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HSE Researcher Appointed Coordinator in Large Hadron Collider Experiment

HSE Researcher Appointed Coordinator in Large Hadron Collider Experiment

© Anna Pantelia / CERN

Mikhail Guschin, Research Fellow at the HSE University Laboratory of Methods for Big Data Analysis of the Faculty of Computer Science, was appointed coordinator of the machine learning and statistics working group in the LHCb Large Hadron Collider experiment at CERN (the European Organization for Nuclear Research). He will be the only representative of a Russian University among the coordinators for the experiment’s working groups.

The LHCb experiment is one of four experiments at the Large Hadron Collider (LHC). Teams of scientists from 87 organizations from 18 countries around the world are participating in it (HSE University joined LHCb as an associate member in June 2018). Any member of the team can nominate a candidate who they believe would be a strong coordinator. The nominations are then considered by the heads of the collaboration, who nominate the best candidate for the post. In December, Mikhail Guschin’s candidacy was unanimously approved by the LHCb Cooperation Council for a two-year term. The research fellow of the HSE University Laboratory of Methods for Big Data Analysis will begin his appointment on January 1, 2021. Among the working group coordinators of the experiment, he is the only representative of a Russian University.

‘This appointment attests to the quality of training we provide our junior researchers,’ says Denis Derkach, Head of the LHCb group at HSE University. ‘Mikhail has been working on the LHCb project for four years and has authored several publications on the application of machine learning to data processing in particle physics. The Basic Research Programme developed by HSE University and the Russian Science Foundation (RSF), which supported our research plan, undoubtedly made a decisive contribution to this success. I hope that we will continue to strengthen the positions of researchers from HSE University in the future.’

‘The first thing I experienced when I learned about my appointment was a sense of incredible responsibility,’ Mikhail Guschin says. ‘After all, this appointment is a form of international recognition of HSE University’s expertise in data analysis and machine learning; all of the participants of a major international experiment will be looking to this expertise.’

As coordinator, Mikhail Guschin will assist the working groups of the experiment in applying modern data analysis techniques in their published research. He is now preparing to take up his post: other coordinators of the team are briefing him on current matters and introducing him to the group’s immediate plans. A meeting with the management of the collaboration is also scheduled to discuss plans for the development of the working group.

Mikhail Guschin, Research Fellow, Laboratory of Methods for Big Data Analysis, Faculty of Computer Science, HSE University

Photo from personal archive

The goal of my group is to make sure machine learning (ML) techniques are applied correctly in the algorithms for collecting and analysing experimental data, because these algorithms will be running for over a year. In recent years, there has been an increase in the popularity of modern ML techniques. Therefore, it is crucial for the experiment that we ensure the correct use of this instrumentation. In particular, my task is to collect the best practices in the use of ML techniques for data analysis, and to make and disseminate recommendations among the working groups of the experiment. Another task is to advise on issues related to data analysis and ML.

Mikhail Guschin says that he expects to get involved in many interesting projects and meet many interesting people during his work as a coordinator. He would like to apply his knowledge to the LHCb experiment and perhaps uncover new secrets of the universe. In addition to working at CERN, he will continue working at HSE University. ‘I intend to continue working at the Faculty of Computer Science laboratory, which brings together a remarkable team of professionals researching the field of data analysis and machine learning.’

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