Balázs graduated with an MSc in Physics at the Eötvös Loránd University (ELTE) in Budapest specializing in particle physics.

He earned his PhD at the Lorentz Institute for Theoretical Physics (Leiden University). His research was on applying methods developed in high-energy physics to calculate properties of strongly correlated matter near quantum criticality.

He then worked in the financial industry as a Data Scientist and Quantitative Researcher. He was developing machine learning models (using mostly feedforward and recurrent neural network based supervised and reinforcement learning methods) for trading strategies using high-frequency orderbook data.

Balázs joined the Computational Systems Neuroscience Lab as a postdoctoral researcher at the end of 2020. He is currently working on hierarchical generative models and continual learning.”