‘The Future Lies with AI Technologies and HSE University Understands That’
At the AI Journey 2023 international conference in Moscow, a ranking of Russian universities that train the best AI specialists was published. HSE University entered the A+ leadership group, taking first place according to such criteria as ‘Demand for hiring graduates’, ‘Quality of educational environment’, and ‘Activities for the development of school education’. Ivan Arzhantsev, Dean of HSE University’s Faculty of Computer Science, spoke to the HSE News Service about how AI specialists are trained at HSE University and what plans the university has in this area.
The rating is compiled by the Artificial Intelligence Alliance, which unites technology companies to develop artificial intelligence in Russia and ensure the country’s leadership in the global market. The association’s members include Sberbank, Gazprom Neft, Yandex, VK, the Russian Direct Investment Fund, SIBUR, Uralchem, Rusagro Group, Severstal, Samolet Group, and others.
— The leaders in the ranking of Russian universities that train the top AI specialists are HSE University, Moscow Institute of Physics and Technology, ITMO University, etc. How, in your opinion, did HSE University manage to achieve this impressive result?
— I am confident that the result was achieved thanks to the right strategy. This includes a focus on advanced scientific research, attracting leading scientists to the faculty, the development of current educational programmes, regular updating of courses, and active work with applicants. It also involves constant interaction with a wide pool of industrial and academic partners, the implementation of online programmes, engagement in the life of a large multidisciplinary university, and work with graduates. This approach was developed jointly with the faculty’s co-organiser, Yandex.
In terms of specific results, I would first of all note three things. Firstly, we are leaders in Russia in the number of publications at A* level conferences according to the CORE ranking. This is an important indicator for computer science—it confirms that the research conducted meets high international standards. Along with conferences, our collaborators are published in leading journals. Secondly, at the latest ICPC World Student Programming Championship, our team showed the best result of any Russian team and received a bronze medal. Finally, for several years now the faculty has been leading in the number of prize winners of the All-Russian Olympiad for school students in computer science and mathematics.
— Tell us how education in the field of AI is structured today at the Faculty of Computer Science.
— Currently, the faculty has five bachelor’s and ten master’s programmes, and we are preparing to open several more programmes next year. Our flagship undergraduate programmes are Applied Mathematics and Information Science and Software Engineering. We also offer an English-taught Bachelor’s degree in Data Science and Business Analytics. Three years ago, we opened an online Bachelor’s programme in Computing and Data Science, and a year later we created an educational programme in Economics and Data Science jointly with the Faculty of Economic Sciences.
All bachelor’s programmes are based on training in fundamental disciplines, a large number of practice-oriented courses, project work, and regular internships in partner organisations.
Most master’s programmes are implemented jointly with partners: a Master’s programme with Sberbank, Financial Technologies and Data Analysis; a double degree programme with Skoltech, Math of Machine Learning; a joint programme with the Institute for System Programming of the Russian Academy of Sciences named after V. P. Ivannikov, System Programming; our new Master’s programme Data Analysis in Development jointly with the Samolet Group, as well as the Modern Computer Science programme and the English-language online Master of Data Science programme jointly with Yandex.
We are also developing online programmes. The CPD Centre implements both open additional professional education programmes and programmes in the field of AI for corporate customers. Course topics include programming languages, mathematics for data analysis, algorithms and data structures, machine learning, and much more.
— How does the Faculty of Computer Science collaborate with other HSE University faculties in terms of AI education or R&D projects?
— Since 2017, HSE University has been implementing a large-scale Data Culture project. The project’s goal is to expand students’ digital competencies. In the first two years of the project’s existence, courses on working with data were included in all undergraduate educational programmes at HSE University’s Moscow campus. The project also works with master’s programmes and doctoral schools and offers its expertise to partner universities. To develop a sufficient level of competencies, three blocks have been identified: digital literacy, algorithmic thinking and programming, and data analysis and AI methods.
For students of other faculties who would like to get acquainted with the topic of AI in more depth, the Faculty of Computer Science offers several minors. The most popular ones include Data Mining and UX Design.
Specialists from the Faculty of Computer Science are included in teams that conduct fundamental research or carry out applied developments in a wide range of socio-economic and humanitarian areas.
On a separate note, I would like to mention our cooperation with the Faculty of Economic Sciences. In addition to the abovementioned joint bachelor’s programme in Economics and Data Science, we participate in teaching double degree programmes that the Faculty of Economic Sciences implements jointly with Far Eastern Federal University and Tyumen State University.
