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 and putting them to the test through collaboration with experimentalists. I have a strong mathematical background and hands-on experience with advanced statistical physics and computer science methods, applied to analyze problems and experimental results from neuroscience and machine learning.

Research Interests

• Population coding and manifold representation of sensory information; the transformation of manifold representations through biological learning.
• Memory encoding with biological learning, the dynamics of memory retrieval, and memory consolidation; their relation to hippocampal phenomenology (theta modulation, sharp wave ripples, behavioral timescale synaptic plasticity, sleep stages, etc.).
• The interplay and functional role of reward-modulated plasticity, homeostasis plasticity, Hebbian, and anti-Hebbian plasticity. Biological alternatives to error backpropagation, or biological implementation of gradient descent.
• Neural implementation of world-models, namely inference of state changes in the environment, and their possible contribution to predictive sensory and control schemes.

PhD Thesis
Memory recall project
Random Matrix Gallery