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.
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Immortal Cells and Mathematics Reveal Mechanism behind Coronavirus Infection
A mathematical model has helped describe the course of infection caused by two variants of coronavirus: Omicron and Delta, and explain the differences between them. It appears that the cell entry rate is lower for Omicron, allowing infected cells ample time to alert neighbouring cells of the threat and trigger the activation of their innate immune response. In the future, the developed model could be employed to investigate any other variant of COVID-19, potentially leading to effective strategies for combating new hazardous strains, such as Pirola and JN.1. The findings from the study conducted with the participation of HSE researchers have been published in PeerJ.
‘The Goal of the Spring into ML School Is to Unite Young Scientists Engaged in Mathematics of AI’
The AI and Digital Science Institute at the HSE Faculty of Computer Science and Innopolis University organised a week-long programme for students, doctoral students, and young scientists on the application of mathematics in machine learning and artificial intelligence. Fifty participants of Spring into ML attended 24 lectures on machine learning, took part in specific pitch sessions, and completed two mini-courses on diffusion models—a developing area of AI for data generation.
Mathematicians Reveal the Mechanism behind Neuron Synchronisation: Hyperchaos
Scientists of the International Laboratory of Dynamic Systems and Applications at HSE Campus in Nizhny Novgorod have described a rare case of synchronisation in a system of chemically coupled neuron models. The study findings enable a mathematical description of atypical brain functioning modes, including those associated with neurodegenerative diseases. The study has been published in Regular and Chaotic Dynamics.
Software for Rapid Detection of Dyslexia Developed in Russia
HSE scientists have developed a software tool for assessing the presence and degree of dyslexia in school students based on their gender, age, school grade, and eye-tracking data. The application is expected to be introduced into clinical practice in 2024. The underlying studies were conducted by specialists in machine learning and neurolinguistics at the HSE AI Research Centre.
‘Every Article on NeurIPS Is Considered a Significant Result’
Staff members of the HSE Faculty of Computer Science will present 12 of their works at the 37th Conference and Workshop on Neural Information Processing Systems (NeurIPS), one of the most significant events in the field of artificial intelligence and machine learning. This year it will be held on December 10–16 in New Orleans (USA).
‘The Joy of Science Lies in the Euphoria of Learning’
For Elena Nozdrinova, mathematics is her life's work and a realm where she discovers universal order and harmony. In her interview with the HSE Young Scientists project, she speaks about dynamical systems, the Nizhny Novgorod scientific school, and favourite pastimes that help her grow.
HSE University Holds HSE Sber ML Hack
On November 17-19, The HSE Faculty of Computer Science, SBER and cloud technology provider Cloud.ru organised HSE Sber ML Hack, a hackathon based around machine learning. More than 350 undergraduate and graduate students from 54 leading Russian universities took part in the competition.
HSE University Hosts Fall into ML 2023 Conference on Machine Learning
Over three days, more than 300 conference participants attended workshops, seminars, sections and a poster session. During panel discussions, experts deliberated on the regulation of artificial intelligence (AI) technologies and considered collaborative initiatives between academic institutions and industry to advance AI development through megaprojects.
HSE University to Host ‘Fall into ML 2023’ Machine Learning Conference
Machine Learning (ML) is a field of AI that examines methods and algorithms that enable computers to learn based on experience and data and without explicit programming. With its help, AI can analyse data, recall information, build forecasts, and give recommendations. Machine learning algorithms have applications in medicine, stock trading, robotics, drone control and other fields.
New Labs to Open at Faculty of Computer Science
Based on the results of a project competition, two new laboratories are opening at HSE University’s Faculty of Computer Science. The Laboratory for Matrix and Tensor Methods in Machine Learning will be headed by Maxim Rakhuba, Associate Professor at the Big Data and Information Retrieval School. The Laboratory for Cloud and Mobile Technologies will be headed by Dmitry Alexandrov, Professor at the School of Software Engineering.