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iMak AI Lab

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© 2026 iMak AI Lab

Publications

A collection of key scientific and applied works of the laboratory. In the future, the list can be linked to an external database or Google Scholar.

2026

Benchmarking 2D Latent Degradation Spaces for Monitoring-Ready PdM

Dmitry Zhevnenko, Ilya Makarov, Aleksandr Kovalenko

2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems - Posters and Demos (SenSys-Adjunct)•May 2026
predictive maintenanceRULRepresentation LearningBenchmarkSenSys
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2026

Kriging-Guided Fusion with Budget-Adaptive Learned Compression for Spatial Field Reconstruction in WSNs

Vladislav Kulikov, Boris Tolstokulakov, Aleksei Stepin, Mikhail Mozikov, Ilya Makarov

2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems - Posters and Demos (SenSys-Adjunct)•May 2026
Sensor NetworksIoTEdge AIRepresentation LearningSenSys
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2026

Beyond Isolated Clients: Integrating Graph-Based Embeddings into Event Sequence Models

Harry Proshian, Nikita Severin, Sergey Nikolenko, Ivan Kireev, Andrey Savchenko, Ivan Sergeev,

Proceedings of the ACM Web Conference 2026 (WWW)•April 2026
DOI: https://doi.org/10.1145/3774904.3792886
GNNSSLRepresentation LearningRecommender SystemsWWW
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2025

Poster: Car2Vec: Task-Agnostic Latent Embeddings from CAN Bus for Efficient V2X Communication

Aleksandr Kovalenko, Ahmad Ahmad, Alexander Karandeev, Alexey Maslov, Dmitry Zhevnenko, Ilya Makarov

Proceedings of the 31st Annual International Conference on Mobile Computing and Networking•November 2025
DOI: https://doi.org/10.1145/3680207.3765701
V2XSSLContrastive LearningRepresentation LearningMobiCom
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2025

Automation of input control of transistors using deep learning models and analysis of their latent space

AS Chernova, Fedor Pavlovich Meshchaninov, Dmitry Zhevnenko, Evgenii Sergeevich Gornev

Doklady Rossijskoj Akademii Nauk. Mathematika, Informatika, Processy Upravlenia•September 2025
DOI: https://doi.org/10.7868/S2686954325070239
MicroelectronicsAnomaly DetectionIndustrial AIRepresentation Learning