Research
Complex Systems, Statistical Physics, Machine Learning
Interests
My research focuses on complex systems. I am particularly passionate about researching society, technological infrastructures, and their interaction. However, my scientific interests are broader, as I deliberately develop and use mathematical models and algorithms that can be transferred across application areas. Ultimately, my goal is to produce principled research that informs decision-making and contributes to a better world.
More specifically, I am now working on power grids and statistical physics for the UKRI project Stability of the South African Power Grid: A data-driven statistical physics approach and, also within the engineering domain, I have studied urban mobility. Alongside application-oriented research, I am fond of fundamental research topics related to complex systems, such as Bayesian inference and generative models. While in industry, I worked on explainable machine learning for scientific discovery.
I like technical work involving mathematical modeling, but I believe observations should always fuel research questions. Therefore, I put data first, whether for training machine learning models, analyzing and interpreting their hidden patterns, or formulating optimization problems that I then enjoy solving. On top of this, I also have a keen interest in clean and efficient code.
For updated information and material such as publications, slides and codes, see:
aleable.github.io
