Resume
Academic Achievements
- Keynote speaker at the ICLR Neural Compression workshop in 2021; successfully defended PhD thesis in 2020; invited talk on automation boundaries at Brave New World conference in 2018; contributed talk on AI influence at 34c3 (Chaos Communication Congress) in 2017; contributed talk on Bayesian compression at MILA/CIFAR Deep Learning and Reinforcement Learning Summer School in 2017; tutorial on deep learning for the arts at Electromagnetic Field Festival in 2016; 4-week project on neural style transfer for music in 2016.
Research Experience
- Research scientist (s/h) at FAIR NY; actively collaborating with researchers from the Vector Institute and the University of Amsterdam.
Education
- PhD under the supervision of Prof. Max Welling; worked at the Austrian Research Institute for AI, Intelligent Music Processing and Machine Learning Group led by Prof. Gerhard Widmer; studied Physics and Numerical Simulations in Leipzig and Amsterdam.
Background
- Main research focus: intersection of information theory and probabilistic machine learning / deep learning. Actively collaborating with researchers from the Vector Institute and the University of Amsterdam.
Miscellany
- Projects include Bunker Streams, Save your Soul, Woodwork, Lügenpresse, Hebocon, Goethe on my Mind, Lumière, The prank call archive, Futuristic Farming, Haunted Farm.