Our three pillars: Machine Learning, Logical Reasoning, Computational Perception
The LIT AI Lab headed by Prof. Sepp Hochreiter was founded as a permanent research center of the Linz Institute of Technology (LIT). In the unique environment offered by the Johannes Kepler University (JKU) Linz, the LIT AI Lab bundles JKU’s world-class expertise in artificial intelligence (AI) for shaping and advancing AI research and its industrial applications.
The LIT Lab is committed to scientific excellence. Our focus is on theoretical and experimental research in machine learning, logical reasoning, and computational perception. We train the next generations of AI researchers and educate engineers at various academic levels in AI technology.
“Artificial Intelligence (AI) is the part of computer science concerned with designing intelligent computer systems, that is, systems that exhibit characteristics we associate with intelligence in human behaviour – understanding language, learning, reasoning, solving problems, and so on.”
(Barr & Feigenbaum, 1981)
Our Goals, Mission, and Team: Learn More About Us.
Created in 2017 as a permanent research institution, the LIT AI Lab started with three seed groups conducting core AI research:
and three further research groups:
The expertise of these six groups is now complemented by
at our Graduate School of Artifical Intelligence. The doctoral program benefits from the synergies of these nine groups, focusing on interdisciplinary research to advance AI. In order to broaden the application areas of our AI research in the LIT AI Lab, we collaborate closely with other JKU institutes that conduct related research as well as with international companies.
A city of music just the way you like it
Project Manager: Markus Schedl
Institute of Computational Perception / LIT AI Lab
First talk by Richard Küng, Institute for Integrated Circuits, Johannes Kepler University Linz
Trusted Artificial Intelligence: Towards Certification of Machine Learning Applications
In our new paper, we identify and counter domain shifts in machine learning models for COVID-19 diagnosis from blood tests: