Krešimir Kumerički

Krešimir Kumerički (full professor at Department of Physics, Faculty of Science, University of Zagreb, and guest professor at University of Regensburg).

Obtained PhD in physics at University of Zagreb. Worked as visiting researcher for longer periods at Universities of Oslo and Regensburg.

Published 34 research papers in international journals, which are cited 1400+ times. Field of expertise: theoretical elementary particle physics, in particular quark-gluon structure of particles like proton, and beyond-standard-models of neutrino mass.

Recently proposed application of neural networks to determination of quark pressure in proton (results were published in prestigious journal Nature).

Revealing subatomic world with neural networks 

Artificial intelligence and, in particular, machine learning (ML) algorithms shine when applied to “big data”.

And there are very few places today where interesting data is produced at such an enormous rate as in high energy physics experiments (like Large Hadron Collider in CERN).

We will discuss comparative advantages of ML algorithms in science, and show how we use neural networks to push boundaries of knowledge about the elusive world of subatomic particles.