Ilia Kamyshev
PhD thesis: Decomposition of electric signals with constant fundamental frequency
Supervisor: Elena Gryazina
IDC Committee members: -
Biography:
Graduated from Skolkovo Institute of Science and Technology. Started doing research in the field of energy disaggregation. Master thesis is entitled “Non-Intrusive Load Monitoring (NILM) from Short-Term Current Patterns”. Several contributions were proposed: (i) novel method on large-scale datasets simulation for NILM; (ii) novel neural network architecture to decompose up to 54 different categories of appliances, where up to 10 can work simultaneously.
The goal of the PhD research is to develop a theory of decomposition of electric signals presented in the power grids. Focused on the analytical derivation of the novel method for energy disaggregation problem, its capabilities and limitations. Main areas of interest are deep learning, statistics and functional analysis.
Publications
[preprint] Kamyshev I, Kriukov D, Gryazina E. COLD: Concurrent Loads Disaggregator for Non-Intrusive Load Monitoring. arXiv preprint arXiv:2106.02352. 2021 Jun 4.
Conferences
- “NILM: achievements and challenges”. The 4th International Symposium on Smart Grid. Jinan, Shandong, China October 2021
2. “Fundamentals of Artificial Intelligence”. Artificial Intelligence for Electrical Engineering. IEEE Region 10 Educational Activities, IEEE Bombay Section Educational Activities Committee & RIT-IEEE Student Branch. Bombay, India October 2021
