Tomasz Golan has been working at NeuroSYS since 2017. His research interests include computer vision and machine learning algorithms.

He worked on various problems related to image classification, object detection, and pose estimation. He holds a PhD in theoretical physics for the thesis on modeling nuclear effects in a Monte Carlo neutrino event generator. For about 10 years, he was a member of the T2K collaboration – a particle physics experiment studying neutrino oscillation – and, together with all the collaborators, he was awarded the 2016 Breakthrough Prize in Fundamental Physics.

In the years 2014-2016, he worked as a Postdoctoral Associate in a joint appointment with Fermi National Accelerator Laboratory (Scientific Computing Division) and the University of Rochester (Department of Physics and Astronomy). He was responsible for implementing theoretical models in the GENIE Neutrino Monte Carlo Generator and designing the system for automated validation running on Fermilab’s servers. He also joined the MINERvA collaboration (a high energy physics experiment studying neutrino interactions with nuclei), where he was the coordinator of the Monte Carlo generators group and one of the originators of using machine learning methods for physics reconstruction.

In the years 2016-2019, he was an assistant professor at the University of Wroclaw, continuing his research on neutrino interactions and the application of machine learning in high energy physics. He joined the MINERvA Institutional Board to represent the University of Wroclaw within the collaboration. He is the co-author of 50+ scientific publications in journals from ICI Master Journal List. He presented his research at 6 international conferences and he was a member of the scientific committee of the NuInt 2017 conference.