Group of Prof. Dr. Nicola Serra

An interdisciplinary grant to apply optimisation technques from the natural sciences to supply chain and logistics has been approved! See more details here: https://www.news.uzh.ch/en/articles/news/2025/discovery-grant.html

Our group is focussed on machine learning applied to several different fields. The original focus was on experimental particle physics, focussed on the analysis of huge amount of data collected at CERN. Currently our particle physics research is focussed on the application of machine learning to detector design, which is a highly challenging problem that must deal with complex constraints and large uncertainty. We are also involed in multiple interdisciplanery projects, which are focussed on optimising large and complex systems that also face large and unpredictable uncertainty. 

Nicola Serra is Full Professor at the University of Zurich, working at the interface of experimental particle physics, machine learning, and interdisciplinary decision systems under uncertainty. His research career has been strongly connected to CERN, where he has contributed to the LHCb experiment and has been a co-initiator of both the SHiP and SND@LHC experiments. He serves as Physics Coordinator of SHiP and is a member of the collaboration boards of LHCb, SND@LHC, and the Mu3e experiment at PSI. His group has played a leading role in applying artificial intelligence to high-energy physics, including reinforcement learning for detector design, graph neural networks for event reconstruction, and generative methods for simulation. More recently, his research has expanded toward interdisciplinary applications of machine learning and reinforcement learning in healthcare and epidemiology through an SNSF Sinergia project (https://data.snf.ch/grants/grant/216636), and toward decision support for logistics and supply chain through a BRIDGE Discovery project (https://www.news.uzh.ch/en/articles/news/2025/discovery-grant.html).