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, multi-task and self-supervised learning.
I pursue my doctoral studies at the Max Planck International Research School for Intelligent Systems advised by Matthias Bethge in Tübingen. I am co-advised by Mackenzie Mathis at EPFL and will visit her lab at EPFL in my second PhD year as part of the ELLIS PhD & PostDoc program. In September 2020, I joined Amazon Web Services in Tübingen as an Applied Science Intern where I am advised by Matthias Bethge, Bernhard Schölkopf and Peter Gehler.
Previously, I worked on self-supervised representation learning for speech processing with Michael Auli, Alexei Baevski and Ronan Collobert at Facebook AI Research in Menlo Park, CA. For my Master’s thesis, I worked on Domain Adaptation in Brains and Machines with Matthias Bethge and Alexander Ecker at the Max Planck Institute for Intelligent Systems and University of Tübingen and Jakob Macke at TU Munich.
Aside from my research, I’m a strong supporter of exposing children to modern computer science topics early on during their school education. That’s why I co-founded and advised IT4Kids to teach CS in elementary school, KI macht Schule to teach AI and Machine Learning fundamentals in high school and helped organizing the German National Competition in AI for high school students. If you want to join our team and bring AI education to every school in Germany, don’t hesitate to reach out!
Likewise, if you are a student looking for opportunities for an internship, Bachelor or Master’s thesis, have a look at my past work and current student projects and ping me if you’re interested in working with me.
Incoming Visiting PhD Student (ELLIS), 2021
École polytechnique fédérale de Lausanne
Applied Science Intern, Fall 2020
Amazon Web Services, Tübingen
PhD Candidate in Machine Learning and Neuroscience, from 2019
Intl. Max Planck Graduate School for Intelligent Systems, Tübingen
AI Resident, Self-Supervised Learning for Speech Recognition, 2018 - 2019
Facebook AI Research, Menlo Park, CA
MSc in Neuroengineering, 2016 - 2018
Technical University of Munich
BSc in Electrical Engineering, Information Technology and Computer Engineering, 2013 - 2016
RWTH Aachen University
I am always looking for motivated students interested in joining me in the Bethge and/or Mathis lab. If you’re interested in working with me on topics around robustness, domain adaptation, reinforcement learning and self-supervised learning at the intersection of neuroscience and machine learning, please contact me at firstname.lastname@example.org.
I am currently working with:
In the past, I also worked with:
A full and up-to-date list is also available on Google Scholar.