My goal is to build machine learning models capable of approaching the performance of biological brains in terms of flexibility to changes in tasks and environments. Drawing inspiration from adaptation behavior of biological systems, I study methods for domain adaptation and self-supervised learning and build machine learning tools for robust scientific inference in neuroscience and other life sciences.
I will start my own lab at Helmholtz Munich in January 2024. If you are looking for opportunities for a position as PhD student, postdoc, research engineer, research assistant, or an internship, Bachelor or Master’s thesis, have a look at my past work and student projects and ping me if you’re interested in working with me.
I pursue my doctoral studies at the Max Planck International Research School for Intelligent School and the Swiss Federal Institute of Technology Lausanne (EPFL) , advised by Matthias Bethge and Mackenzie Mathis in the ELLIS PhD & PostDoc program .
Links to stes.io (10)
cebra.aiLearnable latent embeddings for joint behavioural and neural analysis
Learnable latent embeddings for joint behavioural and neural analysis