Website: https://sites.google.com/view/ryomoore/home

I obtained my doctoral degree in mathematics from the University of North Carolina at Chapel Hill (USA) under the supervision of Prof. Idris Assani. Since then, I have conducted postdoctoral research at Pontificia Universidad Católica de Chile and at Southern University of Science and Technology (China).

My research has focused on ergodic theory, a branch of dynamical systems that studies the statistical behavior of chaotic systems. I have worked on several topics in ergodic theory, including Wiener–Wintner systems, nonconventional ergodic averages, multifractal analysis, and partially hyperbolic diffeomorphisms.

Currently, I am interested in analyzing mathematical propervies of various information measures—such as entropy, divergence, and mutual information—drawing on my background in functional analysis, measure theory, and probability.

I am an applied mathematician with over a decade of experience in mathematical physiology and systems biology. I specialise in modelling complex biological processes, including calcium signalling, cellular electrophysiology, and cancer cell metabolism. My work includes four and a half years at the Institute of Metabolism and Systems Research at the University of Birmingham, England, where I focused on modelling cancer biology. Currently, I am pursuing a theoretical approach to cellular metabolism, aiming to develop a fundamental theory to improve model accuracy and provide deeper insights for oncometabolism.

Selected research: 

[1] Vera-Sigüenza, Elías, et al. "A mathematical model of fluid transport in an accurate reconstruction of parotid acinar cells." Bulletin of mathematical biology 81 (2019): 699-721.

[2] Vera-Sigüenza, Elías, et al. "Pyruvate from bone marrow mesenchymal stem cells supports myeloma redox homeostasis and anabolism." bioRxiv (2024): 2024-08.

[3] Vera-Sigüenza, Elías, et al. "A Mathematical Exploration of SDH-b Loss in Chromaffin Cells." Bulletin of Mathematical Biology 87.4 (2025): 1-36.

Ph.D. 2020 (University of Auckland New Zealand)

I am a mathematician interested in Markov processes and their applications in statistics and probability. In my doctoral work, I constructed non-diffusive extensions of the Wright-Fisher process using transformations of time and space and proved that these processes had desirable and interesting properties such as stochastic duality and the admission of exact sampling schemes. I have also applied machine learning and Bayesian nonparametric to cluster cases of crimes by suspect in a dataset from the UK's national crime agency. I am now at the Okinawa Institute of Science & Technology where I am working on proving tighter bounds for mixing times and convergence rates of Markov processes. We take an approach based on information theory, spectral theory, functional analysis and measure theory and the results have potential applications to hypothesis testing.

PhD 2024 University of Warwick (UK)

I got my Master degree of Physics from Sharif University of Technology, where I worked on Complex Systems and Stochastic processes with applications in Biology and Economy. After a research internship program at OIST, I am studying as a PhD student. In particular, I am interested in Stochasticity, Non-equilibrium Physics, Information Theory, and Manifolds. Beyond calculations, I enjoy philosophy, games, and arts.

I am a Computer Scientist. I received my Master’s degree in Computer Science from the University of Salerno, Italy, in 2022, and I am currently pursuing a Ph.D. there under the supervision of Prof. Ugo Vaccaro. 

My research interests include Information Theory, Data Structures, and Search Algorithms. 

Currently, my work focuses primarily on search procedures and on the construction and analysis of particular classes of binary prefix and/or alphabetic codes.

I am a master’s student in Machine Learning at MBZUAI, UAE, where I work on optimization for machine learning under the supervision of Dr. Samuel Horváth. Prior to this, I completed my undergraduate degree in Electrical Engineering at New York University Abu Dhabi. At OIST, my internship focuses on understanding the performance of gradient-based optimization in variational (Bayesian) inference, and on characterizing its convergence rate through the study of the underlying geometry. 

I am a third-year PhD student at EPFL in the Laboratory for Information in Networked Systems (LINX). Previously, I was an algorithms researcher at Entropica Labs, a quantum computing startup in Singapore. Before that, I completed both my Bachelor’s and Master’s degree at EPFL.

I am fortunate to be co-advised by Prof. Michael Gastpar (EPFL) and Prof. Amedeo Esposito (OIST). My research interests span a variety of topics, including Information Theory, Probability Theory and Statistics.