Takwa Hamdi | Energy Technologies | Best Researcher Award

Published on by Computer Scientists Awards

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.

Profile: Scopus | LinkedIn | ResearchGate

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.

Aymen saad | Energy Technologies | Best Researcher Award

Published on by Computer Scientists Awards

Mr. Aymen saad | Energy Technologies | Best Researcher Award

Lecturer | University of Technology Malaysia | Iraq

Mr. Aymen Saad is a dedicated academic and researcher in the field of computer and microelectronic systems engineering. He has established himself as an experienced lecturer at Al-Furat Al-Awsat Technical University, Kufa Management Technical College, where he has been contributing to education and research for many years. His work bridges theory and practice, with a strong interest in artificial intelligence and advanced computing systems. Alongside his teaching responsibilities, he has developed a reputation for impactful research, particularly in deep learning, machine learning, and biomedical image analysis, while maintaining a strong presence in international research communities.

Publication Profile

Scopus

ORCID

Google Scholar

Education Background

Mr. Aymen Saad began his academic journey by earning a bachelor’s degree in computer science from the Islamic University of Iraq. He later advanced his knowledge through a master’s degree in computer and microelectronics systems engineering at University of Technology Malaysia. Building on this foundation, he is currently pursuing his doctoral studies at the same institution, focusing on advanced applications of artificial intelligence and deep learning in computer vision and signal processing. His academic progression reflects a clear commitment to developing both technical expertise and research excellence in applied computer science and engineering fields.

Professional Experience

Mr. Aymen saad has served as a lecturer at Al-Furat Al-Awsat Technical University in Iraq, teaching within the Department of Information Technology Management. His professional career extends beyond teaching, as he actively engages in academic research and publications in reputed international outlets. With significant contributions in artificial intelligence applications, he has collaborated with researchers worldwide, presenting in conferences and publishing in peer-reviewed journals. He has also developed practical frameworks for disease detection, image enhancement, and pattern recognition, demonstrating the applied relevance of his work in solving modern engineering and healthcare challenges.

Awards and Honors

Throughout his academic journey, Mr. Aymen Saad has been recognized for his research contributions and teaching excellence. His growing h-index reflects the impact of his work in artificial intelligence and computer vision. His involvement in international conferences has earned him scholarly visibility and recognition, while his consistent publishing record in leading indexed journals highlights his dedication to advancing research in his field. Additionally, his professional profiles across platforms such as Google Scholar, ResearchGate, and Scopus emphasize his active participation and acknowledgment within the global academic community.

Research Focus

Mr. Aymen saad ’s research focuses on artificial intelligence, deep learning, and computer vision with applications across healthcare, security, and engineering systems. His studies span image and video processing, pattern recognition, optical character recognition, and medical image classification. He has contributed significantly to the development of robust models for cancer detection, COVID diagnostics, and brain tumor classification, as well as innovations in license plate recognition and fire detection. His current and future work aims to explore hybrid intelligent systems, bio-inspired algorithms, and advanced deep learning frameworks for solving real-world problems with greater efficiency and accuracy.

Publication Top Notes

Classification COVID-19 Based on Enhancement X-Ray Images and Low Complexity Model
Published Year: 2021
Citation: 56

Classification of Bird Sound Using High-and Low-Complexity Convolutional Neural Networks
Published Year: 2022
Citation: 42

An Optimized Deep Learning Approach for Robust Image Quality Classification
Published Year: 2023
Citation: 38

A Novel Deep Learning Approach for Brain Tumors Classification Using MRI Images
Published Year: 2023
Citation: 35

Automatic Vehicle License Plate Recognition Using Lightweight Deep Learning Approach
Published Year: 2023
Citation: 29

Conclusion

Mr. Aymen Saad is a skilled computer and microelectronic systems engineer, academic, and researcher with a strong background in artificial intelligence. His education, professional teaching experience, and extensive research portfolio reflect his dedication to both learning and sharing knowledge. With numerous publications, conference presentations, and ongoing projects, he continues to advance innovative solutions in medical diagnostics, intelligent systems, and computational modeling. His future research aspirations highlight his determination to contribute further to global knowledge in AI, ensuring that his work remains impactful in both academic and practical domains.