Master in Math of Machine Learning

(Previously—'Statistical Learning Theory' Master's program)

This joint program trains the next generation of scientists to effectively carry out fundamental research and work on new challenging problems in statistical learning theory. This field is at the cutting edge of various disciplines of mathematics and computer science. It is one of the most dynamic areas of modern science, encompassing mathematical statistics, machine learning, optimization, and information and complexity theory. From the start of the program, students collaborate in thematic working groups and actively participate in research, learning from HSE and Skoltech scientists as well as leading global specialists in statistics, optimization, and machine learning.

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Program Overview

This program stands at the crossroads of various disciplines of modern mathematics and computer science, including statistics, optimization, learning theory, information theory, complexity theory, as well as at the intersection of science and innovation in the field of modern information technology. Leading experts at HSE and Skoltech jointly provide instruction in this unique research-driven program.

Students participate in one or more working groups (research seminars), where they determine focus areas for an initial survey report and then solve challenges at the intersection of cutting-edge research and technology in statistical learning theory. These seminars are built on teamwork, as the tasks are undertaken are so complex that they can’t be solved by one person alone. Students learn how to effectively collaborate, bringing together their diverse collective skills, competencies, and experiences to determine successful solutions for complicated issues.

Program courses are taught by leading HSE experts, including globally renowned scholars such as Dr. Yurii Nesterov, Dr. Denis Belomestny, Dr. Dmitry Vetrov, Dr. Andrei Sobolevski, Dr. Alexey Naumov, and Dr. Quentin Paris. Lectures are also delivered by Skoltech professors including Dr. Ivan Oseledets, Dr. Viktor Lempitsky, Dr. Evgeny Burnaev, and Dr. Yury Maximov. This team is rather young, but its members have already made significant research achievements.

The program actively cooperates with the Russian Academy of Sciences Institute for Information Transmission Problems, as well as with relevant faculties at Moscow State University and the Moscow Institute of Physics and Technology. Graduates go on to work for major Russian and international companies and are in high demand for their exceptional mathematical skills.