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News
August 25, 2026
Scientists Develop Algorithm for More Reliable Processors in Data Centres
Researchers from HSE MIEM and Samara University have developed the LRF-3D algorithm to automatically bypass idle nodes in three-dimensional networks-on-chip. Thanks to its hierarchical architecture, the algorithm outperforms existing solutions in both speed and path accuracy, improving processor reliability for use in data centres, supercomputers, and AI computing. The source code and test results are publicly available.
August 24, 2026
Researchers Develop Method for Direct Generation of Regulatory DNA
Researchers at HSE University have developed a model for generating promoters and enhancers—DNA sequences that regulate gene activity. The model works directly with DNA nucleotides, without first transforming them into a continuous numerical representation. This solution could be useful for applications in synthetic biology and gene therapy. The study results were presented at the ICLR 2026 Workshop ‘Generative AI in Genomics (Gen^2): Barriers and Frontiers.’
August 21, 2026
Social Integration: At the Crossroads of Knowledge and Values
The International Laboratory for Social Integration Research (ILSIR) at HSE University studies the challenges faced by vulnerable groups and explores ways to help them participate fully in everyday life. To develop effective solutions, the laboratory’s researchers combine cutting-edge methods with practical fieldwork. In this interview with the HSE News Service, Laboratory Head Elena Iarskaia-Smirnova discusses the laboratory’s work.

 

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Do accelerators promote the growth of startups? Analysing the effectiveness of startup accelerators through the lens of big data

Technology Analysis & Strategic Management. 2025. Vol. 37. No. 12. P. 2889–2905.
Tekic Z., Hrynkevich A., Malyy M.

Startup accelerators have emerged as a prominent mechanism for supporting early-stage ventures, yet questions persist regarding their effectiveness. This study addresses the gap in understanding by investigating whether accelerators promote the growth of all startups or only those already successful. Leveraging web-search traffic data as a proxy for startup growth, trend analysis is used to assess the impact of acceleration. Using a sample of 103 startups from Y Combinator from 2017 and 2018, the analysis reveals that accelerators aid startups regardless of their pre-acceleration growth status (i.e. growing, stagnating or declining). Furthermore, non-growing startups selected for acceleration exhibit better chances of achieving growth post-acceleration compared to already growing counterparts. These findings add important insights into the understanding of accelerators’ effectiveness, demonstrating that accelerators work for all selected startups, not only for those already successful. Our findings offer two important practical implications: policymakers and stakeholders should continue supporting accelerators due to their positive impact on startup growth and reducing uncertainty; startups should focus on their future potential and vision when applying for an acceleration program. Using the introduced approach, future research could compare the effectiveness of accelerators offering offline and online programs, targeting specific industry sectors, and across different periods.

Research target: Economics and Management
Language: English
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Keywords: effectivenessgrowthstartupGoogle Trendsstart-up accelerator
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