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News
October 1, 2026
HSE Researchers Show How Congenital Motor Disorders Affect Brain Development
Researchers from HSE University’s Institute for Cognitive Neuroscience have synthesised the findings of their previous studies on brain development in children with obstetric brachial plexus palsy and arthrogryposis. Their analysis shows that impaired motor function in early childhood not only limits children’s motor experience but also affects memory, categorical thinking, and information processing. The study has been published in Frontiers in Psychology.
October 1, 2026
Window into the Body: Scientists Develop Neural Network to Detect Risk of 15 Diseases from Retinal Images
Russian universities, with the participation of HSE University, Sber, and Z-union, have developed a neural network that can simultaneously assess the risk of 15 types of pathology from retinal photographs, including not only eye diseases but also cardiovascular conditions. The AI system can help clinicians detect potentially concerning changes at an early stage, identify signs reflecting the condition of retinal blood vessels, and determine whether a patient may need further examination. The paper has been published in Frontiers in Medicine.
September 30, 2026
'We Did Not Limit the Time for Questions'
The International Laboratory for Supercomputer Atomistic Modelling and Multi-Scale Analysis at HSE University held a major conference on molecular dynamics. Participants had the opportunity to attend all the presentations, while speakers were given as much time as they needed to answer questions. The HSE News Service interviewed Grigory Smirnov, Head of the Laboratory, and Genri Norman, Chief Research Fellow, about the conference preparations and the discussions it generated.

 

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MEDES '20: Proceedings of the 12th International Conference on Management of Digital EcoSystems

NY : Association for Computing Machinery (ACM), 2020.

Nowadays, we live in a world, in which independent entities such as individuals, organizations, services, software, and applications sharing one or several missions and focusing on the interactions and inter-relationships among them, are strongly connected. This situation gives rise to an intelligent environment namely «digital ecosystem». This latter includes different producers of data (the Web, Internet of Things, Sensors, etc.), consumers of data (end users, applications, systems, etc.), networking capabilities to ensure data transfer and sharing, data-enabled services, processes (including AI and Big Data), deployment infrastructures (e.g., Cloud computing), processing capabilities, visualization and reporting facilities. The services related to such an eco-system have to support new self-* properties such as self-management, self-healing, and self-configuration and at the same time satisfy non-functional requirements such as performance, security, data privacy, etc. During the past years, the International Conference on ManagEment of Digital EcoSystems (MEDES) has become one of the most important international scientific events to bring together researchers, developers and practitioners to discuss latest research issues and experiences in developing solutions to design, deploy, exploit and tune emerging ecosystems.

This year, the 12th International Conference on Management of Digital EcoSystems (MEDES'20) was supposed to be held in Abu Dhabi, UAE but was finally held from November 2nd - 4th, 2020 in virtual mode due to COVID-19 virus. It aimed at developing and bring together in virtual mode a diverse community from academia, research laboratories and industry interested in exploring the manifold challenges and issues related to web technologies and resource management of Digital Ecosystems and how current approaches and technologies can be evolved and adapted to this end.

Chapters
Big-Data Driven Digital Ecosystem Framework for Online Predictive Control
Suleykin A., Bakhtadze N., Panfilov Peter, , in: MEDES '20: Proceedings of the 12th International Conference on Management of Digital EcoSystems.: NY: Association for Computing Machinery (ACM), 2020. P. 92–95.
In this paper, Big-Data Driven Digital Ecosystem Framework (BDDDEF) for Online Predictive Control Systems is created. The proposed framework consists of different Agents, where each Agent is a distributed and virtual service. In our work, we provide solutions to the Big Data challenges in building Digital Ecosystems for Online Control including high volumes, velocity and ...
Added: February 5, 2021
Research target: Economics and Management Computer Science Natural Sciences Engineering and Technology
Priority areas: economics management business informatics engineering science
Language: English
Keywords: big dataData-drivendigital ecosystemAIdigital infrastructuredata-enabled services
MEDES '20: Proceedings of the 12th International Conference on Management of Digital EcoSystems
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