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.
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.
Researchers at the HSE FCSAI 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.
The paper presents a detailed catalog of undue techniques used by unscrupulous customers to design corrupt tenders. It was developed in 2019-2021 as part of a project to study corruption in Russian public procurement. The catalog seeks to contribute to enhancing corruption prevention and detection methods. It can also inform the design of public procurement ...
Dmitry Ivanov, Alexander Nesterov, , in: EC '19 Proceedings of the 2019 ACM Conference on Economics and Computation.: Association for Computing Machinery (ACM), 2019. P. 69–70.
We propose a novel machine-learning-based approach to detect bid leakage in first-price sealed-bid auctions. We extract and analyze the data on more than 1.4 million Russian procurement auctions between 2014 and 2018. As bid leakage in each particular auction is tacit, the direct classification is impossible. Instead, we reduce the problem of bid leakage detection ...
The papers in these Proceedings were presented at the 20th ACM Conference on Economics and Computation (EC'19), held between June 24 and 28, 2019, as part of the 2019 ACM Federated Computing Research Conference in Phoenix, Arizona, USA. Since 1999 the ACM Special Interest Group on Electronic Commerce (SIGecom) has sponsored EC, the leading scientific ...