The LAboratory of Methods for Big Data Analysis (LAMBDA) currently focuses on using machine-learning and data analysis methods to solve issues in fundamental sciences such as particle physics and astrophysics. The Laboratory’s main developmental direction is to work with leading scientists from these fields to search for answers to the universe’s mysteries. Specifically, the Laboratory cooperates with the European Organization for Nuclear Research (CERN), researching the events of the Large Hadron Collider and raising the efficiency of data analysis.
In addition, the Laboratory’s educational activities include organizing and carrying out academic seminars and summer/winter schools on big data analysis and providing scientific guidance to thesis and dissertation work.
LAMBDA was created in February 2015.
The Autumn School took place from November 23 to 26 in mixed format. The classes were hosted at Yandex School of Data Analysis. Those who were not able to attend on-campus joined online.
Ten universities and institutes have announced a partnership to construct an electron-positron collider in order to study the production and properties of charmed particles and tau leptons. The new experiment will be part of the Super C-Tau Factory project. It was founded by two international teams and eight from Russia, including HSE University.
A competition of research centres looking to receive grants through the Artificial Intelligence federal project has concluded, and HSE University is among the winners. Winning centres will focus on developing new AI technologies that expand its application, overcoming existing limitations for solving applied problems and optimizing AI models.
"My Model Will Be Used to Analyse Data from the ATLAS Detector Collected During the New Collider Launch in 2022"
Tigran Ramazyan, a fourth-year student of the Data Science and Business Analytics double-degree programme, has talked about his studies at the Faculty and internship at CERN openlab.
On July 15-30, the Seventh International School on Machine Learning in High Energy Physics (MLHEP) organised by the Laboratory of Methods for Big Data Analysis (LAMBDA), Yandex School of Data Analysis and EPFL (Switzerland) took place.
Artem Maevskiy, LAMBDA researcher, participated in giving an Imperial Collegue London (ICL) Machine Learning & Deep Learning online-course.
‘We Facilitate High-Speed Car Crashes and Study How Car Engines Work Based on Photos of Flying Debris’
Nikita Kazeev holds a Candidate of Sciences degree (Russian equivalent of a PhD) in Computer Science and a PhD in Physics. He is a Research Fellow at the LAMBDA Laboratory and works at CERN. In an interview with HSE News Service, he talked about what it was like to defend his dissertation in a double doctoral degree programme at HSE University and Sapienza University of Rome, what it is like to conduct research in Geneva, and why it is imperative to communicate with colleagues.
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.
Laboratory of Methods for Big Data Analysis (LAMBDA) of the Faculty of Computer Science, HSE University held the sixth summer school on Machine Learning in High Energy Physics (MLHEP) on July 16-30. The school was organised in cooperation with Yandex School of Data Analysis and EPFL High Energy Physics Laboratory. This year the school was listed as an official EPFL course with 4 ECTS credits awarded to the participants successfully passing the school requirements.
𝐋𝐀𝐌𝐁𝐃𝐀 scientists Andrey Ustyuzhanin and Denis Derkach have participated as speakers at the Open conference on artificial intelligence “𝐎𝐩𝐞𝐧𝐓𝐚𝐥𝐤𝐬.𝐀𝐈”