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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

 

 

Seyed Iman Taheri | Power systems Award | Best Scholar Award

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