About me

I am Arinze Lawrence Folarin, a Ph.D. candidate in Applied Mathematics at Ludwig-Maximilians-Universität (LMU) Munich. My research lies at the intersection of applied mathematics, signal processing, and machine learning, with a particular focus on low-rank models and optimization. I am currently working on the recovery of low-rank tensors via tractable algorithms, such as Riemannian Gradient Iteration and Tensor Iterative Hard Thresholding, with applications in high-dimensional data analysis.

Short Bio

I completed my undergraduate studies in Mathematics at the University of Ibadan, Nigeria. I then pursued a master's degree in Mathematical Sciences at the African Institute for Mathematical Sciences (AIMS), affiliated with Stellenbosch University, South Africa. Subsequently, I earned a second research-based Master’s degree in Applied Mathematics from the University of Cape Town, South Africa.

Currently, I am pursuing my Ph.D. at LMU Munich, where I work on low-rank tensor recovery using efficient and scalable algorithms.

Research Topics

Compressed Sensing and Signal Recovery, Low-Rank Matrix and Tensor Recovery, Riemannian Gradient Iteration, Tensor Iterative Hard Thresholding, Machine Learning (Reinforcement Learning Algorithms)