Join HSE's English-taught Courses on Coursera
In July, HSE is launching two English-taught courses on Coursera. Enrollement for the courses is still open. The full list of online courses offered by HSE is available on HSE MOOCs page.
Addressing Large Hadron Collider Challenges by Machine Learning
The course is part of the Advanced Machine Learning specialization. It is intended for those who have already studied the methods of machine learning and would like to apply them to practical research problems, in particular, in high energy physics. Many of the experiments are carried out on a Large Hadron Collider and require processing of huge amounts of information. The course will help participants to understand how to do it. Background in physics is not required.
The course starts July 9 and applications are open till July 14 (the course is relaunched every two weeks). The course is taught in English.
Mathematics for Economists
The course is intended for bachelor’s and first-year master’s students who would like to gain skills in applying mathematical knowledge and expertise to solving economic problems. Participants will also learn how to present proofs. The authors of the course believe that mathematical concepts are not only beautiful theories in books; they can help to better understand the real life situations.
The course starts July 16. The course is taught in English.
Mathematicians at the Higher School of Economics have developed a model that explains how cell specialization arises in the context of resource constraints. The results are published in PLOS One journal.
An international group of researchers (the first author is Nikita Kalinin, HSE Saint-Petersburg, the last author is Ernesto Lupercio, CINVESTAV, Mexico) has presented the first continuous model describing self-organised criticality. The proposed solution is simpler and more universal than the classical sandpile model: it integrates areas as remote from one another as economics, developmental biology and gravity in the context of tropical geometry. The paper was published in PNAS.
Graduates of the Faculty of Mathematics at HSE, Andrey Ionov and Lera Starichkova, who have since enrolled in educational programmes at leading international universities, spoke about their love for mathematics, the level of the Bachelor programme at HSE, and admission to foreign PhD programmes.
The HSE Summer University is off to a strong start this year, and one of its programmes – the Research Experience for Undergraduates (REU) in Mathematics – has already been met with considerable enthusiasm by participating students. Designed for undergraduate students majoring in Mathematics or related areas, participants work on research projects under the supervision of distinguished mathematicians.
Moscow Lectures, a new series of books in English, is set to be published by Springer Nature. The series is issued jointly by HSE and Skoltech, and its Editor-in-Chief is Alexey Gorodentsev, Professor at the HSE Faculty of Mathematics. Twelve volumes are currently in preparation and the first volume will be published at the beginning of June 2018. The series builds on the outstanding research and education in the field of mathematics in Moscow. It is aimed at graduate and undergraduate students, as well as lecturers and researchers, across the globe.
On May 29, Samsung opened its new Artificial Intelligence Centre in Moscow. Dmitry Vetrov, Professor of the HSE Faculty of Computer Science, will become one of its leaders and oversee research in machine learning.
A team of HSE students has sucessfully returned after taking part in the 28th Vojtěch Jarník International Mathematical Competition, held in the Czech Republic. The competition has been held annually since 1991 by the University of Ostrava in the Czech Republic. Students compete in two age groups: category I (junior group) is for first and second-year students under 22 years and category II (senior group) is for older students.
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%.
On March 24, a mathematics test 'Q.E.D.' (quod erat demonstrandum, meaning 'which was to be proved') will take place, organized by Yandex. It is open to anyone who is interested. As on previous occasions, HSE will be one of the test sites.