About me
Driven by a relentless curiosity about the human brain and armed with a diverse background in computer sciences & electrical engineering, my academic journey has been guided by a fascination for interdisciplinary applications of computer science. During my undergraduate studies, I found my passion for computational neuroscience, leading 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 challenges and enhancing human well-being.
Research interests:
Theory:
- Algorithms
- Graph theory
- Network science
- Artificial intelligence
- Probabilistic programming
Application:
- Network neuroscience
- Whole-brain connectomics
- High-resolution Connectomics
- Normative brain connectivity
- Brain-Behavior investigations
- Computational neuropsychiatry