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iMak AI Lab

Research and products at the intersection of science and industry.

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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

Interactive Framework for Interpretable Fault Diagnosis with Graph Neural Networks

Alexander Kozhevnikov, Maria Shtark, Petr Ivanov, Aleksandr Kovalenko, Dmitry Zhevnenko, Viacheslav Vasilev,

2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems - Posters and Demos (SenSys-Adjunct)•May 2026
GNNFault DiagnosisExplainable AIIndustrial AISenSys
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2026

Parallel Graph Neural Network Ensemble with Learnable Adjacency Matrices for Efficient Human Activity Recognition

Aleksandr Kovalenko, Miron Makhlin, Dmitry Zhevnenko, Artem Nikonorov, Ilya Makarov

2026 ACM/IEEE International Conference on Embedded Artificial Intelligence and Sensing Systems - Posters and Demos (SenSys-Adjunct)•May 2026
GNNHuman Activity RecognitionIoTSenSys
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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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2026

Framework GNN-AID: Graph Neural Network Analysis, Interpretation and Defense

Kirill Lukianov, Mikhail Drobyshevskiy, Georgii Sazonov, Mikhail Soloviov, Ilya Makarov

Proceedings of the AAAI Conference on Artificial Intelligence•March 2026
GNNExplainable AITrustworthy AIAAAI
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2025

Discovery of chemically modified higher tungsten boride by means of hybrid GNN/DFT approach

Nikita Matsokin, Roman Eremin, Anastasia Kuznetsova, Innokentiy Humonen, Aliaksei Krautsou, Vladimir Lazarev,

npj Computational Materials•June 2025
Materials ScienceGNNChemistryAI for Sciencenpj Computational Materials
2025

Impact of crystal structure symmetry in training datasets on GNN-based energy assessments for chemically disordered CsPbI3

Aliaksei Krautsou, Innokentiy Humonen, Vladimir Lazarev, Roman Eremin, Semen Budennyy

Scientific Reports•March 2025
Materials ScienceGNNChemistry