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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
‘I Would Like My Research to Help Make the World a Calmer and Better Place
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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Институциональные факторы размещения прямых иностранных инвестиций в предприятия российской пищевой промышленности

С. 324–327.
Gladysheva A. A., Ratnikova T. A.

Does the institutional environment in Russian regions significantly stimulate the inflow of foreign direct investment in Russian food industry enterprises or is the investor interested only in the size of a market? The sample of about 5000 food industry companies of different subindustries from different Russian regions is analyzed to give the answer to this question. The main idea of this investigation is to determine the institutional factors which effect the distribution of the FDI and to test whether the transport infrastructure in the region and in the neighboring ones plays an important role. The estimation of a multilevel binary model with spatial effects of analyzed factors gives the idea for the possible solution on the problem discovered above.

Language: Russian
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Keywords: прямые иностранные инвестициитранспортная инфраструктурарегионы РоссииRussian regionstransport infrastructure Foreign Direct Investment (FDI)предприятия пищевой промышленностиspatial lagsпространственные лагифактор агломерациимногоуровневая модель бинарного выбораfood industry companiesfactor of agglomerationmultilevel binary modelregional institutesрегиональные институты

In book

Системное моделирование социально-экономических процессов: труды 36-й Международной научной школы-семинара, г. Воронеж, 29 сентября – 4 октября 2013 г.
Воронеж: Издательский дом ВГУ, 2014.
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