Claudiu-Ionel Nicola | Systems Engineering | Best Research Award

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Dr. Claudiu-Ionel Nicola | Systems Engineering | Best Research Award

Lecturer/Scientific Researcher | University of Craiova | Romania

 

Short Bio 🌟

Claudiu-Ionel Nicola is an accomplished academic and researcher specializing in Systems Engineering, currently serving as a Lecturer at the University of Craiova, Romania. His expertise spans advanced control algorithms, embedded systems integration, and SCADA systems, with a keen interest in industrial automation and electric drives.

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Education 📚

Claudiu-Ionel Nicola earned his PhD in Systems Engineering from the University of Craiova, focusing on advanced control algorithms in embedded systems integrated into SCADA systems. He holds a Master’s degree in Systems Engineering and a Bachelor’s degree in Systems and Computer Engineering, both from the University of Craiova.

Experience 💼

With over a decade of experience at the National Institute for Research, Development and Testing in Electrical Engineering (ICMET), Claudiu-Ionel Nicola has been actively involved in research projects, numerical simulations, and software development for SCADA and embedded systems.

Research Interests 🧠

His research interests include system and process modeling, automation software, virtual instrumentation, data acquisition systems, SCADA systems, and control of electric drives in microgrids.

Award 🏆

Claudiu-Ionel Nicola received the 2023 Scientific Article Award for his work on DC-AC Converter Control Systems, recognized for its comparative performance analysis using robust and nonlinear controllers.

Publication 📖

Complementary analysis for DGA based on Duval methods and furan compounds using artificial neural networks

AM Aciu, CI Nicola, M Nicola, MC Nițu
Energies 14 (3), 588
SCADA systems architecture based on OPC and web servers and integration of applications for industrial process control
M Nicola, CI Nicola, M Duta, D Sacerdotianu
International Journal of Control Science and Engineering 8 (1), 13-21

Improvement of PMSM sensorless control based on synergetic and sliding mode controllers using a reinforcement learning deep deterministic policy gradient agent

M Nicola, CI Nicola, D Selișteanu
Energies 15 (6), 2208

Sensorless Predictive Control for PMSM Using MRAS Observer

M Nicola, CI Nicola
2019 International Conference on Electromechanical and Energy Systems

 

Nooshin Bigdeli | Energy systems | Best Researcher Award

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Prof.Dr.Nooshin Bigdeli | Energy systems | Best Researcher Award

Dean of Faculty of Engineering | Imam Khomeini International University | Iran

Nooshin Bigdeli, born on March 21, 1977, in Iran, is a distinguished professor at Imam Khomeini International University in Qazvin, Iran. She earned her Ph.D. in Electrical Engineering, specializing in Control, from Sharif University of Technology in Tehran in 2007. Her academic journey has been marked by significant contributions to Control Theory, Nonlinear Systems, Artificial Intelligence, Data Mining, and Energy System Management and Behavioral Analysis.

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Education 📚

Nooshin Bigdeli received her Ph.D. in Electrical Engineering with a specialization in Control from Sharif University of Technology, Tehran, Iran, in 2007.

Experience 💼

Since obtaining her Ph.D., Dr. Bigdeli has been a faculty member in the Control Engineering Department at Imam Khomeini International University, Qazvin, Iran.

Research Interest 🧠

Her research interests span Control Theory, Nonlinear Systems, Artificial Intelligence, Data Mining, and the Management and Behavioral Analysis of Energy Systems. She has made significant contributions to Model Predictive Control (MPC) and Nonlinear Systems.

Award 🏆

Dr. Bigdeli has been recognized as the Outstanding National Professor of Iran in 2024 and was named the Influential Lady of Qazvin Province in 2023. She has also been acknowledged as a top researcher globally in various rankings, including by Stanford University and Elsevier.

Publications 📄

Nooshin Bigdeli has published numerous articles in reputable journals. One notable publication is:

  • Optimal management of hybrid PV/fuel cell/battery power system: A comparison of optimal hybrid approaches
    Published in Renewable and Sustainable Energy Reviews in 2015.
    Cited 175 times.