Farouk Zouari | Electrical Engineering | Editorial Board Member

Published on by Global Scholar Awards

Assist. Prof. Dr. Farouk Zouari | Electrical Engineering | Editorial Board Member 

Researcher | University of Tunis El Manar | Tunisia

Dr. Farouk Zouari is a distinguished researcher specializing in Electrical Engineering, Artificial Intelligence, Adaptive Control, and Computer Engineering, recognized for his pioneering contributions to intelligent control of nonlinear, fractional-order, and chaotic systems. His research primarily focuses on advanced neural and fuzzy control, time-delay system modeling, nonlinear system stabilization, and innovative output-feedback strategies, while his emerging interests explore AI-driven decision algorithms, intelligent medical control systems, and adaptive synchronization of complex dynamic systems. Dr. Zouari has served in key academic and research roles, collaborating extensively with multidisciplinary teams to develop next-generation control architectures, neural approximators, observer-based feedback systems, and high-precision adaptive controllers that strengthen both theoretical frameworks and real-world engineering applications. His contributions include novel designs for neural network controllers, intelligent fuzzy synchronization mechanisms, adaptive quantized control schemes, and robust backstepping approaches that address actuator nonlinearities, pseudo-state constraints, and fractional-order uncertainties. He has also advanced event-triggered control, intelligent drug-dosage dynamic modeling, and optimal control of electromechanical systems, providing impactful innovations with industrial, biomedical, and automation-related applications. Dr. Zouari’s growing body of research has resulted in high-impact publications that are widely cited for their methodological rigor and technical depth, contributing significantly to advancing nonlinear system control, computational intelligence, and real-time dynamic system optimization. His work has supported new engineering solutions, informed emerging policies on intelligent automation, and inspired further exploration into hybrid AI-control paradigms for next-generation autonomous systems. Driven by a deep commitment to scientific progress, his vision centers on integrating adaptive intelligence into complex engineering infrastructures to enhance efficiency, safety, and resilience across industries. He aims to bridge theoretical advancements with scalable real-world innovations, strengthening global research in intelligent control and enabling transformative technologies that benefit society through smarter automation, precision medical systems, and sustainable intelligent engineering solutions.

Profiles: Google Scholar | ORCID | Scopus | Linkedin | ResearchGate 

Featured Publications

1. Zouari, F., Ibeas, A., Boulkroune, A., Cao, J., & Arefi, M. M. (2018). Adaptive neural output-feedback control for nonstrict-feedback time-delay fractional-order systems with output constraints and actuator nonlinearities. Neural Networks, 105, 256–276.

2. Boubellouta, A., Zouari, F., & Boulkroune, A. (2019). Intelligent fuzzy controller for chaos synchronization of uncertain fractional-order chaotic systems with input nonlinearities. International Journal of General Systems, 48(3), 211–234.

3. Zouari, F., Ibeas, A., Boulkroune, A., Cao, J., & Arefi, M. M. (2021). Neural network controller design for fractional-order systems with input nonlinearities and asymmetric time-varying pseudo-state constraints. Chaos, Solitons & Fractals, 144, 110742.

4. Zouari, F., Boulkroune, A., & Ibeas, A. (2017). Neural adaptive quantized output-feedback control-based synchronization of uncertain time-delay incommensurate fractional-order chaotic systems with input nonlinearities. Neurocomputing, 237, 200–225.

5. Zouari, F., Ibeas, A., Boulkroune, A., Cao, J., & Arefi, M. M. (2019). Neuro-adaptive tracking control of non-integer order systems with input nonlinearities and time-varying output constraints. Information Sciences, 485, 170–199.

Farzin Golzar | Energy | Excellence in Research Award

Published on by Global Scholar Awards

Assist. Prof. Dr. Farzin Golzar | Energy | Excellence in Research Award

Assistant Professor | KTH Royal Institute of Technology | Sweden

Farzin Golzar is an accomplished researcher and Assistant Professor specializing in Energy Systems Engineering and Renewable Energy Technology, with a professional focus on integrating advanced modeling techniques to address complex sustainability challenges. His research centers on the application of artificial intelligence for modeling and optimizing energy systems, hybridizing data-driven statistical models with process-driven physical frameworks, and advancing comparative life-cycle impact assessment to enhance environmental decision-making. He also explores energy conversion and storage solutions aimed at accelerating global energy transitions. Dr. Golzar’s professional journey includes his current role at the Heat and Power Technology Division of KTH Royal Institute of Technology, building on previous contributions as a climate strategy consultant supporting national and international stakeholders across sectors such as buildings, transport, and agriculture, as well as prior academic roles including his postdoctoral position at KTH and leadership responsibilities within Sharif University of Technology and the Sharif Energy Research Institute. His research contributions span innovative system-to-cell multiphysics modeling, optimization of hybrid solar-battery systems, AI-based CO₂ emission prediction models, and integrated assessment methods for greenhouse and wastewater systems, along with a series of influential publications on lithium-ion battery degradation, renewable energy system optimization, and climate-positive fuel cell applications. His work has supported major funded projects on sustainable water–energy systems, circular urban economies, urban wastewater treatment supported by AI-based tools, and decarbonization pathways for transportation, demonstrating his ability to bridge scientific innovation with applied solutions. Through collaborations with institutions such as ETH Zurich, international research groups, and environmental agencies, he has contributed to policy-relevant insights for energy system planning and climate mitigation. With a vision grounded in scientific rigor and societal relevance, Dr. Golzar strives to advance sustainable energy transitions by developing data-driven, scalable, and environmentally conscious solutions that support global climate objectives. His work ultimately aims to empower industry, policymakers, and communities with tools and methodologies that improve resource efficiency, reduce environmental impacts, and promote resilient, low-carbon energy futures.

Profiles: ORCID  | Google Scholar | LinkedIn

Featured Publications

1. Smajila, L., Trevisan, S., Golzar, F., Vaidya, K., & Guedez, R. (2025). Comparative analysis of technoeconomic and techno-environmental approach to optimal sizing and dispatch of hybrid solar–battery systems. Energy Conversion and Management X, 25, 100858. https://doi.org/10.1016/j.ecmx.2024.100858

2. Heidary, B., Kiani, M. A., & Golzar, F. (2025). Toward sustainable development: Energy transition scenarios for oil-dependent countries, with Iran as a case study. Energies, 18(10). https://doi.org/10.3390/en18102651

3. Talaei, M., Astaneh, M., Farahani, E. G., & Golzar, F. (2023). Application of artificial intelligence for predicting CO₂ emission using weighted multi-task learning. Energies, 16(16), 5956. https://doi.org/10.3390/en16165956

4. Golzar, F., & Silveira, S. (2021). Impact of wastewater heat recovery in buildings on the performance of centralized energy recovery: A case study of Stockholm. Applied Energy, 297, 117141. https://doi.org/10.1016/j.apenergy.2021.117141

5. Nilsson, D., Karpouzoglou, T., Wallin, J., Blomkvist, P., Golzar, F., & Martin, V. (2023). Is on-property heat and greywater recovery a sustainable option? A quantitative and qualitative assessment up to 2050. Energy Policy, 182, 113727. https://doi.org/10.1016/j.enpol.2023.113727