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August 13, 2026
‘Working with AI Solves a Wide Range of Engineering Problems
Artificial intelligence is a working tool based on a balanced combination of algorithms and engineering. Experts and doctoral students from the HSE Moscow Institute of Electronics and Mathematics explain how AI technologies can improve an application, device, or system, and what engineering tasks are solved in the process.
August 12, 2026
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Whatever task Saraa Ali, Junior Research Fellow at the Laboratory of Methods for Big Data Analysis (LAMBDA) of the AI and Digital Science Institute (HSE Faculty of Computer Science), is working on, she thinks about how it can benefit people. She told the Young Scientists of HSE University project about her large family, diagnosing three-phase motors, and her dream of building a children’s home in her native country.
August 11, 2026
‘The Peak of Stupidity and ‘The Valley of Despair: HSE Economists Propose an Explanation for the Dunning–Kruger Effect
The Dunning–Kruger effect, which describes a sharp surge in self-confidence among beginners followed by an equally rapid decline as they gain experience, can be explained by the nature of the learning process and the acquisition of new knowledge. This conclusion was reached by Andrey Vorchik of the HSE Faculty of Economic Sciences together with independent researcher Murat Mamyshev. They developed a mathematical model of learning and demonstrated how subjective confidence is formed and changes as knowledge accumulates, as well as how teachers can reduce the ‘valley of despair’ experienced by learners.

 

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Разработка модели рейтинговой системы оценки качества предоставляемых водителями услуг в компаниях –агрегаторах такси

Бизнес-информатика. 2022. Т. 16. № 4. С. 68–81.
Shevgunov T., Вавилова Ж. А., Kravchenko T. K., Левченко Л. Л.

  This paper deals with the problem of quantitative description and improvement of the quality of the service provided by taxi aggregator companies working on the Russian market. This problem seems to be insufficiently addressed in open research publications due to its high specificity, though some research aiming at searching the quality metrics have been conducted for some companies worldwide. The goal of the current research is mathematical formalization of a rating system assessing the driver service quality that allows one to design a parametrically tunable model. The proposed mathematical model of the rating system is described by means of a state graph where the transition from a vertex to another happens when the explicitly written conditions are satisfied. We show that the rating evaluation for a driver remaining in the active can be carried out by means of linear filtration performed as digital signal processing of the time series consisting of the scores which are given to the driver by their passengers. The type and waveform of the filter impulse response is suggested. The A/B-test conducted for the group of drivers working with a taxi aggregator proved the fact that the integral metric of service quality is sensitive to changes in the parameters of the proposed rating system; this eventually led to a decrease in the rate of taxi rides accompanied with a negative client experience. The rating system model developed can be utilized to increase the quality of the service provided by the taxi aggregator by means of more effective differentiation of the drivers, while the subsequent optimization of the rating system parameters can serve as a tool for achieving indicators supporting the strategic goals of the company.

Research target: Economics and Management Computer Science Electronics and Electrical Engineering
Language: Russian
DOI
Text on another site
Keywords: рейтинговая системацифровая обработка сигналовrating systemdigital signal processingграф состоянийthe state graphtaxi aggregatordriver ratinglinear filtering агрегатор такси водительский рейтинглинейная фильтрация
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