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AboutMy 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 International Max Planck Research School for Intelligent Systems advised by Matthias Bethge and Mackenzie Mathis at EPFL. I am currently visiting EPFL in my second PhD year as part of the ELLIS PhD & PostDoc program.
Last fall, I worked as an Applied Science Intern at Amazon Web Services in Tübingen with Matthias Bethge, Bernhard Schölkopf and Peter Gehler on object-centric representation learning. Prior to starting my doctoral studies, 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.
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.
|Steffen Schneider, Jin Hwa Lee, Mackenzie Weygandt Mathis
|Learnable latent embeddings for joint behavioral and neural analysis|
|Steffen Schneider, Evgenia Rusak, Luisa Eck, Oliver Bringmann, Wieland Brendel, Matthias Bethge
Neural Information Processing Systems (NeurIPS), 2020
|Improving robustness against common corruptions by covariate shift adaptation|
|Steffen Schneider, Alexei Baevski, Ronan Collobert, Michael Auli
|wav2vec: Unsupervised Pre-training for Speech Recognition|