My mission is to build socially beneficial, interpretable and theoretically substantiated machine learning systems.
I am a member of Pembroke College, funded by the Cambridge-Tübingen PhD fellowship with generous donations from Microsoft.
My background is in Physics and Mathematics. I was fortunate to spend time at Harvard, working with Paul Chesler and Wilke van der Schee, as well as at Stanford, working with William East and Tom Abel.
- 05/2018: Two papers accepted at ICML 2018
- 04/2018: I will join Amazon for a summer internship
- 11/2017: "Learning Independent Causal Mechanisms" accepted at NIPS workshop on Learning Disentangled Representations
- 11/2017: "ConvWave" accepted at NIPS workshop on Deep Learning for Physical Sciences
- 09/2017: "Avoiding Discrimination Through Causal Reasoning" accepted at NIPS 2017
Selected Publications & Projects
- Albert Einstein Institute (Potsdam-Golm, Germany): Machine Learning powered CBC Search
- Alan Turing Institute (London, UK): Fairness in Machine Learning
- Max Planck Institute for Software Systems (Saarbrücken, Germany): Fairness in Machine Learning
- Stanford University (CA, USA): Searching for Gravitational Waves with Machine Learning
- University of Regensburg (Regensburg, Germany): Fully Convolutional Networks for Gravitational Wave Searches
- Microsoft Research (Cambridge, UK): Learning Independent Causal Mechanisms
- I organized the first external CamTue workshop in November 2017 on Mallorca.
- I thoroughly enjoy teaching, was active in the Schülerzirkel Mathematik in Regensburg, a TA for many courses in Math, Physics, and CS, lectured a semi-annual course on Computer- and Microcontroller-Technology, and co-lectured the course Green-IT at the summer academy 2016 in Leysin, organized by the German Academic Scholarship Foundation.
- I like building things, for example: Babyzen - A flexible sensor BoosterPack [codeproject article][short video][report (pdf)] or some things here.