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 two further research groups:
The expertise of these three groups is now complemented by
at our Graduate School of Artifical Intelligence. The doctoral program benefits from the synergies of these six 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.
The dramatic increase in using of Artificial Intelligence (AI) and machine learning methods in different fields of science becomes an essential asset in the development of the chemical industry, including pharmaceutical, agro biotech, and other chemical companies. However, the application of AI in these fields is not straightforward and requires excellent knowledge of chemistry. Thus, there is a strong need to train and prepare a new generation of scientists who have skills both in machine learning and in chemistry and can advance medicinal chemistry, which is the prime goal of the AIDD proposal. Research WPs include sixteen topics selected to cover the key innovative directions in machine learning in chemistry. Fellows employed will be supervised by academics who have excellent complementary expertise and contributed some of the fundamental AI algorithms which are used billions of times per day in the world, and leading EU Pharma companies who are in charge of new medicine and public health. All developed methods can be used individually but will also contribute to an integrated "One Chemistry" model that can predict outcomes ranging from different properties to molecule generation and synthesis. Training on various modalities allows the model to understand how to intertwine chemistry and biology to develop a new drug making its design robust and explainable. All partners agreed to make their software open source. It will boost the field and will provide the broadest possible dissemination of the results both to the academy and industry, including SMEs. The network will offer comprehensive, structured training through a well-elaborated Curriculum, online courses, and six Schools. The IP policy and commercial exploitation of the project results have the highest priority supported by intellectual property asset management organizations. Comprehensive public engagement activities will complement the dissemination of results to the scientific community.
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 956832.
The project will start on January 1st, 2021
ELLIS Health online workshops
The JKU and the Viennese software company Anyline will embark on a joint AI research partnership - including funding from the Austrian Research Promotion Agency.
AI expert Sepp Hochreiter has been named as one of the 10 most important researchers in the field of Deep Learning.