I recently joined Alex Pouget‘s lab in Geneva, Switzerland. From 2014 to 2017, I was a postdoc in Wei Ji Ma‘s lab at NYU, NY, USA. I obtained my PhD at the Doctoral Training Centre for computational neuroscience based in Edinburgh, UK, under the supervision of Sethu Vijayakumar and Daniel Wolpert. I spent several months of my PhD at the Computational and Biological Learning Lab in Cambridge, UK.
My research focuses on how the brain combines different sources of perceptual information when there are multiple possible underlying explanations (causal inference). I also study how the brain represents and computes with uncertainty. I explore these question with mathematical modelling, computational analysis and human psychophysics.
Recently, I have been developing machine learning methods to facilitate the life of a modeler, using Bayesian optimization and Monte Carlo techniques for the purpose of model evaluation. Check out my package Bayesian adaptive direct search for model fitting.
I like to explore complex settings with a minimal set of assumptions. Prior to my entrance in neuroscience, I have been briefly working on cellular automata. I did my physics MSc thesis in statistical mechanics and cosmology, hiding my interest in the foundations of quantum mechanics, because in a physicist it used to be interpreted as a sign of senility. In the past, I worked for several years as editor and consultant for science and science-fiction.