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.
The participants were given the task of predicting the gender of a bank customer based on transactional activity from the SBER Risks Division. This information helps businesses develop banking products, as well as personalising services. As a key metric for evaluating the quality of the model, participants had to calculate ROC-AUC (a metric that allows the evaluation of the quality of a binary classification model).
For the first time at the Faculty of Computer Science, the competition was held on the DS Works.ru platform from Cloud.ru.
On the final day, the teams presented their solutions. The jury included experts from the Joint Department with Sberbank ‘Financial Technologies and Data Analysis’, the AI and Digital Science Institute, the Hackathon Club of the Faculty of Computer Science, Sber, Cloud.ru and RUTUBE.
The ‘Misiskovo’ team from Skoltech and MISIS won the competition, while the ‘BoilTheKettle’ team of third-year undergraduate students from HSE Faculty of Computer Science took second place. The bronze medal was awarded to the team from Central University, and the audience award went to the ‘Makaki v atake’ (‘Macaques in Attack’) team from the Moscow State University. All participants received prizes from Sber and other gifts.
Director of the AI and Digital Science Institute, Head of the Joint Department with Sberbank ‘Financial Technologies and Data Analysis’
‘The Joint Department with Sberbank together with the Hackathon Club held the largest hackathon at the faculty so far, with more than 350 participants taking part in the event. I would like to thank Sber ‘Risks’ Division for setting the task and participating in the expert committee, and the team from DS Works.ru platform from Cloud.ru for the infrastructure allowing us to automatically evaluate the quality of students' solutions.’
Managing Director — Head of the Research Centre, Risks Division, Sber
‘The hackathon is a unique event. It embodies our commitment to innovation and the development of artificial intelligence. The task of determining the gender of the client for banking transactions, which we set for the participants, reflects our desire to constantly improve the quality of services and personalise our service for each client. Hundreds of young artificial intelligence specialists took part in this hackathon. I would like to thank HSE Faculty of Computer Science for their cooperation and support in organising this event. Our joint efforts will help attract new talented specialists in the field of AI.’
Data scientist, Cloud.ru
'This event turned out to be not only a source of inspiration for students, but also an excellent example of successful integration with current business tasks. The hackathon not only gave the participants an opportunity to demonstrate their professionalism, but also presented advanced technologies and innovations in the field of machine learning.'
First place — ‘Misiskovo’ team
2nd-year student of the ‘Data Science’ master’s programme, Skolkovo Institute of Science and Technology
'The atmosphere of the competition was exciting, and the part with the defense of solutions added interactivity and tested our ability to present and defend our ideas. I was glad to meet a lot of new people, as the exchange of ideas and joint work on the solution creates a favorable atmosphere for growth and development.'
Second place — ‘BoilTheKettle’ team
3rd-year student of the ‘Software Engineering’ programme, HSE University
'HSE Sber ML Hack was the first ML hackathon for me. The organisers have done a lot to make it interesting and convenient for the participants to work on the task: there was a leaderboard, and a large prepared dataset. Experts from SBER provided useful recommendations to the participants, which, I think, can be applied in real life situations.
The ‘BoilTheKettle’ team (Shamil Ziganshin, Maxim Kaverin and Viktor Demyanenko) includes some outstanding ML specialists from the Software Engineering programme, which is one of the keys to our success. I am grateful to the organisers of the hackathon and glad that my university has the opportunity to put our knowledge into practice in a competitive format, especially together with industrial companies. This really motivates us to work hard.'
Third place — Central University team
4th-year student of the Information Science and Computation Technology, HSE MIEM, ‘Academy of Data Science’ programme, Central University
‘The students from Central University and I decided to start participating in hackathons with a team representing our university. Our choice fell on a friendly hackathon from the HSE Faculty of Computer Science and Sber. We are glad that we managed to win a prize and enjoy the unforgettable experience of participating in the hackathon!’
Audience Award — ‘Makaki v atake’ team
3rd-year student of the ‘Fundamental and Applied Physics’ programme, MSU
‘We will definitely remember this hackathon. During these two days, we managed to be initially sad that we were unable to send a solution, but then we had a lot of fun coming up with memes and making a presentation to defend our solution.’
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.
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).
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.
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.
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.
Joint Project of Scientists from HSE University and Surgut State University to Help Prevent Recurrent Heart Attacks and Strokes
One of the winning projects of a competition held by HSE University’s Mirror Laboratories last June focuses on the use of machine learning technologies to predict the outcomes of acute coronary syndrome. It is implemented by HSE University’s International Laboratory of Bioinformatics together with the Research and Educational Centre of the Medical Institute at Surgut State University. Maria Poptsova, Head of the International Laboratory of Bioinformatics and Associate Professor at HSE University’s Faculty of Computer Science, talks about how this joint project originated, how it will help patients, and how work to implement it will be organised.
On August 28–30, HSE University’s Faculty of Computer Science held the 4th Summer School on Machine Learning in Bioinformatics. This year, 670 people registered for the event, and over 300 visited in person. The programme included lectures and seminars on various spheres of bioinformatics: applied bioinformatics and the bioinformatics of DNA, RNA, and proteins; elementary genomics; modern methods of data analysis and molecular biology. The lectures were complemented by practical tasks aimed at different levels of knowledge.
Fall into ML 2023: HSE University’s Faculty of Computer Science Organises Conference on Machine Learning
On October 26–28, HSE University’s Institute of Artificial Intelligence and Digital Sciences at the Faculty of Computer Science will hold a conference titled Fall into ML 2023 withsupport from the HSE University AI Research Centre . The event is dedicated to promising directions of fundamental AI development.
HSE Researchers Examine Wellbeing of Russian Social Media Users and Rank Public Holidays by Popularity
Researchers of the HSE Graduate School of Business trained a machine-learning (ML) model to infer users' subjective wellbeing from social media posts. Having processed 10 million tweets, the researchers compiled a rating of holidays celebrated in Russia based on their popularity. The New Year tops the list, but Russian-speaking users of Twitter are also happy to celebrate Defender of the Fatherland Day, International Women's Day, and Halloween. The study findings have been published in PeerJ Computer Science.
A group of researchers from the HSE Faculty of Computer Science and the Sber AI Lab has increased the speed of gradient boosting, one of the most efficient machine learning algorithms. The proposed approach will make it possible to solve classification and regression problems faster. The results of the work were presented at the NeurIPS conference.