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个人简介
Starting as a trained graphic designer and audio engineer, I shifted my career interests and graduated in physics with a Doctor of Science (Dr. rer. nat.) in 2021. Following my passions, I focused my studies on computational physics, emphasizing deep learning and its applicability within physics. After a first PostDoc in the group of Daniela Rupp at ETH Zurich, where I led the machine-learning projects, I am now doing my second PostDoc at the Max-Planck-Institute of Animal Behavior in the group of Ariana Strandburg-Peshkin.
I have experience leading a small team of researchers and have completed the "Leading for tomorrow" program offered to only a few each year by the Deutsche Physikalische Gesellschaft.
I have strong programming skills in Python (especially with Tensorflow and Pandas/Scikit) and a robust mathematical understanding of most machine-learning algorithms, including Attention Networks, Variational approaches (VAE), classical Neural Networks, Random Forest methods, linear and logistic regression analysis, and PCA, SVD based approaches. I wrote or contributed to several data acquisition pipelines used in large-scale experiments and have experience in deploying these pipelines on cloud solutions like GCP.
In addition, I am a "Trusted Reviewer" for Institute of Physics Publishing and have peer-reviewed for Journals like "Journal of Physics: Condensed Matter" and "Machine Learning: Science and Technology".
研究兴趣
论文共 8 篇作者统计合作学者相似作者
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Nature Communicationsno. 1 (2018)
High-Brightness Sources and Light-driven Interactions (2018)
作者统计
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D-Core
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