About me
My academic journey has been guided by a fascination for interdisciplinary applications of computer science aiming to solve real-world problems. Enthusiasm for computational neuroscience led me to pursue a PhD focused on computational models of brain connectivity. Now, I am on an exhilarating journey, exploring computational methods that offer a deeper understanding of the complexities of the human brain.
My primary interests lie in the dynamic interplay between complex networks, algorithms, and artificial intelligence within the context of computational neuroscience. As open science initiatives and the availability of neuroimaging datasets continue to expand, I see boundless opportunities to build powerful tools that unlock the secrets of the brain. I am determined to improve computational models that bridge brain connectivity with individual differences, shedding light on the factors that influence behavioral traits and psychopathologies.
Ultimately, my vision is to contribute to a future where computational neuroscience plays a pivotal role in transforming our understanding of the human brain and its intricate workings, ushering in new avenues for tackling neurological and psychiatric challenges with the overarching goal of enhancing mental well-being.
Research interests:
Theory:
- Algorithms
- Artificial intelligence
- Network science
- Probabilistic programming
Application:
- Network neuroscience
- Whole-brain connectomics
- High-resolution Connectomics
- Normative brain charting
- Brain-Behavior investigations
- Computational neuropsychiatry