PhD Candidate, Computer Science
Institute for Machine Learning, ETH Zürich
Learning and Adaptive Systems Group
bunnec at inf.ethz.ch
I am a PhD student in Computer Science at the Eidgenössische Technische Hochschule (ETH) Zürich under the supervision of Andreas Krause and member of the Learning and Adaptive Systems Group. Before, I worked with Stefanie Jegelka as a Master student at the Massachusetts Institute of Technology (MIT). During my Master’s studies in Computational Biology, I also interned at IBM Research Zürich in the Computational Systems Biology Group.
Throughout my undergraduate and graduate studies I’ve been a Fellow of the German National Academic Foundation. For my Master’s studies I received the Excellence Scholarship of the ETH Foundation. I am a recipient of the ETH Medal.
- Learning Graph Models for Template-Free Retrosynthesis
Vignesh Ram Somnath, Charlotte Bunne, Connor W. Coley, Andreas Krause, Regina Barzilay
Best Paper Award and Contributed Talk at ICML Workshop on Graph Representation Learning and Beyond (GRL+), 2020.
[paper][workshop paper][code (coming soon)]
- Learning Generative Models across Incomparable Spaces
Charlotte Bunne, David Alvarez-Melis, Andreas Krause, Stefanie Jegelka
International Conference on Machine Learning (ICML), 2019.
Best Paper Award and Contributed Talk at NeurIPS Workshop on Relational Representation Learning (R2L), 2018.
- Studying Invariances of Trained Convolutional Neural Networks
Charlotte Bunne, Lukas Rahmann, Thomas Wolf
- Backbone circularization of Bacillus subtilis family 11 xylanase increases its thermostability and its resistance against aggregation
Max C. Waldhauer, Silvan N. Schmitz, Constantin Ahlmann-Eltze, Jan G. Gleixner, Carolin C. Schmelas, Anna G. Huhn, Charlotte Bunne, Magdalena Büscher, Max Horn, Nils Klughammer, Jakob Kreft, Elisabeth Schäfer, Philipp A. Bayer, Stephen G. Krämer, Julia Neugebauer, Pierre Wehler, Matthias P. Mayer, Roland Eils, Barbara Di Ventura
Molecular BioSystems, 2015.
Women in Data Science Conference (WiDS)
Women in Data Science (WiDS) is a one day technical conference aiming to inspire and educate data scientists worldwide, regardless of gender, and support the women in the field. I was an ambassador and part of the organisation team of the WiDS Conference in Zürich 2018.
I joined the iGEM Team Heidelberg 2014 of Heidelberg University. We developed a heat stable DNA-methyltransferase for a PCR 2.0 and designed a standardized intein-based mechanism for protein modifications (BBF RFC 105).