T. Konstantin Rusch
Postdoctoral researcher at MIT.
My name is T. Konstantin Rusch and I’m a postdoctoral researcher at CSAIL, MIT working with Daniela Rus. Before that I finished a PhD in Machine Learning / Applied Mathematics at ETH Zurich, where I was lucky enough to get advised by Siddhartha Mishra. Moreover, during my PhD studies I had a second affiliation at the EECS Department at UC Berkeley, advised by Michael Mahoney.
My main research interest is in combining physics with machine learning.
Thereby, I focus on physics-inspired machine learning, which can be described
as leveraging structure from physical systems to construct novel machine
learning methods with better inductive biases. Additionally, I work
on combining methods from numerical analysis with machine learning
to solve problems in computational science and engineering.
Contact: tkrusch [at] mit.edu
news
| Feb, 2024 | Paper accepted at TMLR (joint work with Cambridge, DeepMind, Oxford, and MILA): How does over-squashing affect the power of GNNs? |
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| Sep, 2023 | Paper accepted at NeurIPS 2023 (joint work with Caltech): Neural Oscillators are Universal |
| Sep, 2023 | I successfully defended my PhD thesis. I am thankful to my advisor Siddhartha Mishra and my examiners Max Welling and Michael Mahoney. |
| Jan, 2023 | Paper accepted at ICLR 2023 (joint work with Berkeley and Oxford): Gradient Gating for Deep Multi-Rate Learning on Graphs |
| Dec, 2022 | We organize a workshop at ICLR 2023: Together with colleagues from Berkeley, Google, Twitter, ETH and Microsoft Research we are organizing a workshop on Physics for Machine Learning. We invite submissions on machine learning methods with a physics-based inductive bias. |