A mathematical model of Covid-19 spreading in Nizhny Novgorod Region, which has been created by the Big Data Laboratory at Nizhny Novgorod Development Strategy Project Office, has been widely discussed in the media and on social networks. The research was led by Anastasia Popova, a master’s student of HSE University in Nizhny Novgorod, repeat winner of machine learning competitions, and winner of Ilya Segalovich Award by Yandex. In the following interview given on April 15, Anastasia speaks about how the model was developed, the data it uses, and long-term potential applications.
Researchers at HSE’s Laboratory of Methods for Big Data Analysis (LAMBDA) and the Yandex School of Data Analysis have significantly reduced the cost of CERN’s future SHiP detector. The detector will search for particles responsible for still unexplained phenomena in the Universe. With use of modern machine learning methods, LAMBDA and Yandex scientists came up with very effective configuration of magnets which protect the detector from background particles. As a result, the cost of the entire structure was reduced by 25%.