in Industrial and Systems Engineering (Lehigh ISE) at Lehigh University, advised by Professor Akwum Onwunta. My dissertation, PDEs and Machine Learning with Applications in Imaging, develops optimization and deep learning methods for inverse problems and imaging.
Before Lehigh, I earned a Master's degree in Mathematical Sciences from the African Institute for Mathematical Sciences (AIMS) in Rwanda, and a Bachelor's degree in Pure and Applied Mathematics from Ladoke Akintola University of Technology (LAUTECH) in Ogbomoso, Nigeria.
I served as President of the Lehigh INFORMS Student Chapter for 2025–2026, and as Vice President and Treasurer of the Lehigh University Graduate Association of Nigerian Students.
Education
Ph.D. in Industrial and Systems Engineering
M.Sc. in Mathematical Sciences
Advisor: Prof. Dedunje Biatat V.A. Thesis: Artificial Neural Networks Under Constraint.
B.Tech. in Pure and Applied Mathematics
Grade: 4.52/5.0. First Class Honors.
Research Interests
Mathematical optimization · Scientific computing · Machine learning · Inverse problems · Medical imaging · Partial differential equations
Selected Publications
Deep learning methods for inverse problems using connections between proximal operators and Hamilton–Jacobi equations
Momentum-based minimization of the Ginzburg–Landau functional on Euclidean spaces and graphs
Ongoing Projects
Learned Proximal Networks
Learning proximal operators directly with input-convex neural networks, and using the learned prior for reconstruction in inverse problems.
Learned Proximal Networks for High-Dimensional Hamilton–Jacobi PDEs
Learning a convex potential whose gradient is the proximal operator, then recovering the prior without per-query inversion.