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Subject
News
September 11, 2026
How to Assess Students Knowledge in the Age of AI
A researcher at HSE University has proposed a flowchart to help lecturers decide how to assess students who use artificial intelligence. It shows where the use of AI should be restricted and where it can be incorporated into the learning process. The article has been published in IT Professional.
September 9, 2026
‘Balkan Hospitality Opens Doors: Studying Dialects on the Verge of Extinction
You cannot study spoken dialects from books. Instead, you need to go to a village, seek out its elders, and earn the trust of local residents before you can record hours of spontaneous stories. This is how Natalia Muravleva, Associate Professor at the Faculty of Humanities, conducts her research. Her internship in Serbia continued her long-standing study of dialects spoken by Macedonian settlers. In this interview, she discusses how diaspora cultural centres help researchers reach informants, why native speakers need to be interviewed only in their own language (otherwise, as she puts it, they may 'break'), and how a single field season helped her finalise her monograph. She also shares warm memories of autumn in Belgrade and of colleagues with whom grammar can be discussed in three languages at once.
September 9, 2026
Scientists Train Neural Network to Generate Process Plans from 3D Models
Researchers at the HSE FCS AI and Digital Science Institute have developed CAD2TechSpec, a framework that converts 3D models of mechanical parts into machining process plans—step-by-step instructions for machine tools. The solution aims to reduce the time required for the design and preparation of technical process documentation in mechanical engineering, aircraft manufacturing, and other high-tech industries. The study findings have been published in PeerJ Computer Science.

 

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The Professional Face: Gendered Executive Facial Cues and Follower Growth on LinkedIn

International Journal of Consumer Studies. 2026. Vol. 50. No. 2. Article e70178.
Marina Zavertiaeva, de Cabo R. M., Gimeno R., Contreras G.

This study investigates how gendered facial cues shape the visibility of executives personal brands on LinkedIn. Building on signaling theory, we analyze 5575 public executive profiles, extract facial metrics through machine-learning landmark detection, and model direct and indirect pathways to digital visibility outcomes proxied by follower counts using negative binomial regressions and generalized structural equation modeling (GSEM). Facial trustworthiness is strongly associated with follower counts for both genders, especially for women, while friendliness shows gender-opposite patterns, and attractiveness is not associated with the number of followers. Career capital (years of experience and number of roles) serves as a key mediator linking facial impressions to digital visibility outcomes. The study shows that trustworthiness can be an effective facial signal in professional digital markets; theorizes career capital as a signal-conversion mechanism; and shows how gendered role expectations can shape symbolic consumption on LinkedIn.

Research target: Economics and Management
Language: English
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DOI
Text on another site
Keywords: гендерные различияpersonal brandingперсональный брендингtrustworthinessfacial cues gender differencesвоспринимаемое довериеSignalling theoryсигнальная теорияfriendlinessLinkedInчерты лицадружелюбность
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