— How important is it for HSE University to partner with market leaders in the field of AI technologies?
— Without such partnerships, a modern computer science department simply cannot exist. Each module is taught by 80 to 100 Yandex employees. As a rule, these are young people who work on relevant issues in the company, and communication with such teachers brings benefits and pleasure to students. The joint department with Sberbank is active as always: colleagues teach at undergraduate and graduate levels, supervise coursework and graduation projects, give lectures, and very recently held the largest hackathon in the history of the department with more than 350 participants. 1C is an industrial partner of software engineering programmes. Lately, we have been cooperating a lot with Tinkoff and Central University. This summer, a joint department with MTS was opened.
I would like to acknowledge our academic partners. The faculty has been working for many years with industrial partnership departments: the Informatics and Management Department of the Federal Research Centre of the Russian Academy of Sciences, the department of the A. A. Kharkevich Institute for Information Transmission Problems of RAS, and the department of the V. P. Ivannikov Institute for System Programming of RAS. This year, an industrial partnership department was opened at the V. A. Steklov Mathematical Institute of RAS.
— What role does the recently created Institute of Artificial Intelligence and Digital Sciences at the Faculty of Computer Science play in the development of education and R&D in the field of AI?
— The Institute of Artificial Intelligence and Digital Sciences is very young; its creation was approved four months ago. The institute includes four leading laboratories of the faculty. The institute's main topics are related to the projects of HSE University’s AI Research Centre. Let me remind you that in 2021, HSE University was among the winners of the competition for a grant from the Russian government to create an Artificial Intelligence Centre. The creation of the AI Centre is a wonderful opportunity for the faculty to reach a qualitatively new level of research and applied development.
— Why is HSE University the best place to learn about AI technologies?
— Because the future lies with AI technologies. HSE University understands this and is successfully working on their development and implementation in all areas of the university’s activities. Because we are constantly changing, we know how to teach new things, and we explain complex things in a simple way. Because we are the largest university, where almost all areas of study are represented, and unique opportunities for interdisciplinary interaction will open up for you. Because we know how to listen to business, we understand its interests and expectations. Once you join us, you will study with the strongest and most motivated students, and the atmosphere and contacts will stay with you for life.
The English-language programme of HSE Online ‘Master of Computer Vision’ will change its name to ‘Artificial Intelligence and Computer Vision’ in 2024. Andrey Savchenko, the programme academic supervisor, shares how the new name will affect the programme semantics, why AI has become the main federal trend in the field of information technology, and what tasks graduates will solve.
In December, the HSE Institute for Statistical Studies and Economics of Knowledge and the HSE AI Research Centre participated in UNCTAD eWeek to discuss the future of the emerging digital economy. One of the topics discussed during the conference was artificial intelligence and its applications in driving the digital transformation of industry sectors. The session was co-organised by HSE University.
HSE University has proved its leading position in the first group of the ‘Research Leadership’ field under the Priority 2030 programme. The university has also received the highest grant for teaching digital competencies to students, demonstrating its educational leadership in the fields of digital technologies and AI.
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).
A multimodal neural network model by Sber, under the supervision of HSE University’s expert commission, has successfully passed the Unified State Exam in social studies. GigaChat completed all exam tasks and scored 67 points.
The International Sber Conference of Artificial Intelligence, ‘AI Journey 2023’ recently took place in Moscow. Alexander Rogachev, doctoral student of the HSE Faculty of Computer Science, and Egor Egorov, an HSE 4th-year undergraduate student became the winners of the AIJ Science competition for scientific articles on artificial intelligence that was held as part of the event. The research was carried out under the umbrella of the HSE's Laboratory of Methods for Big Data Analysis (LAMBDA).
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.
Top development teams around the world are trying to create a neural network similar to a curious but bored three-year-old kid. IQ.HSE shares why this approach is necessary and how such methods can bring us closer to creating strong artificial intelligence.
Seungmin Jin, from South Korea, is researching the field of Explainable AI and planning to defend his PhD on ‘A Visual Analytics System for Explaining and Improving Attention-Based Traffic Forecasting Models’ at HSE University this year. In September, he passed the pre-defence procedure at the HSE Faculty of Computer Science School of Data Analysis and Artificial Intelligence. In his interview for the HSE News Service, he talks about his academic path and plans for the future.
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.