Blessing Ayegba | Clean Energy | Research Excellence Award

Ms. Blessing Ayegba | Clean Energy | Research Excellence Award 

Concordia University | Canada

Blessing Ayegba is a Ph.D. candidate specializing in building energy flexibility, grid-integrated systems, and indoor thermal comfort. Her research focuses on developing scalable, occupant-centered control strategies that enhance energy efficiency while maintaining comfort in buildings. She has contributed to advancing Building Energy Flexibility Indicators and demonstrated practical solutions for reducing peak energy demand through optimized temperature control. Her scholarly impact includes 35 citations, with an h-index of 1 and an i10-index of 1, reflecting emerging influence in the field. Her work integrates renewable energy, storage, and smart systems, supporting resilient and sustainable power grids worldwide.

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Sana Kordoghli | Energy Sustainability | Research Excellence Award

Prof. Sana Kordoghli | Energy Sustainability | Research Excellence Award

University of Carthage-Tunisia | Tunisia

Dr. Sana Kordoghli is an Associate Professor in energy engineering with strong expertise in sustainable energy systems, smart grids, and environmental valorization. She has authored 20 scientific documents, receiving 281 citations across 233 documents, with an h-index of 10. In preview mode, the “View h-index” button is disabled. She founded a Master’s program in Management and Digitalisation of Energy at the University of Carthage and actively contributes to international research projects on hydrogen production, waste-to-energy, and circular economy solutions. She supervises doctoral research and supports innovation and entrepreneurship through academic initiatives.

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Khaled Ben Abdallah | Energy Sustainability | Research Excellence Award

Prof. Dr. Khaled Ben Abdallah | Energy Sustainability | Research Excellence Award

Khaled Ben Abdallah is a Maître Assistant in transport and logistics sciences at the Institut Supérieur du Transport et de la Logistique, University of Sousse, Tunisia. His expertise focuses on transport economics, sustainability, and advanced econometric modeling. He holds a doctorate in economics and has extensive teaching experience across undergraduate and postgraduate levels. His research covers sustainable transport, green logistics, and policy-oriented analysis, with numerous publications in high-impact journals. His scientific impact includes 258 citations across 241 documents, 16 indexed publications, and an h-index of 7. He actively supervises research, contributes to academic development, and collaborates internationally.

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Ashiq Bhat | Energy Sustainability | Research Excellence Award

Mr. Ashiq Bhat | Energy Sustainability | Research Excellence Award

Thapar Institute of Engineering and Technology | India

Ashiq Nazir Bhat is a researcher, educator, and full-stack developer specializing in energy systems, artificial intelligence, and federated learning. He has extensive teaching experience in computer science and has contributed to advanced courses in data science, conversational AI, and predictive analytics. His research focuses on vehicle-to-grid energy optimization, privacy-preserving machine learning, and explainable AI. He has developed smart energy systems, real-time monitoring platforms, and secure web applications. Proficient in multiple programming languages and cloud technologies, he actively contributes to research publications, conferences, and peer review, demonstrating strong expertise in both academic research and practical technology development.

Featured Publications

Wahad Rahman | Energy Sustainability | Best Researcher Award

Mr. Wahad Rahman | Energy Sustainability | Best Researcher Award

Mr. Wahad Rahman | University of Engineering and Technology Peshawar | Pakistan

A highly skilled engineering professional with extensive experience in mechatronics, renewable energy systems, additive manufacturing, and Internet of Things (IoT) technologies. With a strong academic foundation including advanced research in hybrid energy harvesting systems, this expert has contributed significantly to cutting-edge developments in sustainable power solutions for sensor networks and pipeline monitoring applications. Current work in additive manufacturing and reverse engineering involves leading research and development initiatives, operating advanced 3D printing technologies (FDM, SLA), managing high-precision 3D scanning, and conducting specialized training programs. This blends practical engineering with innovation-driven problem-solving across industrial and applied research environments. Previously, research contributions in sensor and energy harvesting systems included the design and development of micro Kaplan and Crossflow turbines, IoT-based pipeline monitoring solutions, energy-efficient wireless sensor nodes, and experimental setups for testing hybrid energy harvesters. These projects demonstrate strong proficiency in mechanical design, simulation, prototyping, and system integration. With several years of experience in academia, this professional has taught undergraduate theory and laboratory courses in mechanics of materials, fluid mechanics, robotics, and engineering software tools such as MATLAB and SolidWorks. Extensive involvement in STEM capacity-building programs further highlights commitment to engineering education and technology dissemination. Research expertise spans renewable energy, hybrid and flow-based energy harvesting, control systems, self-powered systems, power management circuits, wireless sensors, and IoT technologies. Published work includes multiple journal articles in reputable international outlets focusing on piezoelectric, electromagnetic, and hybrid energy harvesters, turbine modeling, RF energy harvesting, and sensor network applications. Professional development includes specialized training in IoT, Arduino, Raspberry Pi, MATLAB, image processing, robotics, content writing, and digital marketing, demonstrating a broad multidisciplinary skillset. Overall, this profile reflects a dynamic researcher and engineer dedicated to advancing sustainable energy solutions, intelligent monitoring systems, and modern manufacturing technologies.

