Biography
Aoun’s research focuses on improving how power systems operate and plan under high shares of variable renewables. At KAUST he is developing advanced unit commitment methods that explicitly consider renewable uncertainty and system stability while searching for algorithmic speed-ups and new formulations using quantum computation. Earlier work includes stochastic AC optimal power flow solved with machine learning surrogates, and course projects on grid-following and grid-forming inverter modeling for wind farms plus HVDC design for bulk power transfer.
During his master’s degree (fully funded) at Skoltech, Moscow (2022-2024), Aoun worked on a modified frequency control strategy for solar PV inverters using a virtual synchronous generator approach. His bachelor’s degree in Electrical Engineering (COMSATS University Islamabad, 2017-2021) included an ERASMUS+ semester at Sehir University Istanbul, in 2019. For his final-year project he developed an AI-based automatic meter reading framework that used deep neural networks for digit detection and recognition. He graduated as the silver medalist of his class.
Aoun has industrial experience from internships with LESCO in Pakistan and Shakarganj Mills Limited, and he worked as a Management Trainee Engineer at Shakarganj Mills Limited from 2021 to 2022. He programs primarily in MATLAB and Python and is actively developing skills in quantum software stacks such as PennyLane and Qiskit to apply quantum techniques to optimization problems in power systems.
Research Interests
- Unit commitment and scheduling for systems with high renewable penetration
- Quantum and hybrid quantum-classical algorithms for power-system optimization
- Stochastic AC optimal power flow and machine-learning-based surrogates
- Grid-forming and grid-following inverter modeling and control for wind farms
- HVDC system design and power transfer studies
About
Aoun is a Ph.D. student in the department of Electrical and Computer Engineering at KAUST working on unit commitment optimization for systems with high renewable penetration. His research spans unit commitment with stability constraints for high integration of renewable sources, stochastic AC optimal power flow, inverter modeling for wind farms, HVDC power transfer design, and exploring quantum computation techniques for unit commitment. He combines power-systems expertise with applied machine learning and practical experience in MATLAB and Python-based toolchains, including quantum frameworks such as PennyLane and Qiskit.
Awards and Distinctions
- Masters Fully Funded Scholarship, SKOLKOVO Institute of Science and Technology, 2022 - 2024
- Erasmus+ Exchange Program, Sehir University Istanbul, 2019
- Silver Medalist, Comsats University Islamabad, 2017 - 2021
- PWWB Scholarship, Comsats University Islamabad, 2017 - 2021
Qualifications
Education
- Master of Science (M.S.)
- Energy Systems (), SKOLKOVO Institute of Science and Technology, Moscow., Russian Federation, 2024
- Bachelor of Science (B.S.)
- Electrical Engineering, COMSATS University Islamabad, Pakistan, 2021
- Erasmus+ Exchange Program
- Electrical Engineering, Sehir University Istanbul, Turkey, 2019
Licenses and Certifications
- Management Trainee Engineer, Shakarganj Mills Limited, Jhang, Pakistan., Wed, Sep 15 2021 - Mon, Aug 29 2022
- Research Intern, EMAX Laboratories Moscow, Mon, May 29 - Tue, Jul 25 2023
- Intern, Lahore Electric Supply Company (LESCO), Wed, Jul 21 - Fri, Sep 10 2021
- Intern, Shakarganj Mills Limited, Mon, Jun 24 - Fri, Aug 23 2019
- English
- Full professional proficiency
- Urdu
- Full professional proficiency
