Spotlights
Articles showcase the heart of the Computer Science Department: exceptional individuals, ground-breaking research, a strong focus on key topics and current projects, along with an inherent dedication to the development of computer science.
Test of Time Award for Peter Müller
Professor Peter Müller and his co-author have been awarded the prestigious ETAPS Test of Time Award for their paper “A Basis for Verifying Multi-threaded Programs”. The ETAPS Test of Time Award has been established to recognise outstanding papers published more than 10 years ago. Congratulations!
Making augmented reality suitable for society
ETH Zurich is establishing the Augmented Reality Research Hub (ETHAR) in close collaboration with Google. The hub aims to promote interdisciplinary research and produce scientific publications, open-source systems, and new datasets in the field of augmented reality. It is being led by Computer Science Professors Christian Holz and Thomas Hofmann.
Federal Council Guy Parmelin and ETH president Joël Mesot visit INSAIT in Bulgaria
On Wednesday, 7 May 2025, Federal Councillor Guy Parmelin visited the Institute for Computer Science, Artificial Intelligence and Technology (INSAIT) in Bulgaria. Among those in attendance were D-INFK Professor and INSAIT founder Martin Vechev, ETH President Joël Mesot, and the Bulgarian Prime Minister, Rosen Zhelyazkov. The visit marked the third anniversary of INSAIT’s official opening and the fourth year since its inception.
ETH Team wins 2025 Geneva Cyber 9/12 Strategy Challenge
On 10 and 11 April, the cyber competition Geneva Cyber 9/12 Strategy Challenge 2025 took place. Team PhishTank from ETH Zurich won first place, while Team Ephex from EPFL came in third. Congratulations!
AI provides reliable answers with less computational overhead
ETH Zurich researchers have introduced SIFT (Selecting Informative data for Fine-Tuning), a novel algorithm that enhances the reliability of AI responses by reducing uncertainty through tailored data enrichment. Developed by Jonas Hübotter during his doctoral studies in the Learning & Adaptive Systems Group under the supervision of Prof. Andreas Krause, the method identifies data most relevant to a specific query and filters out redundant information.