Ms. Takwa Hamdi | Energy Technologies | Best Researcher Award

PhD Candidate in Mechanical and Energy Engineering | University of Gabes | Tunisia

Ms. Takwa Hamdi is a dedicated PhD student in Mechanical and Energy Engineering at the National Engineering School of Gabes, Tunisia, specializing in advanced combustion modeling and alternative fuels. With a strong academic foundation, she has pursued her bachelor’s, master’s, and doctoral studies in mechanical engineering with excellence, graduating as class valedictorian during her master’s program. Her research focuses on dual-fuel engine combustion, particularly the use of light alcohols and hydrogen in internal combustion engines, employing advanced numerical simulation tools such as ANSYS Forte, Matlab, Abaqus, SolidWorks, and CFD-based approaches. Driven by a passion for sustainable energy solutions, she is motivated to contribute to the development of low-emission technologies that address global energy challenges. Alongside her research, Takwa serves as an Adjunct Lecturer at the Higher Institute of Technological Studies of Gabes, where she teaches courses in dismountable assembly processes, CAD using SolidWorks, welding, and mechanical design projects, combining theoretical knowledge with hands-on applications to support student learning. She has also gained experience in developing educational materials, supervising student projects, and guiding practical workshops, which highlights her strong communication and leadership skills. Fluent in Arabic, French, and English, she is able to collaborate effectively in international and multicultural environments. Beyond her academic and teaching career, she demonstrates strengths in analytical thinking, problem-solving, and research innovation, with interests in technology, cultural exploration, and community volunteering. Motivated, research-oriented, and passionate about innovation, Takwa aims to further her expertise by contributing to cutting-edge projects in energy, combustion, and sustainability through collaborative scientific research and internships.

Featured Publications

Hamdi, T., Hamdi, F., Molima, S., Domínguez, V. M., Rodríguez-Fernández, J., Hernández, J. J., & Chrigui, M. (2025). Numerical investigation of hydrogen substitution ratio effects on spray characteristics, combustion behavior, and emissions in a dual-fuel compression ignition engine.

Molima, S., Hamdi, F., Hamdi, T., Muya, G. T., Mondo, K., Amsini, S., & Chrigui, M. (2025). Effects of H2 substitution on combustion and emissions in ammonia/diesel compression ignition engine. Energy Conversion and Management, Elsevier.

Hamdi, T., Hamdi, F., Molima, S., Hernandez, J. J., & Chrigui, M. (2025). Computational analysis on the effect of methanol energy ratio on the spray and combustion pattern of a dual-fuel compression ignition engine. Journal of Energy Resources Technology, ASME.

Dr. Dawei Qiu | Smart Grid | Best Researcher Award

Lecturer, University of Exeter, United Kingdom

Dr. Dawei Qiu is a distinguished scholar in smart energy systems, currently serving as a Lecturer at the University of Exeter, UK 🏫. With a strong background in electrical engineering and power systems, he specializes in AI-driven reinforcement learning, market design for low-carbon energy transition, and resilience enhancement of energy systems ⚡. His extensive research contributions in smart grids and power systems have earned him recognition in academia, with a Google Scholar citation count of 2,109, an h-index of 24, and an h10-index of 35 📊.

Publication Profile

Google Scholar

🎓 Education

Dr. Qiu holds a Ph.D. in Electrical Engineering from Imperial College London (2016–2020) 🎓, where he conducted pioneering research on local flexibility’s impact on electricity retailers under the supervision of Prof. Goran Strbac. Prior to this, he completed his M.Sc. in Power System Engineering from University College London (2014–2015) and obtained his B.Eng. in Electrical and Electronic Engineering from Northumbria University at Newcastle (2010–2014) ⚙️. His academic journey has been shaped by esteemed mentors, including Dr. Ben Hanson and Dr. Zhiwei (David) Gao, IEEE Fellow.

💼 Experience

Dr. Qiu’s professional career spans academia and research institutions, where he has contributed significantly to energy systems innovation 🌍. Before joining the University of Exeter in 2024, he was a Research Fellow at Imperial College London (2023–2024), specializing in market design for low-carbon energy systems. He also served as a Research Associate at the same institution from 2020 to 2023 🔬. His work in smart grids and energy resilience has been instrumental in shaping sustainable and intelligent power infrastructure.

🏆 Awards and Honors

Dr. Qiu’s research excellence has been acknowledged through various accolades 🏅. His contributions to smart energy systems, AI-driven reinforcement learning, and low-carbon market design have positioned him as a leading researcher in the field. His studies have been published in top-tier journals, and his work has received high citations, demonstrating its impact on the global research community 🌟.

🔬 Research Focus

Dr. Qiu’s research is centered on leveraging artificial intelligence and reinforcement learning for power and energy applications 🤖. His work explores market mechanisms for cost-effective and sustainable energy transitions, as well as the resilience enhancement of energy systems in response to climate change 🌍. His expertise in AI-driven optimization and machine learning applications in energy systems makes him a key contributor to the advancement of smart grid technologies.

🔚 Conclusion

Dr. Dawei Qiu is a leading researcher in smart energy systems, with a strong academic background and impactful contributions to power systems engineering 🔬. His expertise in AI-driven market optimization, reinforcement learning, and resilient energy systems has made him a valuable asset to the research community 🌍. With his ongoing work at the University of Exeter, he continues to drive innovation in low-carbon and intelligent energy solutions ⚡.

🔗 Publications

A knowledge-based safe reinforcement learning approach for real-time automatic control in a smart energy hub – Applied Energy (Under review, 2025) 🔗 Link

Enhanced Meta Reinforcement Learning for Resilient Transient Stabilization – IEEE Transactions on Power Systems (Under review, 2025) 🔗 Link

Machine learning-based economic model predictive control for energy hubs with variable energy efficiencies – Energy (First round revision, 2024) 🔗 Link

A Review of Resilience Enhancement Measures for Hydrogen-penetrated Multi-energy Systems – Proceedings of the IEEE (Under review, 2025) 🔗 Link

Coordinated Optimal Dispatch Based on Dynamic Feasible Operation Region Aggregation – IEEE Transactions on Smart Grid (First round revision, 2024) 🔗 Link

A Sequential Multi-Agent Reinforcement Learning Method for Coordinated Reconfiguration of Substation and MV Distribution Networks – IEEE Transactions on Power Systems (Under review, 2024) 🔗 Link

Enhancing Microgrid Resilience through a Two-Layer Control Framework for Electric Vehicle Integration and Communication Load Management – IEEE Internet of Things Journal (Under review, 2024) 🔗 Link

Coordinated Electric Vehicle Control in Microgrids Towards Multi-Service Provisions: A Transformer Learning-based Risk Management Strategy – Energy (Under review, 2024) 🔗 Link

Adaptive Resilient Control Against False Data Injection Attacks for a Multi-Energy Microgrid Using Deep Reinforcement Learning – IEEE Transactions on Network Science and Engineering (Under review, 2024) 🔗 Link

Takwa Hamdi | Energy Technologies | Best Researcher Award

Ms. Takwa Hamdi | Energy Technologies | Best Researcher Award

Featured Publications