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News
October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.

 

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Artificial Intelligence in Humanitarian Projects of the World Food Program

Scientific and Technical Information Processing. 2026. Vol. 53. No. 2. P. 155–161.
Fomina Y., Guseva M. N., Izz Eldin A. M.

This study examines the potential of artificial intelligence (AI) to improve the effectiveness of the World Food Program (WFP). Focusing on complex humanitarian situations, it explores the ability of AI to address operational inefficiencies by streamlining logistics, reducing costs, and improving decision-making in crises. It begins by developing a conceptual framework based on case studies of AI use in such areas as earthquake relief in Nepal (International Red Cross), COVID-19 monitoring using BlueDot algorithms (World Health Organization), and the use of AI in UNICEF education initiatives, to demonstrate the effectiveness of AI technologies such as predictive analytics and machine learning. These examples highlight challenges in scalability and ethical governance of AI tools when applied to humanitarian projects. The study focuses on analyzing WFP AI-based projects and identifying challenges such as skills shortages, data privacy issues, resistance to technological change, expected high implementation costs, and weak digital infrastructure in crisis regions. While WFP projects such as SCOUT, SHAPES, and SKAI ensure more efficient and sustainable delivery of humanitarian aid, the limited adoption of AI by WFP highlights the need for further innovation.

Language: English
DOI
Text on another site
Keywords: managementpredictive analyticsResource OptimizationAI (artificial intellence)humanitarian aidWorld Food Programme
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