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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

MemSARAD: Hybrid Spatial-Memory Modeling for Industrial Sensing Systems

Alina Kozhevnikova, Andrei Zakharov, Ilya Makarov

2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems - Posters and Demos (SenSys-Adjunct)•May 2026
Anomaly DetectionIndustrial AIIoTTime Series AnalysisSenSys
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2026

Benchmarking IoT Time-Series Anomaly Detection with Event-Level Augmentations

Dmitry Zhevnenko, Ilya Makarov, Aleksandr Kovalenko, Fedor Meshchaninov, Anton Kozhukhov, Vladislav Travnikov,

arXiv preprint arXiv:2602.15457•February 2026
Anomaly DetectionTime Series AnalysisIoTBenchmarkarXiv
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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
2025

SensorDBSCAN: Semi-Supervised Active Learning Powered Method for Anomaly Detection and Diagnosis

Petr Ivanov, Maria Shtark, Alexander Kozhevnikov, Maksim Golyadkin, Dmitry Botov, Ilya Makarov

IEEE Access•February 2025
DOI: https://doi.org/10.1109/ACCESS.2025.3537649
Anomaly DetectionFault DiagnosisActive LearningIndustrial AIIEEE Access
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