CV
Computational Neuroscientist and Data Scientist
A concise overview of my experience, education, and selected academic activity.
Summary
I work across computational neuroscience, data science, machine learning, and scientific computing. My background combines mathematics and computer science with experience building reproducible analyses, simulations, data pipelines, and practical research tools.
Work Experience
- University of Strasbourg
Data Scientist and Researcher
Strasbourg, France · since 2024Network neuroscience, spiking-network simulation, and laboratory computing - University of Bonn
Data Scientist and Researcher
Bonn, Germany · 2020–2022Machine learning on RNA data and reproducible transcriptomic pipelines - Frankfurt Institute for Advanced Studies
Data Scientist and Researcher
Frankfurt, Germany · 2018–2019Mean-field modelling of epilepsy in an AI- and ML-focused environment - University of Freiburg
Data Scientist and Researcher
Freiburg, Germany · 2012–2017Network controllability, observability, and neuronal modelling
Education
- PhD — Computer Science (2017)
KTH - Royal Institute of Technology, Stockholm, Sweden
PhD — Computational Neuroscience (2017)
University of Freiburg, Freiburg, Germany - Master's — Mathematics (2010)
University of Bordeaux, Bordeaux, France
University of Padova, Padova, Italy - Bachelor's — Mathematics (Physics minor)
Debub University, Hawassa & Dilla, Ethiopia
Selected Conferences & Workshops
- CNS26
- OHBM26
- dFC correlates with cognitive resiliencePoster
- BrainNet
- Structural control of SNN degenerationSlides
More (earlier conferences)
- Activity resilience to degenerationPoster
- Why must resting state be restlessly dynamic?Poster
- Degeneration on controllability and dynamicsSlides
- Relevance of topology on SNNsSlides
- Basics on ML: supervised & unsupervised learningSlides
- Controllability of complex systems
- Data mining and modeling
- Dynamic networks and computations
- Computation in neurons and networks
Teaching and Tutorials
- Recent
- Earlier