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 with support from the HSE University AI Research Centre . The event is dedicated to promising directions of fundamental AI development.
The forum will cover topics such as general machine learning issues, deep neural networks, reinforcement learning, applications of machine learning in industry, natural, and social sciences, healthcare, and climate science, as well as language models, computer vision, optimisation, robotics, trusted AI, autonomous vehicles, etc.
The conference will be held in an A* format. Participants will enjoy a busy three-day programme featuring:
two panel discussions: ‘Science in Academia and Industry’ and ‘Strong AI: Risks and Benefits’
four workshops: ‘Diagnostics of Neural Networks’, ‘Artificial Intelligence in Physics’, ‘Reinforcement Learning’, and ‘AI in Biology and Medicine’
reports and a poster session
Alexey Naumov, organiser of Fall into ML
‘For the second year in a row, we are holding a conference at which almost all Russian authors of A* publications in the field of AI will give presentations and present posters. The highlight of the conference is the poster session, in which all authors participate. This format makes it much easier to communicate with colleagues and ask them questions. I hope that this year, the conference will be as successful as last year and become the main scientific event of the year on AI in the country.’
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.
On September 4, the HSE University building on Pokrovsky Bulvar hosted ARTificial Fest, an event devoted to neural network art. The festival was organised by the HSE University Faculty of Creative Industries, the HSE Career centre, and the Chisty List (‘Blank Page’) student organisation. The event was open not only to students and staff of HSE University, but also to anyone interested in the blending of machine algorithms and art.
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.
At Sarov Technopark, Researchers from HSE Faculty of Computer Science Discussed AI for Data Analysis in Physics
The Laboratory of Methods for Data Analysis of the HSE Faculty of Computer Science, in collaboration with the All-Russian Research Institute of Experimental Physics (RFNC-VNIIEF, Sarov) and the National Centre for Physics and Mathematics, recently held the Second All-Russian School-Seminar on High Energy Physics and Accelerator Technology.
From July 18 to October 15, 2023, the HSE University Faculty of Computer Science and AI Centre invite those interested to take part in the online Binary Super Resolution Challenge (BSRC-2023). The top 50 teams will receive prizes, and the top three will receive cash prizes.
Researchers at the HSE Artificial Intelligence Centre have created software for predicting the location of elements of the human genome. The scientists used deep learning methods based on complex data on various human molecular components. The research followed the objectives of the ‘Artificial Intelligence’ federal project of the ‘Digital Economy’ national project.
Aleksey Kychkin, a researcher at the Laboratory for Interdisciplinary Empirical Studies (LINES), and Oleg Gorshkov, a research assistant at LINES, received a patent for a system that predicts the spatial distribution of harmful substances in atmospheric air using an artificial intelligence unit. The invention can be used for integrated planning and notification of the risks of atmospheric air pollution by harmful substances. The work was carried out under a grant from the HSE University Artificial Intelligence Centre. The HSE News Service spoke with Aleksey Kychkin about the benefits of the new system, its application, and how it came to life.
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.