Ievgen Zaitsev Editor at IgMin Research
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Biography
Ievgen Zaitsev born in Kiev, Ukraine, 1983. Received the B.Tech. and M.Tech degrees in measurement engineering from National Technical University of Ukraine "Kyiv Polytechnic Institute", Kyiv, Ukraine, in 2005 and 2007, respectively. The Ph. D. degree in devices and methods of measurement electric and magnetic quantities from Institute of Electrodynamics, National Academy of Sciences of Ukraine, Kyiv, Ukraine, in 2012.
The Doctor of science degree in computer systems and components from Institute of Electrodynamics, NAS of Ukraine, Kyiv, Ukraine, in 2020. He is currently head of the department of theoretical electrical engineering and diagnostics of electrical equipment, Institute of Electrodynamics, National Academy of Sciences of Ukraine, Kyiv, Ukraine. He holds several patents, is the author of over 200 journals, conference papers, books and book chapters.
Research Interest
Sensor design and integration for power equipment fault diagnosing, renewable energy sources, distributed generation, smart grid, optoelectronics, device modelling and fabrication
Editor
Work Details
Department Head
Institute of Electrodynamics of the National Academy of Sciences of Ukraine
Theoretical electrical engineering and diagnostics of electrical equipment
Ukraine
0000-0003-3303-471X Contribution by Topic Area
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Which articles are now trending?
Research Articles
- Biomimetic Synthesis of Calcium Carbonate in Bile in the presence of Amino Acids
- Prevalence of Non-specific Low Back Pain Among Chinese Healthcare Workers (Surgeons and Surgical Nurses): A Multi-Center Survey Study
- Physical Activity and Lifestyle of Female Students of the Faculty of Health Sciences University of Applied Sciences in Tarnów (Poland)
- Screening for Sexually Transmitted Infections in Adolescents with Genitourinary Complaints: Is There a Still Role for Endocervical Gram Stains?
- Methodology of the Professional-Business Game for the Development of a Cadet Leader in Professional Training Courses (L-1B) of the Tactical Level of Military Education
- Enhancing Material Property Predictions through Optimized KNN Imputation and Deep Neural Network Modeling
