معرفی
Naima Elosegui Borras is a Researcher at the Technical University of Berlin, affiliated with the Berlin Institute for the Foundations of Learning and Data (BIFOLD). Her interdisciplinary work bridges machine learning foundations and neuroscience, focusing on theoretical frameworks for neural computation.
Her educational background includes:
- MSc in Neural Systems and Computation (2023) from ETH Zürich and UZH Zürich (joint program)
- BSc in Neuroscience (Honours) (2020) from The University of Edinburgh
Her core research integrates Information Geometry and Statistical Physics to analyze learning dynamics in neural systems, with specific investigations into criticality in reservoir computing, hippocampal plasticity modeling, and neuromorphic vestibular system implementations. This NeuroAI-focused work employs probabilistic machine learning to uncover universal principles across biological and artificial networks.
Through BIFOLD, she contributes to foundational AI research while maintaining active open-source development on GitHub. Her 16 public repositories demonstrate technical proficiency in Jupyter Notebooks, Component Pascal, and neural network simulations, with recent contributions reflecting ongoing doctoral research activities.
No scientific awards or grants are documented in available sources. As a doctoral researcher, she has no formal advisees but collaborates through GitHub projects visible to the research community.
