PhD in Machine Learning, 2018
Delft University of Technology
MSc in Neuroscience, 2013
Intelligent behaviour fascinates me: how animals can efficiently process a flood of sensory signals and learn to survive. Nature has produced elegant solutions for information processing that I believe can help us tackle challenges in modern society. I’m passionate about taking what we know from how brains process information, to making intelligent machines.
My work in the lab focuses on deploying our agents to mobile robotics applications. I collaborate with industry to solve practical problems using free energy minimisation and I collaborate with researchers in control systems and robotics to study how neuro-biological processes of action and perception can be used for engineering.
Previously, I worked on the theoretical limitations of machine learning: I tried to understand when and why algorithms fail to generalize from a training sample to real-world settings. I designed robust estimators, which have been applied to image, signal, and natural language processing problems.