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Featured Publications

Rahman, W. U., & Khan, F. U. (2025). A hybrid flow energy harvester to power an IoT-based wireless sensor system for the digitization and monitoring of pipeline networks. Machines, 13(11). https://doi.org/10.3390/machines13111025

Rahman, W. U., & Khan, F. U. (2025). An integrated fluid flow and solar hybrid energy harvester for pipeline monitoring system. AIP Advances. https://doi.org/10.1063/5.0284001

Rahman, W. U., & Khan, F. U. (2025). A survey of flow-based energy harvesters for powering sustainable wireless sensor nodes. Journal of Renewable and Sustainable Energy. https://doi.org/10.1063/5.0237597

Rahman, W. U., & Khan, F. U. (2023). A hybrid flow energy harvester using combined piezoelectric and electromagnetic transductions for pipeline network monitoring. Journal of Intelligent Material Systems and Structures. https://doi.org/10.1177/1045389X221147647

Mr. Wenzhuang Liu | Energy Sustainability | Best Researcher Award | 2573

Mr. Wenzhuang Liu | Energy Sustainability | Best Researcher Award

Mr. Wenzhuang Liu | North China University of Science and Technology | China

This researcher has built a strong academic foundation in energy systems and renewable energy integration, focusing on innovative methods to enhance the flexibility, efficiency, and sustainability of modern power grids. With advanced studies in engineering thermophysics and hands-on experience in multiple research projects, the researcher has developed a deep understanding of thermodynamics, energy storage systems, and the challenges associated with large-scale renewable energy integration under contemporary carbon-neutrality goals. A key contribution is the development of an optimized configuration regulation method for energy storage systems (ESS) designed to address peak-shaving pressures arising from the widespread adoption of renewable energy. This method integrates deep peak shaving of thermal power units with coordinated demand-side response strategies, forming a comprehensive source-load-storage interaction model. By accounting for uncertainties in renewable generation and dynamic load variations, the framework enhances system responsiveness and operational flexibility. Simulation studies conducted across multiple scheduling scenarios demonstrate substantial improvements, including reductions in overall operation cost, unit operating cost, and renewable energy input cost. The findings highlight the method’s potential to significantly boost renewable energy utilization while maintaining economic and operational stability in power systems. Beyond this flagship innovation, the researcher has contributed to ongoing projects related to optimizing energy storage configurations for enhanced peak regulation. Their scholarly output includes publications in reputable journals and active engagement in funded research initiatives supported by scientific foundations and industrial laboratories. The researcher has also patented a novel ESS configuration approach centered on deep peak shaving and source-load-storage coordination. Overall, the researcher’s work advances both theoretical and application-oriented dimensions of renewable energy integration. Their contributions support more resilient, responsive, and economically viable power systems, making a meaningful impact on the transition toward low-carbon energy futures and reinforcing their suitability for recognition under research excellence awards.

Profiles: ScopusOrcid 

Featured Publications

Liu, J., Zhang, Z., Xie, Q., & Liu, W. (2024). Dual-phase model: Estimating the temperature and hydrodynamic size of magnetic nanoparticles with protein-corona formation. Applied Physics Letters. https://doi.org/10.1063/5.0199403

Li, L., Yi, W., Cui, X., & Liu, W. (2023). Rapid and high sensitivity temperature measurement based on near-extinction photoelastic modulated magneto-optical Kerr effect of Fe-Gd nanofilm. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2023.3323049

Liu, J., Huang, P., Zhang, Z., Xie, Q., & Liu, W. (2023). The nonlinear dynamics of magnetic nanoparticles: A thermometry in complex magnetic fields. Applied Physics Letters. https://doi.org/10.1063/5.0151058

Cui, X., Li, L., & Liu, W. (2022). A rapid and sensitive magnetic immunoassay of biomolecules based on magnetic nanoparticles. IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2022.3216405

Guo, S., Yi, W., & Liu, W. (2022). Biological thermometer based on the temperature sensitivity of magnetic nanoparticle paraSHIFT. Nanotechnology. https://doi.org/10.1088/1361-6528/ac3b81

Peng, H., Cheng, C., Wan, Q., Jia, S., Wang, S., Lv, J., Liang, D., Liu, W., Liu, X., Zheng, H., et al. (2022). Fast multi-parametric imaging in abdomen by B1+ corrected dual-flip angle sequence with interleaved echo acquisition. Magnetic Resonance in Medicine. https://doi.org/10.1002/mrm.29127