István Csabai professor of physics, corresponding member of the Hungarian Academy of Sciences. He is doing research in several multidisciplinary fields where the new technologies make it possible to collect and analyze large amounts of data. His research focus is to understand complex systems, be it the living cell, the manmade Internet, or the large scale structure of the Universe. With his research group at Eötvös University, Budapest they combine the standard domain knowledge of the traditional disciplines with methods of modern statistical analysis, data mining, machine learning and efficient computational techniques.
Data-intensive approach in sciences
According to Arthur C. Clarke, “Any sufficiently advanced technology is indistinguishable from magic.” This is not just science fiction. Understanding the laws of mechanics made us able to build pyramids and cathedrals. Based on the laws of thermodynamics the invention of the steam engine empowered us to cross oceans and continents and today we all have „seven-league boots” in our garages. Understanding electrodynamics and quantum mechanics brought us the transistor that is at the heart of the Internet and the modern „magic mirrors”, the mobile phones. With the advancements of high throughput techniques, we may be ready to tackle another frontier: medicine at last, because it is the most sophisticated and complex.In the last decade, technological development increased the amount of data available at an incredible pace. This is true for all the sciences from microbiology to cosmology and even for our daily lives. In order to cope with the new challenges and seize the opportunities that arise, beyond human intelligence, machine learning is playing an increasingly important role. In my presentation I will try to sketch the path of data-driven sciences and show examples from different disciplines.