Machine Learning Helps Improve Perovskite Solar Cells
A team of researchers from HSE MIEM, LPI RAS, and the University of Southern California have applied machine learning to the analysis of internal defects in perovskite solar cells and proposed ways to improve their energy efficiency. The findings of the study performed on the Cs2AgBiBr6 double perovskite can be used to develop more efficient and durable perovskite-based materials. The paper has been published in the Journal of Physical Chemistry Letters.
Russian Researchers Propose New Approach to Studying Facial Emotion Recognition
Researchers of the HSE University and the Southern Federal University (SFedU) have tested a new method for studying the perception of facial emotional expressions. They suggest that asking subjects to recognise emotional expressions from dynamic video clips rather than static photographs can improve the accuracy of findings, eg in psychiatric and neurological studies. The paper is published in Applied Sciences.
Mathematicians and Practicing Surgeons to Fight Venous Diseases
One million people in Russia suffer from venous diseases. The ‘Intelligent data analysis for healthcare information systems’ Mirror Lab project brings together expertise in mathematics and medicine in order to better diagnose various conditions in phlebology. Project leader Vasilii Gromov talked to The HSE LooK about its achievements and prospects.
Registration with presentation deadline - July 15, 2023