Andreas Trügler

Details about my work and research.

About myself

I am a theoretical physicist working at the interface between cryptography, artificial intelligence, and quantum information.

Andreas Trügler

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I’m especially interesed in secure quantum computation, cryptographic privacy-enhancing technologies and AI applications in physics and climate research.

For almost a decade I was working more or less solely on numerical simulations in plasmonics and theoretical nanophysics, where I mostly dealt with electromagnetic fields and electron oscillations at the nanoscale. Check out my textbook on plasmonics if you want to know more.

I obtained my PhD in the group of Ulrich Hohenester in 2011. I continued to work at the Institute of Physics in Graz for several years and also spent time abroad during research stays in Italy, Spain, Canada and France.

In June 2020 I obtained my Venia Docendi (habilitation) in theoretical physics and applied mathematics.

From Physics to AI and Cryptography

After another research project had ended I co-founded a Swedish data science company, where we were working on machine learning algorithms, neural networks, and AI solutions for earth observations based on satellite and remote sensing data. In 2019 I additionally entered a new research field based on cryptography and joined Know-Center in Graz, where I’m currently the deputy head of the data security research area. I am leading two research projects about privacy-preserving and explainable AI and have started to focus my research especially on secure quantum computation. Since October 2021 I’m also affiliated with the Institute of Geography and Regional Science at the University of Graz, where I am working on combining AI solutions with climate research and glaciology. Since 2022 I’m also doing research at the Institute of Interactive Systems and Data Science at Graz University of Technology.

Title image: Sermilik Fjord, Greenland 2018, © Andreas Trügler

Research Interests


I'm a scientist and researcher working on privacy-preserving machine learning applications.