Photo of Dr Gabriel Berzunza Ojeda

Dr Gabriel Berzunza Ojeda

Lecturer Mathematical Sciences

Research

Research Overview

My general research interests concern probability theory and stochastic processes, especially branching structures. My work also intersects with a wide variety of (applied) probability models arising in coalescent theory, fragmentation theory, Lévy processes, percolation, random trees, random walks and stochastic population models. Often these research interests are motivated by applications to other scientific areas such as biology, computer science or physics.

Stochastic Processes in Combinatorial Structures

My interests lie in the application of stochastic process methods to study models of (random) discrete structures that include trees, and more generally, graphs. Trees are an important object in graph theory and combinatorics as well as a basic object for data structures, algorithms in computer science (these includes uniform random recursive trees, scale-free random trees, binary search trees), and graphical representations for genealogical data in biology (for example, Galton-Watson trees). Recently, I have been particularly interested in topics related to percolation, reduction procedures and scaling limits of (random) trees.

Branching processes and interacting particle systems

My aim is to understand fundamental probability models and stochastic processes that describe the evolution of population models forward and backwards in time. For example, branching processes can roughly be thought of as models for populations of ‘animals’ which breed, die, maybe move around in space and interact with other ‘animals’. In particular, I am interested in questions concerning the long-term behaviour (extinction, survival, stationarity, etc) of these population models as well as in the description of their genealogy.

Miscellaneous topics

In general, I am always interested in finding new connections between my main research interests and other areas of probability theory, stochastic processes and even outside of mathematics, where one can apply similar models and probabilistic tools.

Research Group Membership