Winners of the International Olympiad in Artificial Intelligence Admitted to HSE University
In mid-August, Bulgaria hosted the finals of the first International Olympiad in Artificial Intelligence (IOAI) among high school students. The Russian team demonstrated excellent results, winning gold medals in the scientific round, silver medals in the practical round, and coming first in both rounds overall. This year two members of the Russian team were accepted into the programmes of the HSE Faculty of Computer Science.
In the final round of the competition, the Russian team faced off against school students from 39 countries, including China, Japan, Canada, Sweden, the Netherlands, and the USA. The Central University (CU), established with the support of T-Bank, was responsible for training the team.
Currently, two members of the Russian team, Nikita Kurlaev and Andrey Gritsaev, are first-year students at HSE University. They talked to HSE News Service about the Olympiad, the admission process, and their plans for the future.
Nikita Kurlaev
About the Olympiad
— The fact that this year’s Olympiad was the first of its kind greatly influenced our experience of participating in it. It differs from traditional international Olympiads like IMO and IOI, which have a large international community and a long history of training participants. We went to the competition without knowing what tasks we would face, who the other participants would be, or how the results would be checked, etc. We prepared using official materials, but clearly it wasn’t enough.
Many teams that did not win medals included participants or candidates for the IOI and IMO national teams. These are extremely smart people who, unfortunately, did not dedicate enough time to studying the features of ML. I am sure that next year it will be even more challenging but also more interesting to participate in this Olympiad.
I am pleased to have taken first place, although it was a difficult achievement. We have been diligently preparing for a long time and we have benefited from years of experience in Olympiads, including the All-Russian Olympiad for schoolchildren, as well as our knowledge of mathematics and computer science.
About machine learning
— I've been interested in machine learning for a long time, but I didn't acquire the skills I needed to study it until the 10th grade. Even a basic understanding of ML methods requires a good knowledge of mathematics at a level beyond the school curriculum. At first, ML seemed like magic to me, and I tried unsuccessfully to play around with existing models. It wasn’t until grades 10–11 that I started to study machine learning more seriously. I read articles and books about ML, worked on small projects.
About HSE University
— I have realised that HSE University meets my requirements much better than other universities. This decision was based on several factors, including university values, campus infrastructure, teaching staff, and study process. I am confident that the ‘Applied Mathematics and Information Science’ programme at FCS offers the best bachelor's programme in computer science in Russia.
About my future plans
— In the next four years, my main focus will be on completing my degree. I may participate in student competitions or internships, but studying remains my top priority. After graduating, I hope to pursue a master’s degree in a related field. I envision myself engaging in scientific research and perhaps working in the ML field. While it’s difficult to predict what my interests will be in a few years, at the moment, I can only speak about my current interests, hoping they will remain relevant in the future.
Andrey Gritsaev
About the Olympiad
— I wanted to participate in the Olympiad for several reasons. Firstly, it was an opportunity to compete and solve problems in a field that I’m interested in. Secondly, I wanted to meet smart students from other countries who shared my passion for AI. The Olympiad consisted of two rounds: a scientific round and a practical round. In the scientific round, we were given problems that simulated real research in AI. These problems were divided into three categories: machine learning, natural language processing, and computer vision. During the practical round, we conducted experiments with AI software, such as ChatGPT and DALL-E 2.
Tips for high school students
— Consider participating in the All-Russian Olympiad in Artificial Intelligence if you are interested in this field. Additionally, if you want to learn more about machine learning, I suggest taking some courses. This year, there may be training camps preparing for AI Olympiads, so it's worth keeping an eye out for updates from the Olympiad community.
About my future plans
— In the next few years, I intend to pursue research and work in this area.
See also:
AI vs AI: Scientists Develop Neural Networks to Detect Generated Text Insertions
A research team, including Alexander Shirnin from HSE University, has developed two models designed to detect AI-generated insertions in scientific texts. The AIpom system integrates two types of models: a decoder and an encoder. The Papilusion system is designed to detect modifications through synonyms and summarisation by neural networks, using one type of models: encoders. In the future, these models will assist in verifying the originality and credibility of scientific publications. Articles describing the Papilusion and AIpom systems have been published in the ACL Anthology Digital Archive.
HSE Researchers Develop Python Library for Analysing Eye Movements
A research team at HSE University has developed EyeFeatures, a Python library for analysing and modelling eye movement data. This tool is designed to simplify the work of scientists and developers by enabling them to efficiently process complex data and create predictive models.
‘Many Want to Create AI-Based Products and Become More Competitive’
In 2024, the online Russian-taught master’s programme ‘Artificial Intelligence,’ offered by the HSE Faculty of Computer Science, saw a record number of first-year students—over 300. What accounts for such a high interest in AI, how the curriculum is structured, and what new skills will graduates acquire? Elena Kantonistova, the programme’s academic director, shares more.
'I Would Like to Leave a Lasting Impact on Science'
Aibek Alanov pursues his own scientific research and leads two teams of scientists, one at HSE University and the other at AIRI. In this interview for the HSE Young Scientists project, he explores the parallels between today's AI researchers and early 20th-century physicists, discusses generative models, and shares his passion for bachata partner dancing.
HSE’S Achievements in AI Presented at AIJ
The AI Journey international conference hosted a session led by Deputy Prime Minister Dmitry Chernyshenko highlighting the achievements of Russian research centres in artificial intelligence. Alexey Masyutin, Head of the HSE AI Research Centre, showcased the centre’s key developments.
Drivers of Progress and Sources of Revenue: The Role of Universities in Technology Transfer
In the modern world, the effective transfer of socio-economic and humanities-based knowledge to the real economy and public administration is essential. Universities play a decisive role in this process. They have the capability to unite diverse teams and, in partnership with the state and businesses, develop and enhance advanced technologies.
AI on Guard of Ecology: Students from Russia and Belarus Propose New Solutions to Environmental Problems
An international online hackathon dedicated to solving environmental problems was held at HSE University in Nizhny Novgorod. Students employed artificial intelligence and computer vision to develop innovative solutions for image segmentation, predictive modelling (forecasting future events based on data from the past) of emissions and creating chatbots for nature reserves and national parks.
Taming the Element: How AI Is Integrating into the Educational Process Around the World
Artificial intelligence is gradually becoming an indispensable part of higher education. Both students and teachers use it to reduce the volume of routine tasks and expand their capabilities. The limitations and prospects of AI are discussed in the report ‘The Beginning of the End or a New Era? The Effects of Generative Artificial Intelligence (GAI) in Higher Education,’ published in the journal Modern Education Analytics, under the scientific supervision of HSE Academic Supervisor Yaroslav Kuzminov.
A New Tool Designed to Assess AI Ethics in Medicine Developed at HSE University
A team of researchers at the HSE AI Research Centre has created an index to evaluate the ethical standards of artificial intelligence (AI) systems used in medicine. This tool is designed to minimise potential risks and promote safer development and implementation of AI technologies in medical practice.
HSE Researchers Develop Novel Approach to Evaluating AI Applications in Education
Researchers at HSE University have proposed a novel approach to assessing AI's competency in educational settings. The approach is grounded in psychometric principles and has been empirically tested using the GPT-4 model. This marks the first step in evaluating the true readiness of generative models to serve as assistants for teachers or students. The results have been published in arXiv.