I'm fascinated by how the mind takes in information from our senses, specifically 2D retinal images, and extracts only what it needs to solve the task at hand. How it does so much with so little energy.
At the moment, I study how we represent this information and how we can apply some of the same principles in our perception algorithms.
Application scenarios cover the fields of human action prediction, intuitive physics, planning and other related prediction tasks.
Currently, I'm pursuing my Ph.D in joint supervision by prof. Katerina Fragkiadaki at the Machine Learning Department at CMU in Pittsburgh and prof. José Santos-Victor at the Institute for Systems and Robotics in Lisbon.
"What I cannot create, I do not understand." - R. Feynman
Computer Vision, Disentangled Representation Learning, Topological Representations, Self-Supervised Learning, Generative Models, Bayesian Learning, Language Grounding, Cognitive Robotics, Robotics