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September 21, 2026
Researchers Develop Methodology to Assess the Quality of Legal Representation in Criminal Proceedings
Having a good defence attorney in criminal proceedings can largely determine whether a defendant retains their freedom, health and good name. Researchers at HSE University propose a method for predicting an attorney’s performance based on the outcomes of their previous cases. The methodology takes into account the severity of the charges, the complexity of the cases, and the most likely outcome, drawing on judicial statistics.
September 21, 2026
Algebra, Geometry, and AI: Russian and Vietnamese Mathematicians Discuss Current Research
A delegation of scientists from Hanoi visited the HSE Faculty of Computer Science and then took part in a Russian-Vietnamese conference in St Petersburg. The events were part of the three-year project ‘Flexibility and Computational Methods.’ Over the course of the project, the researchers have prepared joint publications and obtained new mathematical results.
September 18, 2026
When Pictures Hinder Understanding: Illustrations May Impede Learning of Abstract Ideas
Illustrations can help remember specific actions but do not always make abstract ideas easier to learn. Researchers from HSE University and Humboldt University compared how people learn from texts with different levels of abstractness. They found that participants remembered illustrations better and performed better on related tasks after reading a multimedia text about yoga asanas than after reading an abstract text about the Nash equilibrium. The findings could help improve the selection of illustrations for educational and informational materials. The study has been published in Learning and Instruction.

 

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Новая программная платформа для моделирования транспортных потоков с участием беспилотных автомобилей

Вестник ЦЭМИ. 2023. Т. 6. № 1. Статья 5.
Beklaryan A.

The article presents a new software platform for modelling traffic flows involving unmanned vehicles, using a number of advanced technological solutions, in particular, the FLAME GPU supercomputer agent modelling framework, intelligent software modules based on fuzzy and hierarchical clustering, genetic optimization algorithms, a subsystem for visualizing the state of agents-vehicles based on OpenGL, etc. As a result, it is possible to simulate the dynamics of road accidents and output traffic for various configurations of digital road networks within the “smart city” scale. The possibility of using the proposed software platform (implemented using C++ and FLAME GPU) is demonstrated for the problem of estimating the sensitivity of the total number of accidents in relation to important control parameters: arrival rate and average speed of unmanned ground vehicles interacting with usual ground vehicles and other agents of the intelligent transport system.

Research target: Mathematics Computer Science
Language: Russian
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Keywords: кластеризацияgenetic algorithmsгенетические алгоритмыclusteringинтеллектуальные транспортные системыagent-based simulationIntelligent transportation systemsFLAME GPUFLAME GPUunmanned vehiclesмультиагентное имитационное моделированиеautonomous transportбеспилотные автомобилиавтономный транспорт
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