Due to my current position as deputy head of the data security research area at Know-Center and my focus on privacy-enhancing technologies (see projects), I’m very happy about the opportunity to closely collaborate with Christian Rechberger and his excellent team, renowned experts in the field of cryptography and privacy.

Machine learning algorithms are a fascinating set of tools that opened up completely new ways of analytics and evaluations. Modern neural networks outperform human capabilities when it comes to image recognition, reinforcement learning approaches allow computers to learn new tasks with incredible speed and many of the large scientific experiments would not be possible without the application of algorithmes that have learned to deal with the plethora of generated data.

In 2018 the European Union decided to invest 10 billion euros in emerging technologies based on quantum mechanics. This funding initiave is called Quantum flagship and should drive the so called second quantum revolution in Europe.

One of the great things about machine learning algorithms is that they can be applied to so many different fields and problems, that’s one of the main reasons why working with them is so fascinating. Due to my passion for mountains, snow and remote areas like Greenland or Svalbard, linking them with geoscience and glaciology was kind of obvious for me.

Half a century ago it was Richard Feynman who first talked about the incredible possibilities if we investigate physics at the nanoscale (There’s Plenty of Room at the Bottom, 1959, Caltech). It took nearly 20 years until this first concepts became reality.