RJ Nieto
Hi, I’m Rey Joseph “RJ” Nieto.
I am a mathematician and university instructor with a First Class Honours BSc in Mathematics from the University of Bristol. I currently teach mathematics and information technology at Bulacan State University (BulSU) in the Philippines.
Alongside my teaching, I am undertaking structured independent study in dynamical systems, functional analysis, and measure theory and probability. This supports my continuing research in topology-informed computer vision, with potential applications in reliable biomedical and industrial imaging.
Over the longer term, I would like to study the mathematical behaviour of learning systems, including how they change over time and retain information.
Before returning to mathematics, I worked in journalism, broadcasting, public affairs, technical writing, and government communications.
Teaching
Course materials for general education subjects Mathematics in the Modern World and Living in the IT Era, which I teach at BulSU.
Research
My final-year project asked how reliably a computer can recover structural features from an image after blur, rotation, a change in resolution, or sensor noise. Using cubical persistent homology, I derived a computable stability bound and built a parallelised Python pipeline to study how simulated acquisition errors can affect measurements derived from retinal images.
I am now returning to a question left open by that project: whether the effects of sampling and interpolation on a pixel grid can be described more precisely than the conservative general bound used in the thesis. I am also examining whether the contrasting responses of topological and geometric measurements can help distinguish different degradation signatures. This is ongoing research; I am not assuming in advance that either question will yield a new theorem.
Professional Background
My earlier career spans journalism, broadcasting, public affairs, government communications, and digital publishing.