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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.
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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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Andrey Vorchik studies happiness, delivers popular science lectures, and believes that science should address social issues as well. In an interview for the Young Scientists of HSE University project, he spoke about how emotions influence decision-making, the Bermuda Triangle formed by the bathroom, refrigerator, and bed, and the ideal formula for education.

 

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Developing and Using Indicators of Emerging and Enabling Technologies

Ch. 15. P. 349–380.
Gokhberg L., Fursov K., Miles I. D., Perani G.

The chapter focuses on the measurement of emerging technologies that have the potential to transform wide swathes of social and economic activity. The relevance of the topic is explained by the fact that the existing mechanisms of statistical accounting for a number of reasons fail to measure technologies that are at an early stage of development and still do not have specific applications. This results in a reduced ability to manage technology progress. Analyzing the lessons learned from statistical work around ICT and biotechnology, the authors propose a "three-dimensional" approach to the classification of technologies that covers all stages of the R&D cycle — from an idea to market launch of an end-user product or service. The basic components in measuring this area are the scientific base or origin of a given technology, its applications and the socio-economic impact. The authors demonstrate the scope for using technology Foresight to orient statistical work, and suggest that a combination of improved statistical monitoring of ongoing developments, and Foresight analysis of anticipated technology and technology applications, represents a powerful approach to achieving early footholds by way of indicators of emerging technologies in concrete circumstances. The chapter outlines the main requirements for such an approach to be effectively implemented and its results utilized; it concludes with proposals for future methodological and conceptual development.

 

 

 
Language: English
Full text
Text on another site
Keywords: Indicators of Emerging and Enabling Technologiestechnology statisticsinnovation indicatorsS&T indicators
Publication based on the results of:
Development of novel approaches to the analysis and modelling behavior of innovation actors (2013)

In book

Handbook Of Innovation Indicators And Measurement
Handbook Of Innovation Indicators And Measurement
Northampton, Cheltenham: Edward Elgar Publishing, 2013.
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