About me

I am an aspiring scientist in the field of computational neuroscience, interested in developing theories on the dynamics of learning and memory in the brain, with possible applications to machine learning. I have strong mathematical background and hands-on experience with advanced methods from statistical physics and computer science, applied to analyze problems and experimental results from neuroscience and machine learning.

Research Interests

• Population coding and manifold representation of sensory information.
• Biological learning and its relation to memory encoding and usage.
• Neural implementation of world-models and its application to reinforcement learning.
• Biological alternatives to error backpropagation, implementation of gradient descent.
• Predictive coding and its relation to learning and memory.

PhD Thesis