I am a first year master student in the Graduate Training Centre of Neuroscience at the Eberhard Karls University of Tübingen, Germany.

I am deeply fascinated by Machine learning and Deep Learning and the underlying high dimensional mathematical modeling that enables it. The level of generalization and adaptability in deep learning architectures needs to attain a certain level before they can be used as decision-making models instead of prediction models. The introduction of simple perturbations on data distributions can render the best of the deep learning models ineffective. This raises concerns on the wide variety of learning theories that form the core of modern machine and deep learning architectures. My long term vision is to revisit the fundamental theory of deep learning to understand when and why they fail.