Hochsprung Award honours company founded on the basis of information field theory
Analysing the data collected by astronomical instruments and interpreting them to gain precise knowledge about the universe is a complex mathematical problem. Torsten Enßlin developed the Information Field Theory at MPA to provide an optimal solution to this problem. Using this method, more accurate maps of the cosmos can be produced and the data collected by different instruments can be combined. However, his lecture on this topic, which focused purely on fundamental research, led to very application-oriented activities: after their studies, two former MPA PhD students, Maksim Greiner and Theo Steininger, together with the engineer Isabell Franck founded the start-up "IPT - Insight Perspective Technologies GmbH".
The company uses the Bayesian probability calculus, which is also the basis of the information field theory developed for astronomical research. Instead of fundamental research though, the young entrepreneurs use the methods based on this information theory in industrial applications, as they already impressively demonstrated. The start-up company offers the services data analysis, machine learning, and data-based prediction models.
This successful knowledge transfer was honoured with the Hochsprung Award on October 17. Founded in 2000 as part of the high-tech offensive Bavaria, “Hochsprung” is the entrepreneurship network of Bavarian universities. First presented in 2015, the Hochsprung Award has been awarded annually since 2018, alternating between "Entrepreneurship Enablers" and "University Start-ups". This year for the first time start-ups were sought whose founding project was inspired by a lecture course at a public or private Bavarian university - in this case the lecture series on "Information Field Theory" by Torsten Enßlin at the LMU.
"This company foundation beautifully shows how a research environment purely focused on gaining knowledge about the universe can be relevant for business," sums up Torsten Enßlin. "These three Bayesians developed the idea for their foundation already during their doctorates.”