Ayse Tugba Yapici | Engineering and Technology | Best Research Article Award

Published on by Research Hypothesis

Ms. Ayse Tugba Yapici | Engineering and Technology | Best Research Article Award

Ms. Ayse Tugba Yapici | Engineering and Technology | Best Research Article Award | Doctoral Researcher | Kocaeli University | Turkey 

Ms. Ayse Tugba Yapici is an emerging scholar in electrical engineering whose research bridges intelligent energy systems, electric vehicles, and artificial intelligence–driven prediction technologies, reflecting her strong academic preparation and expanding scientific footprint. She earned her PhD in Electrical Engineering from Kocaeli University, where her doctoral studies centered on deep learning approaches for forecasting electric vehicle demand, charging behaviors, and integrated grid impacts. Prior to this, she completed her MSc in Electrical Engineering at Kocaeli University and her BSc in Electrical and Electronics Engineering at Bulent Ecevit University, progressively building a foundation in power electronics, system modeling, and smart energy infrastructures. Professionally, Ms. Ayse Tugba Yapici has gained significant experience as a doctoral researcher contributing to multiple academic studies involving EV charging station optimization, boosting converter analyses, AI-based prediction models, and data-driven approaches for regional transportation planning. Her research interests span electric vehicle technologies, charging station planning, induction heating systems, renewable energy integration, IoT-based intelligent mobility frameworks, and machine learning algorithms including LSTM, GRU, and MLR for performance forecasting. She possesses strong research skills in deep learning model development, Python-based simulation, DigSilent-based power system design, MATLAB/Simulink modeling, geographical data mapping, algorithm optimization, and statistical evaluation metrics such as R², MSE, MAE, and DTW. Her body of work includes multiple SCI and Scopus-indexed publications addressing EV growth prediction, secure IoT frameworks for autonomous taxis, and comparative analyses of deep learning methods for charging time estimation. Ms. Ayse Tugba Yapici has been recognized within academic circles for her contributions to advancing sustainable mobility solutions and has received commendations for her research productivity and multidisciplinary collaborations within Türkiye. Her work continues to support improved policy development, smarter grid integration, and future-ready electric mobility infrastructures. She remains actively involved in scholarly dissemination through conference participation, collaborative studies with engineering experts, and mentorship of junior researchers. Through her growing publication record, analytical expertise, and commitment to advancing intelligent transportation systems, Ms. Ayse Tugba Yapici demonstrates strong potential for continued impact in electrical engineering research, contributing to the broader goals of sustainable energy development, smart city transitions, and technology-driven societal advancement.

Profile: Scopus | ORCID

Featured Publications

  1. Yapici, A. T., Abut, N., & Erfidan, T. (2025). Comparing the effectiveness of deep learning approaches for charging time prediction in electric vehicles: Kocaeli example. Energies. Year: 2025

  2. Yapici, A. T., & Abut, N. (2025). Geleceğe yönelik elektrikli araç ve şarj istasyonu sayılarının LSTM ve GRU derin öğrenme yöntemleri kullanılarak tahmin edilmesi: Kocaeli ili örneği. Politeknik Dergisi. Year: 2025

  3. Yapici, A. T., Abut, N., & Yildirim, A. (2025). Future estimation of electric vehicles and charging stations: Analysis of Sakarya Province with LSTM, GRU and multiple linear regression approaches. Applied Sciences. Year: 2025

  4. Yapici, A. T., & Abut, N. (2025). An intelligent and secure IoT-based framework for predicting charging and travel duration in autonomous electric taxi systems. Applied Sciences. Year: 2025

  5. Yapici, A. T., & Abut, N. (2024). Elektrikli araç devresinde kullanılan boost dönüştürücünün analizine farklı yaklaşımlar. Black Sea Journal of Engineering and Science. Year: 2024

  6. Yapici, A. T., & Abut, N. (2024). Elektrikli araç şarj istasyonu konum tasarımında, DigSilent yazılımı kullanılarak Kocaeli Üniversitesi Umuttepe Kampüsü için örnek uygulama. Black Sea Journal of Engineering and Science. Year: 2024

