Robin Schneider
Machine learning engineer and former theoretical physicist.
ASML Building 3
De Run 6503
5504 DR Veldhoven
I am currently working at ASML as a machine learning engineer. I’m part of modeling and inference group lead by Henk-Jan Smilde. As part of my work I leverage deep learning and techniques from computer vision to analyze images from the YieldStar. In addition I’m improving the whole MLops and data orchestration pipeline from acquiring and processing data to training and selecting the best ML models to finally deploying them.
Before that I was a PhD student at Uppsala University investigating heterotic compactifications on Calabi-Yau manifolds in Magdalena Larfors group. In my thesis I used techniques from machine learning to solve problems in string theory. For example, I found semi-realistic string compactifications with Actor-Critic agents from reinforcement learning. On the other hand, I employed deep convolutional neural nets to learn the cohomologies of Calabi-Yau manifolds and developed a tensorflow package to find solutions to the multi-objective optimisation problem of finding Ricci-flat metrics.
Before my time in Uppsala I completed my undergraduate degree in physics at the University of Münster, with an Erasmus year at Lund University. During my Master’s studies, I also participated in a one year research exchange with IPMU at the University of Tokyo, where I worked with Yuji Tachikawa.
Visit my GitHub profile to learn more about my latest projects and interests.
news
| Apr 30, 2023 | As of the beginning of this year I’m leading the technical competence in applied mathematics for parameter estimation. |
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| Sep 20, 2022 | The long version of our paper describing how-to model CY metrics with neural networks has been published at Machine Learning: Science and Technology. |
| Jun 1, 2022 | Today I had my first day at ASML joining the modeling and inference group. |
| May 21, 2022 | Yesterday I successfully defended my PhD thesis, which you can find here. Big thanks to my opponent Yang-Hui He, my supervisor Magdalena Larfors, and the grading committee. |
| Apr 29, 2022 | I’m happy to announce that I’ll be joining ASML as a ML engineer starting June 1. |
selected publications
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Learning Size and Shape of Calabi-Yau SpacesMachine Learning and the Physical Sciences, Workshop at 35th NeurIPS 2021