In-depth Stories

Researchers at ETH Zurich develop the fastest possible flow algorithm

Rasmus Kyng has written the near-perfect algorithm. It computes the maximum transport flow at minimum cost for any kind of network – be it rail, road or electricity – at a speed that is, mathematically speaking, impossible to beat. The superfast algorithm solves a key question in theoretical computer science and lays the foundation for efficiently computing very large and dynamically changing networks in the future.

by Florian Meyer

"If you survive this, then nothing will stop you"

In this series of interviews, we talk to three people who decided to pursue an academic career after studying computer science and are now working as professors. In the second part, Niao He talks about the challenges of the academic path, what it means for her to be a good teacher and how working as an assistant professor has also boosted her self-confidence.

by Pauline Lüthi

SPY Lab researchers first to ever peek into ChatGPT’s black box

In a world-first, researchers from the SPY Lab led by Professor Florian Tramèr along with collaborators have succeeded in extracting secret information on the large language model behind ChatGPT. The team responsibly disclosed the results of their “model stealing attack” to OpenAI. Following the disclosure, the company immediately implemented countermeasures to protect the model.

by Leonid Leiva Ariosa

How top-flight researchers draw global companies to Switzerland

ETH’s outstanding reputation attracts top-flight researchers from all over the world. This pool of talent makes Zurich a major draw for global companies such as Microsoft, with the opportunity for new research projects being established. Professor Marc Pollefeys from the Department of Computer Science now runs Microsoft’s Mixed Reality & AI Lab alongside his teaching and research commitments at ETH Zurich.

by Corinne Landolt

"AI helps us to grasp more and more complex facts"

Professor Joachim Buhmann

His dissertation in biophysics led Joachim Buhmann into the then still exotic terrain of machine learning in the mid-1980s. Since 2003, when he became an ETH professor, he has helped shape the explosive development of his field. It is not technical progress that worries him, but how society deals with it. Shortly before his retirement, he looks back on his academic career, in which, in addition to teaching and research, administrative functions have also been of great importance.

by Anna Janka / Leonid Leiva Ariosa
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