  7. Yapici, A. T. (2024). Estimation of future number of electric vehicles and charging stations: Analysis of Sakarya Province with LSTM, GRU and MLR approaches. Applied Sciences. Year: 2024

 

Lin Hua | Engineering and Technology | Excellence in Innovation Award

Published on by Research Hypothesis

Assoc. Prof. Dr. Lin Hua | Engineering and Technology | Excellence in Innovation Award

Assoc. Prof. Dr. Lin Hua | Engineering and Technology | Deputy Director | School of Naval Architecture | China 

Assoc. Prof. Dr. Lin Hua is a distinguished scholar in the field of marine engineering and structural integrity research. Her work focuses on understanding and predicting the fatigue life of marine structures under corrosive environments. With a strong academic foundation and a commitment to advancing engineering safety, she has become a recognized name for her contributions to pitting corrosion analysis and continuum damage mechanics modeling. Her research aims to bridge the gap between theoretical modeling and industrial applications, thereby improving the design, maintenance, and operational reliability of marine structures.

Professional Profile 

Education

Assoc. Prof. Dr. Lin Hua earned her doctoral degree in structural engineering from a leading university, where she developed expertise in continuum damage mechanics, fatigue analysis, and advanced computational modeling. Her educational background is complemented by rigorous research training, participation in collaborative projects, and specialized courses in marine structural health monitoring. This academic preparation laid the foundation for her groundbreaking work in fatigue crack initiation life prediction and pit morphology quantification.

Experience

Assoc. Prof. Dr. Lin Hua currently serves as an Associate Professor and leads several research initiatives focused on marine structural reliability. She has successfully collaborated with global research institutes, shipbuilding companies, and offshore engineering organizations to develop practical methodologies that improve the safety and performance of critical structures. Her extensive teaching portfolio includes mentoring graduate students and supervising doctoral dissertations, helping nurture the next generation of researchers. In addition, she has served on technical committees, participated in peer-review processes for high-impact journals, and contributed to the organization of international symposia on marine engineering.

Research Interest

Her primary research interests include fatigue life assessment of marine structures, pitting corrosion modeling, structural health monitoring, and life extension strategies for offshore platforms. She integrates theoretical modeling with computational techniques to predict fatigue crack initiation life under complex environmental conditions. Her recent work explores pit morphology parameters—size, shape, irregularity, and spacing—and their effects on structural integrity. By developing reliable mapping models and efficient numerical approaches, she provides industry stakeholders with actionable solutions to reduce maintenance costs, improve safety, and optimize lifecycle management.

Award

Assoc. Prof. Dr. Lin Hua has been recognized for her innovative contributions through institutional and international awards in the field of structural engineering and marine research. Her achievements include excellence awards for research impact, commendations for collaborative projects, and invitations to serve as a reviewer and advisor for prestigious journals. These accolades underscore her role as a leading researcher committed to advancing knowledge and delivering real-world engineering solutions.

Selected Publication

  • “Theoretical Mapping Model for Pit Morphology Parameters and Fatigue Crack Initiation Life” (Published: 2023, Citations: 45)

  • “Continuum Damage Mechanics-Based Numerical Approach for Marine Structure Life Assessment” (Published: 2022, Citations: 39)

  • “Multi-Factor Quantification of Pit Morphology and Its Effect on Fatigue Life” (Published: 2022, Citations: 31)

  • “Rapid Fatigue Life Prediction of Offshore Structural Components under Corrosive Conditions” (Published: 2021, Citations: 28)

Conclusion

Assoc. Prof. Dr. Lin Hua stands out as a pioneering researcher whose work addresses critical challenges in marine engineering and structural health assessment. Her integration of theoretical modeling, computational techniques, and practical validation has advanced understanding of fatigue life under corrosive conditions, providing a framework for safer marine operations. With a proven record of impactful publications, international collaborations, and mentorship, she continues to shape the future of structural engineering. Her dedication to bridging academic research with industrial application makes her a highly deserving candidate for prestigious awards, and her future research promises to further strengthen global standards in marine structural integrity and safety.