HSE University Strategic Development

Research & Expertise

'Multidisciplinary Expertise Must Be Grounded in a Deep Understanding of Country Specifics'

'Multidisciplinary Expertise Must Be Grounded in a Deep Understanding of Country Specifics'
During the Russia—Islamic World: KazanForum held in Kazan, experts from the HSE Institute for Public Administration and Governance (IPAG) presented the results of studies analysing the potential for establishing multimodal transport and logistics hubs along international transport corridors. One of the key sessions titled The International North–South Transport Corridor and attended by Deputy Prime Ministers Vitaly Savelyev and Marat Khusnullin highlighted the progress towards attaining the objective set by Russian President Vladimir Putin regarding the advancement of Russia's foreign trade potential.

'Global Dialogue about the Future': Key Topics of Expert Lectures at HSE St Petersburg International Partners' Week

'Global Dialogue about the Future': Key Topics of Expert Lectures at HSE St Petersburg International Partners' Week
The International Partners' Week at HSE University-St Petersburg united more than 100 representatives of leading universities from 23 countries. During the large forum, specialists of the campus, invited experts and international partners took part in panel discussions on artificial intelligence, the use of 'soft power', shaping a new generation of leaders and many other topics.

‘Services Must Be Flexible’: How Governments Can Use Artificial Intelligence

‘Services Must Be Flexible’: How Governments Can Use Artificial Intelligence
The HSE International Laboratory for Digital Transformation in Public Administration held a roundtable titled ‘Artificial Intelligence in Public Administration: Current Trends.’ Scholars from Israel, China, and Russia discussed which public services AI can enhance and what key factors must be considered when adopting new technologies.

HSE Scientists Win Prestigious International Prize in Fundamental Physics

Large Hadron Collider
The 2025 Breakthrough Prize in Fundamental Physics has been awarded to the international collaborations of experiments at the Large Hadron Collider (LHC) at CERN, including the LHCb collaboration, in which researchers from HSE University have participated.

IX All-Russian Scientific Student Conference: Supporting Early-Career Scientists

IX All-Russian Scientific Student Conference: Supporting Early-Career Scientists
The IX All-Russian Scientific Student Conference has taken place at the Nizhny Novgorod campus of HSE University, bringing together almost 200 early-career researchers and experts from 14 cities across Russia, from Kaliningrad to Vladivostok, as well as representatives from the African continent.

Cerium Glows Yellow: Chemists Discover How to Control Luminescence of Rare Earth Elements

Cerium Glows Yellow: Chemists Discover How to Control Luminescence of Rare Earth Elements
Researchers at HSE University and the Institute of Petrochemical Synthesis of the Russian Academy of Sciences have discovered a way to control both the colour and brightness of the glow emitted by rare earth elements. Their luminescence is generally predictable—for example, cerium typically emits light in the ultraviolet range. However, the scientists have demonstrated that this can be altered. They created a chemical environment in which a cerium ion began to emit a yellow glow. The findings could contribute to the development of new light sources, displays, and lasers. The study has been published in Optical Materials.

Genetic Prediction of Cancer Recurrence: Scientists Verify Reliability of Computer Models

Genetic Prediction of Cancer Recurrence: Scientists Verify Reliability of Computer Models
In biomedical research, machine learning algorithms are often used to analyse data—for instance, to predict cancer recurrence. However, it is not always clear whether these algorithms are detecting meaningful patterns or merely fitting random noise in the data. Scientists from HSE University, IBCh RAS, and Moscow State University have developed a test that makes it possible to determine this distinction. It could become an important tool for verifying the reliability of algorithms in medicine and biology. The study has been published on arXiv.

Artificial Intelligence as a Catalyst for Sustainable Development

Artificial Intelligence as a Catalyst for Sustainable Development
Artificial intelligence is transforming every aspect of life, expanding both our capabilities and our boundaries. At the same time, it presents new challenges for humanity, including concerns about safety, ethics, and environmental sustainability. Today, each neural network leaves a significant carbon footprint. However, with responsible management, AI has the potential to benefit the planet and become a cornerstone of a sustainable future economy. Panos Pardalos, Academic Supervisor of the Laboratory of Algorithms and Technologies for Network Analysis at the HSE Campus in Nizhny Novgorod, emphasised this point as he addressed the XXV Yasin (April) International Academic Conference on Economic and Social Development.

HSE Develops Its Own MLOps Platform

HSE Develops Its Own MLOps Platform
HSE researchers have developed an MLOps platform called SmartMLOps. It has been created for artificial intelligence researchers who wish to transform their invention into a fully-fledged service. In the future, the platform may host AI assistants to simplify educational processes, provide medical support, offer consultations, and solve a wide range of other tasks. Creators of AI technologies will be able to obtain a ready-to-use service within just a few hours. Utilising HSE’s supercomputer, the service can be launched in just a few clicks.

Russian Scientists Reconstruct Dynamics of Brain Neuron Model Using Neural Network

Russian Scientists Reconstruct Dynamics of Brain Neuron Model Using Neural Network
Researchers from HSE University in Nizhny Novgorod have shown that a neural network can reconstruct the dynamics of a brain neuron model using just a single set of measurements, such as recordings of its electrical activity. The developed neural network was trained to reconstruct the system's full dynamics and predict its behaviour under changing conditions. This method enables the investigation of complex biological processes, even when not all necessary measurements are available. The study has been published in Chaos, Solitons & Fractals.