
Research Topic A
His proposed UNIPhD project is related to the neutrino mass ordering determination with the JUNO experiment — the next-generation neutrino experiment under construction in China. The first experimental data are expected to be collected during his UNIPhD project. It is a brilliant opportunity to participate in the physical analysis of the neutrino oscillations properties. Moreover, it’s expected that he will develop high-precision reconstruction algorithms for JUNO data processing and participate in the commissioning of the detector.
He obtained his Bachelor’s degree with honours in physics and his Master’s degree with honours in applied mathematics in Russia. His fields of interest are neutrino physics and machine learning (ML) applications. He completed his Master’s thesis on energy reconstruction in the JUNO experiment with ML methods under the supervision of Dr. Yury Malyshkin and Dr. Fedor Ratnikov. He is very grateful to them for their invaluable contribution to his growth as a researcher. His work in JUNO gave him a precious research experience and showed him that the way of the scientist he has chosen is appropriate for him.
