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Tag "HSE as a Global University"

‘Our Result Was Recognised Not Only Within the Project Defence but Also on International Scale’

‘Our Result Was Recognised Not Only Within the Project Defence but Also on International Scale’
This year, the European AI Conference (ECAI 2025) accepted an article titled ‘Multi-Agent Path Finding for Large Agents is Intractable’  by Artem Agafonov, a second-year student of the Applied Mathematics and Information Science Bachelor’s programme at HSE University’s Faculty of Computer Science. The work was co-authored by Konstantin Yakovlev, Head of the Joint Department with Intelligent Technologies of System Analysis and Management at the Federal Research Centre ‘Informatics and Management’ of the RAS and Associate Professor at the Faculty of Applied Sciences. In the interview, Artem Agafonov explained how he came up with the idea for the article and how he was able to present it at an A-level conference.

'Today, Human Existence Without Mathematics Is Difficult; Tomorrow, It Will Be Simply Impossible'

Valery Gritsenko
Mathematicians around the world share a common language and continue to collaborate despite the challenges of recent years. The hub of mathematical networking has been shifting to China, where scientists from various countries meet at conferences and other academic events. Partnerships with leading Chinese universities offer promising opportunities to strengthen existing ties and forge new ones. In this interview with the HSE News Service, Valery Gritsenko, Head of the HSE International Laboratory for Mirror Symmetry and Automorphic Forms, discusses this and other topics, including what AI is and why the state should engage with mathematicians.

Scientists Develop AI Tool for Designing Novel Materials

© iStock
An international team of scientists, including researchers from HSE University, has developed a new generative model called the Wyckoff Transformer (WyFormer) for creating symmetrical crystal structures. The neural network will make it possible to design materials with specified properties for use in semiconductors, solar panels, medical devices, and other high-tech applications. The scientists will present their work at ICML, a leading international conference on machine learning, on July 15 in Vancouver. A preprint of the paper is available on arxiv.org, with the code and data released under an open-source license.