Seyed Abolfazl Hosseini | Communication Systems | Best Researcher Award

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Dr. Seyed Abolfazl Hosseini | Communication Systems | Best Researcher Award

Faculty member | Islamic Azad University | Iran

Dr. Seyed Abolfazl Hosseini is a distinguished faculty member in the Department of Electrical Engineering at Islamic Azad University, Tehran, Iran, specializing in Communication Systems Engineering and Computer Science. He holds a Ph.D. and M.Sc. in Electrical Engineering (Communications Systems Engineering) from Tarbiat Modares University and K.N. Toosi University of Technology, respectively, and a B.Sc. in Control Engineering from Sharif University of Technology. Over his academic career, Dr. Hosseini has served in several leadership capacities, including Dean of the Electrical and Electronics Research Centre, Dean of the Engineering Faculty, and Director of the Department of Communications Engineering. His professional experience extends beyond academia, having served as CEO of Pars Kelend Co., where he managed projects in electronic surveillance, IoT, AI, and network services, and as an expert engineer at the Tehran Traffic Control Company, where he developed remote toll systems and air quality detection methods using image processing. His research primarily focuses on hyperspectral image analysis, digital signal and image processing, machine learning, cryptography, and MIMO communication systems. Dr. Hosseini has authored numerous high-impact publications in leading journals such as IEEE Access, Earth Science Informatics, and Remote Sensing Letters, contributing novel methods in feature reduction, watermarking, and energy-efficient communications. His technical expertise spans rational function approximation, fractal theory, and advanced machine learning algorithms applied to remote sensing and data compression. A dedicated educator and mentor, he has supervised many M.Sc. and Ph.D. candidates and actively participated in developing technical standards and research-driven industrial collaborations. Through his integrated contributions to academia, research, and technology innovation, Dr. Hosseini continues to advance modern communication and computational systems.11 Citations, 3 Documents, 2 h-index.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Hosseini, S. A.*, & Ghassemian, H. (2016). Rational function approximation for feature reduction in hyperspectral data. Remote Sensing Letters, 7(2), 101–110. Citations: 42.

2. Hosseini, S. A.*, & Ghassemian, H. (2015). Hyperspectral data feature extraction using rational function curve fitting. International Journal of Pattern Recognition and Artificial Intelligence. Citations: 23.

3. Hosseini, S. A.*, & Ghassemian, H. (2013). A new hyperspectral image classification approach using fractal dimension of spectral response curve. Proceedings of the Iranian Conference on Electrical Engineering (ICEE). Citations: 17.

4. Hosseini, A., & Ghassemian, H. (2012). Classification of hyperspectral and multispectral images by using fractal dimension of spectral response curve. 20th Iranian Conference on Electrical Engineering (ICEE), 1452–1457. Citations: 19.

5. Beitollahi, M., & Hosseini, S. A.* (2018). Using Savitsky–Golay smoothing filter in hyperspectral data compression by curve fitting. Proceedings of the Iranian Conference on Electrical Engineering (ICEE). Citations: 15.

Milad Samady Shadlu | Signal Processing | Best Researcher Award

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Dr. Milad Samady Shadlu | Signal Processing | Best Researcher Award

Senior Researcher | Islamic Azad University | Iran

Dr. Milad Samady Shadlu is a distinguished lecturer at the University of Applied Science and Technology of Iran, specializing in Power Electronics, Renewable Energy Systems, and Control Engineering. He holds a Ph.D. in Electrical Engineering with a focus on Power Systems and Converters. Dr. Shadlu’s expertise spans the design, modeling, and control of high-power converters and inverters, multilevel converter systems, renewable energy integration, and maximum power point tracking (MPPT) methods for photovoltaic applications. With a strong academic foundation in control strategies and optimization methods, he has led and collaborated on numerous research projects focused on enhancing power system stability, harmonic mitigation, and fault diagnosis in renewable and grid-connected systems. Dr. Shadlu’s research portfolio comprises over twenty-four publications in reputed journals and international conferences, including notable works on MPPT algorithms, model predictive control, and fault analysis in modular multilevel converters and HVDC systems. He has authored and translated several books in the fields of energy storage, converter technology, and solar power generation, reflecting his commitment to academic knowledge dissemination. As an educator, he has taught a wide range of courses in electrical and control engineering and was honored as the Best Lecturer by the University of Applied Science and Technology of North Khorasan. His recognitions include the Best Researcher Award from the Young Researchers and Elite Club of North Khorasan Province. Dr. Shadlu’s current research focuses on fault detection in modular multilevel converters, hybrid control strategies combining extremum seeking and model predictive control methods for PV systems, and advanced control mechanisms for microgrids and active filters. With a robust record of scholarly output, including highly cited works on power converter control and renewable energy applications, Dr. Milad Samady Shadlu stands as an influential figure in modern power electronics research. 133 Citations, 24 Documents, 6 h-index.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Fatemi, S. M., Shadlu, M. S.*, & Talebkhah, A. (2019). Comparison of three-point P&O and hill climbing methods for maximum power point tracking in PV systems. Proceedings of the 10th International Power Electronics, Drive Systems and Technologies Conference (PEDSTC), IEEE. Citations: 33.

2. Shadlu, M. S.* (2019). Comparison of maximum power point tracking (MPPT) algorithms to control DC-DC converters in photovoltaic systems. Recent Advances in Electrical & Electronic Engineering, 12(4), 355–368. Citations: 19.

3. Shadlu, M. S.* (2018). A comparative study between two MPPT algorithms for photovoltaic energy conversion system based on modular multilevel converter. Proceedings of the Iranian Conference on Electrical Engineering (ICEE), IEEE. Citations: 16.

4. Talebkhah, A., Shadlu, M. S.*, & Fatemi, S. M. (2019). Control strategy of a single-phase active power filter with adjustable DC link capacitor voltage for THD reduction in non-linear loads. Proceedings of the 10th International Power Electronics, Drive Systems and Technologies Conference (PEDSTC), IEEE. Citations: 14.

5. Shadlu, M. S.* (2017). Fault detection and diagnosis in voltage source inverters using principal component analysis. Proceedings of the 4th IEEE International Conference on Knowledge-Based Engineering and Innovation (KBEI). Citations: 14.