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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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Dividing Goods or Bads Under Additive Utilities

NRU Higher School of Economics , 2016. No. 147.
Bogomolnaia A., Moulin H., Sandomirskiy F., Yanovskaya E. B.
The Competitive Equilibrium with Equal Incomes is an especially appealing efficient and envy-free division of private goods when utilities are additive: it maximizes the Nash product of utilities and is single-valued and continuous in the marginal rates of substitution. The CEEI to divide bads captures similarly the critical points of the Nash product in the ecient frontier. But it is far from resolute, allowing routinely many divisions with sharply different welfare consequences. Even the much more permissive No Envy property is profoundly ambiguous in the division of bads: the set of ecient and envy-free allocations can have many connected components, and has no single-valued selection continuous in the marginal rates. The CEEI to divide goods is Resource Monotonic (RM): everyone (weakly) bene ts when the manna increases. But when we divide bads eciently, RM is incompatible with Fair Share Guarantee, a much weaker property than No Envy.
Research target: Computer Science Economics and Management Mathematics
Priority areas: economics mathematics
Language: English
Full text
Keywords: fair division of goodsfair division of badscompetitive equilibrium with equal incomesNash productenvy-freenessresource monotonicityindependence of lost bids
Publication based on the results of:
Algorithmic aspects of fair division problems (2016)
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