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Regular version of the site

Laboratory of Methods for Big Data Analysis

The fundamental problem of processing big data lies in the data's diversity and abundance. Analysing heterogeneous information allows for a more complete description of reality to be formed, enabling more accurate forecasting. At the same time, volumes of such data are growing at an exponential rate, and special preparation is required to work with big data effectively. With the aim of creating a world-class practical centre to improve expertise in big data processing and analysis, the LAboratory of Methods for Big Data Analysis (LAMBDA) was created in February 2015.

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.

HSE Researchers Receive a Grant to Search for New Physics

A team of researchers from the HSE Laboratory of Methods for Big Data Analysis (LAMBDA) has won a contest held by the Presidential Research Funding Programme. Researchers with the laboratory are developing a system of algorithms that will help physicists look for new particles in the Large Hadron Collider.

Third summer school on "Machine learning in high energy physics"

From 17 to 23 July the third international school "Machine Learning in High Energy Physics 2017" (MLHEP 2017) will be held in the city of Reading, Great Britain. Within the framework of the summer school there will be lectures and seminars, which will demonstrate real examples of how modern technologies of machine learning allow us to give more precise answers to questions about the structure of our universe.

The International Master Class of CERN Was Held at the Faculty of Computer Science

On 27th of March the Faculty of Computer Science has hosted an international masterclass on data analysis at the Large Hadron Collider for high-school students. This worldwide event organized by CERN and coordinated by Technical University of Dresden has attracted more than 13000 students from 52 countries. The Moscow masterclass was performed in joint effort of Lyceum 1575 (Moscow), Lyceum 5 (Dolgoprudny, Moscow Region) and Kapitsa Phystech Lyceum (Dolgoprudny, Moscow Region). 

LAMBDA Lab seminar: Practical statistics. How do we work the statistics on Large Hadron Collider (LHC)

At the session of our seminar, Fyodor Ratnikov (senior researcher at LAMBDA Lab) delivered a report "Practical statistics. How do we work the statistics on Large Hadron Collider (LHC)"

Seminar LAMBDA on «Data Storage optimization by using data popularity information»

Mikhail Guschin, researcher of SDA delivered the report 'Data Storage optimization by using data popularity information'.

How Programmers Help Unravel the Secrets of Physics

The Summer School on Machine Learning in High Energy Physics, which was co-organised by the HSE Faculty of Computer Science and Russian internet company Yandex, has ended. Below, the Head of HSE's Laboratory of Methods for Big Data Analysis, Andrey Ustyuzhanin, talks about the various ways in which physicists and programmers cooperate. He also discusses how researchers from HSE and Yandex have been participating in CERN experiments and how ordinary smartphone users can help unravel the secrets of the universe.

HSE, Yandex and CERN Researchers Work Together on Machine Learning in High Energy Physics

On August 30, 2015, the Summer School on Machine Learning in High Energy Physics wrapped up this year’s session. The school, which was held at the St. Petersburg Academic University, was organized by HSE in cooperation with the Yandex School of Data Analysis (SDA) and the Yandex Data Factory (YDF). This school is continuing cooperation between Yandex and CERN, which involves YDF and SDA researchers working together with experimental physicists on solving current problems in the field of physics. Many tasks require using machine learning approaches, which allow for greater accuracy and efficiency in these studies.

How Programmers Help Unravel the Secrets of Physics

The Summer School on Machine Learning in High Energy Physics, which was co-organised by the HSE Faculty of Computer Science and Russian internet company Yandex, has ended. Below, the Head of HSE's Laboratory of Methods for Big Data Analysis, Andrey Ustyuzhanin, talks about the various ways in which physicists and programmers cooperate. He also discusses how researchers from HSE and Yandex have been participating in CERN experiments and how ordinary smartphone users can help unravel the secrets of the universe.

Lecture ‘Elementary! Is This the Right Answer?’ at Yandex

On June 5 a lecture by Tiziano Camporesi (CERN) took place at the Extropolis Conference Center. The event was co-organised by the Laboratory of Methods for Big Data Analysis.

LAMBDA Seminar on 'Pattern Recognition Techniques for Finding Very Rare Events in COMET Experiment'

Ewen Gillies, PhD student at the Imperial College of London, COMET experiment member, LAMBDA Research Assistant presented the report 'Pattern Recognition Techniques for Finding Very Rare Events in COMET Experiment' at LAMBDA seminar.