CV
A high-level overview of experience, education, and selected academic activity.
Summary
I work at the intersection of data science, machine learning, and systems. My background combines mathematics, computer science, and computational neuroscience, with a focus on building reproducible analysis pipelines and practical tools.
Experience
- University of Strasbourg
Strasbourg, France · since 2024
Conduct research and development in data analysis, modeling, and simulation. Develop reproducible pipelines, perform network analysis, and design computational experiments across interdisciplinary projects. - University of Bonn
Bonn, Germany · 2020–2022
Designed and analyzed computational models, collaborated across disciplines, and contributed to peer-reviewed publications and conference presentations. - Frankfurt Institute for Advanced Studies
Frankfurt, Germany · 2018–2020
Developed mean-field models, conducted time-series analysis, and applied machine learning methods to complex systems research.
Education
- PhD — Computer Science — (2017)
KTH - Royal Institute of Technology, Stockholm, Sweden
PhD — Computational Neuroscience — (2017)
University of Freiburg, Freiburg, Germany - MSc — Mathematics (2010)
University of Bordeaux, Bordeaux, France
University of Padova, Padova, Italy - BSc — Mathematics (Physics minor) - (2004)
Debub University, Hawassa & Dilla, Ethiopia
Selected Conferences & Workshops
- Dynamic resilience to degenerationPoster
- Why resting state must be restlessly dynamic?Poster
- Degeneration on controllability and dynamicsSlides
- Basics on ML: supervised & unsupervised learningSlides
- Controllability of complex systems
- Data mining and modeling
- Dynamic networks and computations
- Computation in neurons and networks
Teachings and tutorials
- recent
- earlier