Mohammad Reza Eesazadeh | Dynamic State Estimation | Best Researcher Award

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Mr. Mohammad Reza Eesazadeh | Dynamic State Estimation | Best Researcher Award

Mohammad Reza Eesazadeh at Sharif university of technology, Iran

Mr. Mohammad Reza Eesazadeh is a Ph.D. candidate in Electrical Engineering – Power at Sharif University of Technology (SUT), Tehran, specializing in synchro design for electric vehicles and machine learning applications in power systems. He holds an M.Sc. in Electrical Engineering from Shahid Beheshti University, where he focused on dynamic state estimation with non-Gaussian noises, and a B.Sc. in Electrical Engineering from University of Mohaghegh Ardabili. His work experience includes roles as an R&D expert and software developer in energy management systems and power system simulations. He has published research in prestigious journals like the IEEE Sensors Journal, and his research interests include power system modeling, wide-area measurement, and electrical machines.

Profile:

Education:

Mr. Eesazadeh is currently pursuing a Ph.D. in Electrical Engineering – Power at Sharif University of Technology (SUT), Tehran, Iran, where he is developing advanced synchro designs for electric vehicles (EVs) and exploring machine learning topics. He previously earned his M.Sc. in Electrical Engineering – Power Systems from Shahid Beheshti University (SBU), Tehran, graduating with a GPA of 16.28. His Bachelor’s degree in Electrical Engineering was obtained from University of Mohaghegh Ardabili, where he focused on fault current limiters. Mr. Eesazadeh has consistently ranked among the top students, including placing 2nd in the National University Entrance Exam for Ph.D. in 2021 and being in the top 3% for M.Sc. entrance exams.

Professional Experience:

Mr. Eesazadeh has diverse work experience as a software developer and R&D expert, particularly in the power systems sector. He has worked with Modje Niroo Company, Tehran, developing advanced state estimation and power flow modules for energy management systems. At the Research and Technology Deputy of SBU, he led a team to develop a power system simulator for Iran’s Electric Transmission Grid, combining MATLAB, C++, and DIgSILENT for real-time data estimation. His early work includes an internship at Ardabil Province Electricity Distribution Company, focusing on power system expansion planning.

Research Interests:

Mr. Mohammad Reza Eesazadeh’s research interests encompass a broad range of topics within electrical engineering, particularly in power systems and advanced technologies. His work focuses on power system modeling and analysis, with a special emphasis on developing dynamic state estimation techniques. He is also deeply engaged in wide-area measurement systems and system identification, applying data analytics and machine learning to enhance these processes. Additionally, Mr. Eesazadeh is interested in the development of electrical machines, especially for electric vehicles, and electromagnetic sensors such as resolvers and synchros. His innovative contributions to these fields are reflected in his research on improving power system operations and advancing sensor technologies.

Skills:

Mr. Mohammad Reza Eesazadeh possesses a diverse set of skills that span technical, analytical, and personal development areas. His technical expertise includes proficiency in specialized software such as MATLAB (Simulink and Script), DIgSILENT, Ansys Electrical, ePLAN, AutoCAD, and LabVIEW, as well as electrical design tools like ETAP and PSIM. He is also adept in programming languages, including C++, Python, C#, and SQL, leveraging these for tasks like power system analysis, state estimation, and data analytics. Additionally, Mr. Eesazadeh is skilled in various instrumentation and engineering design principles, and his experience in developing Energy Management Systems and SCADA modules further highlights his depth in the field. On the personal side, he is an effective communicator with strong teamwork, leadership, and problem-solving abilities, demonstrated through his roles in R&D teams and his supervision of graduate students. His commitment to self-learning and continuous improvement, combined with his ability to prioritize tasks and make informed decisions, further strengthens his professional profile.

Conclusion:

With his strong educational background, significant work experience, advanced technical skills, and impactful research contributions, Mr. Mohammad Reza Eesazadeh presents a compelling case for the Research for Best Researcher Award. His work in power systems, machine learning applications, and energy management systems positions him as a leader in his field.

Publication Top Noted:

  • Developed square-root cubature Kalman filter-based solution for improving power system state estimation with unknown inputs and non-Gaussian noise
    • Journal: Sustainable Energy, Grids and Networks
    • Volume: 40
    • Year: 2024
    • Article Number: 101523
    • Contributors: M.R. Eesazadeh, M.T. Ameli
    • Citations: 0
  • Development of a Multi-Turn Linear Variable Reluctance Resolver with Integrated Ferromagnetic Core
    • Journal: IEEE Sensors Journal
    • Year: 2024
    • Contributors: S.A. Seyed-Bouzari, M. Eesazadeh, F. Tootoonchian, Z. Nasiri-Gheidari
    • Citations: 0
  • Winding Selection for Wound-Rotor Synchro
    • Journal: IEEE Sensors Journal
    • Volume: 24(1)
    • Pages: 215-222
    • Year: 2024
    • Contributors: M.R. Eesazadeh, Z. Nasiri-Gheidari
    • Citations: 0

