Dr. Ali Ihsan Aygun | Electrical Engineering | Best Researcher Award
Assistant Professor at Duzce University, Turkey
Dr. Ali Ihsan Aygun is an accomplished academic and researcher specializing in Electrical and Computer Engineering, with a strong focus on smart grids, electric vehicles (EVs), and power systems optimization. He earned his PhD from the University of North Carolina at Charlotte (UNCC), where he developed cutting-edge algorithms for smart EV charging and grid stability. Currently an Assistant Professor at Duzce University, Turkey, he teaches and conducts research in power systems and intelligent energy networks. His technical acumen spans Matlab, Python, Opal-RT, and other simulation tools. Dr. Aygun has co-authored several high-impact IEEE publications and presented at prestigious international conferences. His research contributes to sustainable energy practices and the future of electric transportation infrastructure. As a forward-thinking innovator, Dr. Aygun is driving the convergence of clean energy, electric mobility, and grid reliability.
professional profile
Education 
Dr. Ali Ihsan Aygun’s academic foundation is anchored in Electrical and Computer Engineering. He earned his PhD in 2022 from the University of North Carolina at Charlotte (USA), graduating with a perfect 4.00 GPA. Prior to that, he completed a Master’s degree in the same field at George Washington University in Washington, DC, USA, with a GPA of 3.33. He also began a Master’s program at Yıldız Technical University in Istanbul, Turkey, where he maintained a 3.83 GPA before transitioning abroad. His academic journey started with a BSc in Electrical and Electronic Engineering from Yıldız Technical University, where he graduated with 3.47 GPA. His advanced studies have covered power systems, smart grids, electric vehicles, and renewable energy integration, equipping him with both theoretical insight and practical experience to address modern energy challenges.
Work Experience
Dr. Aygun currently serves as an Assistant Professor at Duzce University, Turkey, since February 2022. He teaches both undergraduate and graduate-level courses in electrical and computer engineering while conducting research on power systems and smart grid optimization. His previous role as a Graduate Research Assistant at the Power, Energy, and Intelligent Systems Lab (PEISL) at UNCC (2018–2022) involved developing smart charging and routing algorithms for electric vehicle fleets and conducting grid control simulations. He also worked as a Graduate Teaching Assistant at UNCC, providing instruction for multiple undergraduate courses. Earlier in his career, he served as a Project Manager at Heper Moonlight Corp in Istanbul, where he handled design software like AutoCAD and Dialux and interfaced with clients. These roles reflect a rich blend of academic, research, and industry experience, positioning him as a versatile expert in electrical engineering and energy systems.
🏆 Awards & Honors
Dr. Aygun’s academic distinction is evident from his 4.00 GPA during his PhD studies at UNCC, showcasing exceptional performance in advanced power systems and smart grid research. His work has been published in IEEE Transactions on Industry Applications, a highly reputed journal in electrical engineering, reflecting recognition by the international research community. He was part of several competitive, peer-reviewed international conferences, including IEEE PESGRE and GlobConPT, where his contributions were presented and well-received. His collaborations with Duke Distinguished Professor Dr. Sukumar Kamalasadan and participation in leading-edge projects in electric vehicle energy optimization underscore his high standing in the field. While still in the early stages of his professorship, his research already holds practical and commercial value for the transition to sustainable energy, highlighting his potential for future national and international awards in engineering and clean energy.
Research Focus
Dr. Aygun’s research revolves around smart grid systems, electric vehicle energy management, and decentralized optimization algorithms. His core work involves developing centralized and decentralized smart charging methodologies to improve grid stability, reduce energy costs, and promote sustainable EV integration. He has designed and simulated scenarios such as valley filling, cost minimization, and vehicle-to-grid (V2G) applications. His innovative routing algorithm for EVs incorporates charging station stops and energy efficiency into a hybrid transportation model. Additionally, Dr. Aygun applies optimization techniques like ADMM (Alternating Direction Method of Multipliers) to power distribution networks. His focus also includes integrating flexible loads into grid operations and enhancing real-time grid response capabilities. The ultimate goal of his research is to create intelligent, energy-efficient systems that can adapt to the growing complexities of electric mobility and renewable energy networks.
🛠️ Skills
Dr. Aygun is proficient in programming and modeling tools central to modern power systems research. His programming strengths lie in Matlab and Python, which he uses extensively for algorithm development and simulation. He is adept with industry-leading simulation tools like Simulink, Opal-RT, CYME, PSCAD, PSSE, and PSIM, enabling him to model both microgrids and large-scale power networks. For optimization, he utilizes MOSEK and CVX, allowing for precise mathematical modeling of smart grid and EV scenarios. His design experience includes using AutoCAD, and he is also skilled in Microsoft Office Suite including Word, Excel, PowerPoint, and Visio for documentation and presentation. His strong combination of technical, analytical, and instructional skills makes him highly effective in both research and academic teaching environments, especially in the realm of power systems engineering, electric vehicles, and smart infrastructure.
Conclusion
Dr. Ali Ihsan Aygun is a highly promising early-career researcher with a solid academic background, outstanding technical contributions, and forward-looking research that aligns with global energy challenges. His impactful work on electric vehicle integration, smart charging infrastructure, and grid resilience positions him as a strong candidate for the Best Researcher Award, particularly in the domain of Smart Grid Technologies, Electrical Engineering, and Sustainable Power Systems.
Publications to Noted
Title: Centralized Charging Approach to Manage Electric Vehicle Fleets for Balanced Grid
Authors: A.I. Aygun, S. Kamalasadan
Citations: 10
Year: 2022
Title: Inverter-Angle-Induced Optimized Frequency Regulation Approach for AC–DC Microgrids Using Consensus-Based Identification
Authors: A. Joshi, A.I. Aygun, S. Kamalasadan, K. Biju
Citations: 7
Year: 2022
Title: A Two-Stage Optimal Electric Vehicles Charging Methodology Based on Aggregators Considering Grid Reliability and Operational Efficiency
Authors: A.I. Aygun, M.S. Hasan, A. Joshi, S. Kamalasadan
Citations: 4
Year: 2024
Title: An Optimal Hybrid Management of Electric Vehicle Fleet Charging and Load Scheduling in Active Electric Distribution System
Authors: A.I. Aygun, M.S. Hasan, A. Joshi, S. Kamalasadan
Citations: 4
Year: 2024
Title: An Optimal Approach to Manage Electric Vehicle Fleets Routing
Authors: A.I. Aygun, S. Kamalasadan
Citations: 3
Year: 2022
Title: An Alternating Direction Method of Multipliers (ADMM) Based Optimal Electric Vehicle Fleets Charging in Active Electric Distribution Network
Authors: A.I. Aygun, A. Joshi, S. Kamalasadan
Citations: 2
Year: 2022
Title: A Unified Control Design of Three Phase Inverters Suitable for Both Grid‐Forming and Following Modes of Operation
Authors: A. Ingalalli, A.I. Aygun, S. Kamalasadan
Citations: Not listed
Year: 2025
Title: Smart Charging Algorithms for Electric Vehicles: Addressing Grid Stress Through Real-Time Pricing
Author: A.I. Aygun
Citations: Not listed
Year: 2024
Title: Distributed Generation Approach with Helping of Charging Stations
Author: A.I. Aygun
Citations: Not listed
Year: 2024
Title: Dynamic Speed Optimization for Electric Vehicles
Author: A.I. Aygun
Citations: Not listed
Year: 2024