Together with two other researchers, JKU mathematician Mario Ullrich was presented with the "2021 Joseph F. Traub Prize for Achievement in Information-Based Complexity". Presented annually for particularly outstanding contributions focusing on "information-based complexity", the award is also endowed with USD$ 3,000, which will be shared among the winners.

Ullrich is extremely pleased about the reward and remarked: "I consider the award a tremendous honor and an 'accolade' in my field of research. The award validates the quality and direction of my research even more and as the youngest recipient of this prestigious award to date, it motivates me to forge ahead in the future."

Ullrich was presented with the award in recognition of his contributions to numerics and complexity theory of high-dimensional integration and approximation, particularly his focus on the "power of random information". Over the years, countless fundamental advances have been made in this area, aiming to provide a theoretical explanation for real-world success in Data Science and Machine Learning. Until now, this success has been largely misunderstood as the most successful applications involved complex problems; the data, however, is often used randomly and/or is unstructured - unlike the award Ullrich is receiving with very good reason.