Seyed Iman Taheri | Power systems Award | Best Scholar Award

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Assist Prof Dr. Seyed Iman Taheri | Power systems Award | Best Scholar Award

Assistant Professor of Teaching at the University of Memphis, United States

Seyed Iman Taheri is an Assistant Professor of Teaching in the Department of Electrical and Computer Engineering at the University of Memphis. With a background in electrical engineering and a Ph.D. in Electrical Power Systems, their expertise lies in optimization, smart grids, control systems, renewable energy resources, and distributed generations. They are actively involved in research on designing and modeling distributed energy resources, placement of distributed generations, intelligent optimization algorithms, smart grids, virtual power plants, power systems of vessels, electric vehicles, cybersecurity, machine learning, deep learning, and big data. Their academic and research contributions demonstrate a commitment to advancing knowledge in electrical engineering and addressing challenges in sustainable energy systems.

Profile:

Education:

Seyed Iman Taheri has an impressive academic background in electrical engineering. They earned their Bachelor of Engineering in Electronics from Islamic Azad University in Iran, followed by a Master of Science in Power Electronics and Electrical Machinery from Shiraz University of Technology, Iran. Their academic journey culminated in a Ph.D. in Electrical Power Systems from the University of São Paulo in Brazil, where they focused on optimization strategies for increasing the penetration of distributed energy resources. This research aligns with their goal of contributing to a greener future through innovative energy solutions.

 

Professional Experience:

Seyed Iman Taheri has gained valuable experience in academia and research. They currently serve as an Assistant Professor of Teaching at the University of Memphis, a role they have held since August 2023. Prior to this position, they worked as a Post-Doctoral Fellow at the same university, focusing on research related to Virtual Power Plants from August 2022 to August 2023. Before joining the University of Memphis, Seyed Iman Taheri was a Research Scholar at the University of Central Florida (UCF), where they contributed to a project on real-time power system scheduling and optimization from December 2021 to July 2022.

 

Academic Experience :

Seyed Iman Taheri has been actively involved in academic teaching and support. They currently teach Electronics-I and the electronics laboratory at the University of Memphis, a role they have held since August 2022. Prior to this, they served as a Teacher Assistant at the University of Sao Paulo, where they assisted with the Electromechanical Energy Conversion laboratory from January 2020 to January 2021. These experiences have helped them develop a strong foundation in both teaching and practical aspects of electrical engineering.

Research Interests:

Seyed Iman Taheri is an Assistant Professor of Teaching in the Department of Electrical and Computer Engineering at the University of Memphis. Their research interests lie in power electrical systems, with a focus on optimization, smart grids, control systems, renewable energy resources, and distributed generations. They are currently involved in research on designing and modeling distributed energy resources, placement of distributed generations, intelligent optimization algorithms, smart grids, virtual power plants, power systems of vessels, electric vehicles, cybersecurity, machine learning, deep learning, and big data.

Skills:

Seyed Iman Taheri possesses strong programming skills, particularly in C, Matlab, and Python. They are also proficient in using various software and simulation tools essential for their field, including EWB, PSCAD, MATLAB, Plexos, Open-DSS, PVsyst, and Homer. These skills enable them to conduct advanced research and analysis in electrical power systems effectively.

Publication Top Noted:

Mitigating Cyber Anomalies in Virtual Power Plants Using Artificial-Neural-Network-Based Secondary Control with a Federated Learning-Trust Adaptation

Journal: Energies

Year: 2024

Citations: 0

A Simulated-Annealing-Quasi-Oppositional-Teaching-Learning-Based Optimization Algorithm for Distributed Generation Allocation

Journal: Computation

Year: 2023

Citations: 0

Optimized Configuration of Diesel Engine-Fuel Cell-Battery Hybrid Power Systems in a Platform Supply Vessel to Reduce CO2 Emissions

Journal: Energies

Year: 2022

Citations: 7

Distributed energy resource placement considering hosting capacity by combining teaching–learning-based and honey-bee-mating optimisation algorithms

Journal: Applied Soft Computing

Year: 2021

Citations: 7

Supporting distributed energy resources with optimal placement and sizing of voltage regulators on the distribution system by an improved teaching-learning-based optimization algorithm

Journal: International Transactions on Electrical Energy Systems

Year: 2021

Citations: 2

A trip-ahead strategy for optimal energy dispatch in ship power systems

Journal: Electric Power Systems Research

Year: 2021

Citations: 16

Optimal Cost Management of Distributed Generation Units and Microgrids for Virtual Power Plant Scheduling

Journal: IEEE Access

Year: 2020

Citations: 24

A new modified TLBO algorithm for placement of AVRs in distribution system

Conference: 2019 IEEE PES Conference on Innovative Smart Grid Technologies, ISGT Latin America 2019

Year: 2019

Citations: 8

A New Modification for TLBO Algorithm to Placement of Distributed Generation

Conference: ICCEP 2019 – 7th International Conference on Clean Electrical Power: Renewable Energy Resources Impact

Year: 2019

Citations: 7