HSE Researchers Demonstrate Effectiveness of Machine Learning in Forecasting Inflation
Inflation is a key indicator of economic stability, and being able to accurately forecast its levels across regions is crucial for governments, businesses, and households. Tatiana Bukina and Dmitry Kashin at HSE Campus in Perm have found that machine learning techniques outperform traditional econometric models in long-term inflation forecasting. The results of the study focused on several regions in the Privolzhskiy Federal District have been published in HSE Economic Journal.
Ruthenium Complexes Can Accelerate the Development of New Medicines
A group of scientists at INEOS RAS, HSE University, and MIPT have synthesised catalysts containing a ruthenium atom and an aromatic ring. The scientists have isolated the mirror forms of these catalysts and investigated their effectiveness in producing heterocycles, which are commonly found in the structures of drugs. The research findings have been published in Chemical Communications.
‘Making Useful Acquaintances Quickly and Easily’
From the very beginning of their university years, HSE students start to develop their own start-up ideas. As a result, three graduates of the bachelor’s programme in Software Engineering of the HSE Faculty of Computer Science—Andrey Losyukov, Timofey Valov, and Alexander Kulakov—created the HiBye platform for networking at events. The students presented their project and discussed their start-up with the HSE News Service.