Ivars Namatēvs

Mg.sc.ing.

Researcher

He has been working at EDI since 2020. His research interests focus on supervised and unsupervised machine learning, specifically the Joint Embedding Predictive Architecture (JEPA) for building global models, as well as the study of latent space geometry, decoupling, and dynamics using deep neural networks and explainable artificial intelligence, primarily in medical imaging.

Author and co-author of more than twenty SCOPUS-indexed scientific publications, not only in the field of medicine but also in research related to agriculture, construction, smart energy, and privacy protection.

Projects

Publications

2026
Differentially Private Federated Learning for Remaining Useful Life Prediction(opens in a new window)

Arturs Nikulins, Kārlis Freivalds, Ivars Namatēvs, Kaspars Sudars, Audris Arzovs, Wilhelm Söderkvist Vermelin, Madhav Mishra, Kaspars Ozols.

Applied Sciences, Vol. 16 (6), p. 2784 (raksta numurs), MDPI

DOI(opens in a new window)
2026
ConMonity: An IoT-Enabled LoRa/LTE-M Platform for Multimodal, Real-Time Monitoring of Concrete Curing in Construction Environments(opens in a new window)

Namatēvs, I., Gaigals, G., & Ozols, K.

Sensors, Vol. 26 (1), p. 14, MDPI
2025
Privacy Auditing of Lithium-Ion Battery Ageing Model by Recovering Time-Series Data Using Gradient Inversion Attack in Federated Learning(opens in a new window)

Kaspars Sudars, Ivars Namatēvs, Arturs Nikulins, Kaspars Ozols

Applied Sciences (Switzerland), Vol. 15 (10), MDPI
2025
Privacy Auditing of Lithium-Ion Battery Ageing Model by Recovering Time-Series Data Using Gradient Inversion Attack in Federated Learning(opens in a new window)

Sudars, K., Namatevs, I., Nikulins, A., & Ozols, K.

Applied Sciences, Vol. 15 (10), p. 5704, MDPI
2025
Privacy Auditing in Differential Private Machine Learning: The Current Trends(opens in a new window)

Ivars Namatevs, Kaspars Sudars, Arturs Nikulins, Kaspars Ozols

Applied Sciences, Vol. 15 (2), p. 647, MDPI

Ivars Namatēvs

Projects

Publications

Differentially Private Federated Learning for Remaining Useful Life Prediction(opens in a new window)

ConMonity: An IoT-Enabled LoRa/LTE-M Platform for Multimodal, Real-Time Monitoring of Concrete Curing in Construction Environments(opens in a new window)

Privacy Auditing of Lithium-Ion Battery Ageing Model by Recovering Time-Series Data Using Gradient Inversion Attack in Federated Learning(opens in a new window)

Privacy Auditing of Lithium-Ion Battery Ageing Model by Recovering Time-Series Data Using Gradient Inversion Attack in Federated Learning(opens in a new window)

Privacy Auditing in Differential Private Machine Learning: The Current Trends(opens in a new window)