Description forthcoming

Guillaume Bellec

Guillaume Bellec studies the principles of brain computation using machine learning and artificial intelligence (AI). His work is most well-known for showing how a functional artificial intelligence can emerge from simplified mathematical models of biologically realistic neural networks. He studied machine learning during my Master’s in Paris and completed my PhD in 2019 at the Institute for Theoretical Computer Science of TU Graz in Austria. After a postdoc in the Laboratory of Computational Neuroscience at EPFL in Switzerland, he started my lab in 2025 at TU Wien (Vienna, Austria). Multiple of my publications are published in selective computer science conferences like NeurIPS or ICLR and more generalist journals like Nature Communications.

In 2019 he created Chord ai with another AI researcher Vivien Seguy. Chord ai is a mobile application using deep learning and artificial neural networks to recognize musical chords in real-time. The application and Chord ai has had more than 2,000,000 users on iOS and Android platforms in 2025. The technical achievement has been to bring state-of-the-art artificial intelligence technology to any popular power-limited mobile device. Besides the scientific challenge, he hopes that it will help amateur musicians like him to improve their musical skills.

Since 2025, the work of his research group at TU Wien is funded in part by the WWTF Vienna Research Group leader award Our project is called “AI & Neuroscience”. He and his team are very grateful to the Vienna Science and Technology Funds (WWTF) for their support.

Alex Jantsch

Alex Jantsch received a Ph.D. in Computer Sciene from TU Wien in 1992. Then he made a postdoc with Hannu Tenhunen at KTH, The Royal Institute of Technology in Stockholm, Sweden and stayed at KTH until 2014. During that time he enjoyed working with Ahmed Hemani, Zhonghai Lu, Ingo Sander, Lirong Zheng, Zhuo Zou, Dinesh Pamunuwa and many others, on topics like Networks on Chip and Models of Computation. In 2015 he moved to TU Wien and since then my main research interests are on Self-aware Cyber-physical systems, embedded machine learning, and SoCs and Embedded Systems in general. IEEE Fellow since Jan 2024.

Daniel Müller-Gritschneder

Daniel Müller-Gritschneder is a full professor of Computer Architecture at the Institute of Computer Engineering, TU Wien Informatics, Austria, since 2024. Previously, he was a research group leader at the Chair of Electronic Design Automation and acting professor for Real-time Systems at TU Munich, Germany. He received my Dipl.-Ing., Dr.-Ing. and Habilitation degree from TUM in 2003, 2009 and 2019 respectively. He likes working in collaborative research projects in close cooperation with industry partners and in the past cooperated with companies such as Infineon, Bosch, SPARX Systems, BMW and Mercedes. He often serves in committees for EDA conferences such as DAC, ICCAD, DATE, SAMOS and CODES/ISSS. He is also active in the RISC-V community and co-initiator and steering committee member of the RISC-V Summit Europe. He is a senior member of IEEE. His main research interests are in Electronic System Level Design, RISC-V domain-specific architectures, tinyML/embedded ML compiler toolchains as well as functional safety and HW security.

Activities

Fortcoming