Ayşe Tuğba Yapıcı | Electric Vehicles | Best Research Article Award

Posted on by Automobile Award

Ms. Ayşe Tuğba Yapıcı | Electric Vehicles | Best Research Article Award

Doctoral Researcher  |  Kocaeli University  |  Turkey

Ms. Ayşe Tuğba Yapıcı is a dedicated doctoral researcher whose academic journey is strongly rooted in cutting-edge technologies for electric vehicles, smart energy systems, and intelligent power electronics. She has cultivated significant professional experience through her active involvement in research addressing real-world problems such as electric vehicle charging optimization, grid-integrated charging infrastructures, and advanced modeling of power converter systems. Throughout her career, she has contributed to impactful scientific studies focusing on induction heating systems, charging time prediction using deep learning, and data-driven forecasting on electric vehicle adoption and infrastructure planning. Her research interests include electric vehicle technologies, charging station design, renewable-integrated smart grids, artificial intelligence–based energy forecasting, machine learning and deep learning applications in power systems, and IoT-enhanced smart mobility frameworks. She possesses strong research skills in Python-based deep learning toolkits, MATLAB/Simulink, DigSilent PowerFactory modeling, statistical evaluation metrics, time-series forecasting, optimization algorithms, and performance analysis of intelligent systems. She has published multiple peer-reviewed articles in international SCI/Scopus-indexed journals, delivering innovative research outcomes that offer comprehensive and practical solutions for the sustainable development of electric transportation. Her research achievements include proposing an intelligent deep learning–based framework for EV charging time prediction, integrating spatial–temporal mobility parameters, and enhancing operational efficiency for fast-charging infrastructures. Her work stands out for its interdisciplinary approach and technological significance, supporting the transition toward cleaner mobility, optimized charging networks, and smart energy management. In addition to research excellence, she continues to contribute to academic and scientific communities through conference participation, collaborations, and knowledge dissemination. She aims to advance secure, intelligent, and scalable charging automation systems that support next-generation autonomous electric mobility. Her long-term vision is to shape energy-efficient transportation ecosystems, reduce environmental impacts, and contribute to the global sustainability agenda through innovation and scientific leadership. She has achieved  3 Citations , 2 Documents,  1 h-index.

Featured Publications

Yapıcı, A. T., & Abut, N. (2025, November 23). An intelligent and secure IoT-based framework for predicting charging and travel duration in autonomous electric taxi systems. Applied Sciences.

Yapıcı, A. T., Abut, N., & Yıldırım, A. (2025, October 27). Estimation of future number of electric vehicles and charging stations: Analysis of Sakarya Province with LSTM, GRU and multiple linear regression approaches. Applied Sciences.

Yapıcı, A. T., & Abut, N. (2025, August 21). Geleceğe yönelik elektrikli araç ve şarj istasyonu sayılarının LSTM ve GRU derin öğrenme yöntemleri kullanılarak tahmin edilmesi: Kocaeli ili örneği. Politeknik Dergisi.

Yapıcı, A. T., Abut, N., & Erfidan, T. (2025, April 11). Comparing the effectiveness of deep learning approaches for charging time prediction in electric vehicles: Kocaeli example. Energies.

Yapıcı, A. T., & Abut, N. (2024, September 15). Elektrikli araç şarj istasyonu konum tasarımında, Digsilent yazılımı kullanılarak Kocaeli Üniversitesi Umuttepe Kampüsü için örnek uygulama. Black Sea Journal of Engineering and Science.

Ayşe Tuğba Yapıcı’s research advances intelligent and sustainable electric mobility by integrating deep learning, smart grid technologies, and IoT-based predictive frameworks to optimize charging infrastructure and energy management. Her work supports the transition toward autonomous electric transportation, reducing environmental impacts, improving urban mobility planning, and contributing to global innovation in smart energy systems. She envisions scalable, reliable, and human-centered smart mobility ecosystems that accelerate the adoption of clean transportation worldwide.

Feng Wang | EV Charging Infrastructure | Best Researcher Award

Posted on by Automobile Award

Dr. Feng Wang | EV Charging Infrastructure | Best Researcher Award

Associate Professor  |  Fujian University of Technology |  China

Dr. Feng Wang is a distinguished academic and researcher recognized for his significant contributions to the fields of computer cryptography, network security, and applied mathematics. Currently serving as an Associate Professor at the College of Computer Science and Mathematics, Fujian University of Technology, he has established himself as a prominent figure in the development of secure computational frameworks and innovative cryptographic algorithms. His extensive professional experience spans teaching, research, and collaborative projects that integrate theoretical mathematics with practical applications in cybersecurity. Dr. Wang’s research focuses on computer cryptography, data privacy, and secure communication protocols within distributed and cloud-based computing environments. His scholarly work demonstrates a strong command of mathematical modeling, algorithm design, and encryption mechanisms, enabling the advancement of secure data transmission and protection techniques. He is particularly skilled in areas such as network information assurance, data encryption standards, and privacy-preserving computation, which are essential for modern information systems. Over the years, he has guided numerous students and contributed to academic excellence through publications, peer reviews, and conference participation. Dr. Wang’s dedication to advancing research in computer and network security has earned him recognition within the academic community. His research output continues to influence emerging developments in cybersecurity and applied cryptography, providing a foundation for next-generation secure computing technologies. His work reflects a balance of theoretical insight and practical relevance, aligning with the evolving challenges of global information security. Feng Wang remains committed to fostering academic innovation and interdisciplinary collaboration that bridges mathematics, computer science, and information technology. He has achieved 226 Citations , 34 Documents ,9 h-index.

Profile:  Scopus

Featured Publications

  1. Huang, Z., Wang, F., Chen, X., & Chang, C.-C. (2025). Revisiting “online/offline provable data possession” schemes. Computer Standards & Interfaces.
    Citations: 2

  2. Huang, Z., Wang, F., Chen, X., & Chang, C.-C. (2025). Reversible data hiding with secret encrypted image sharing and adaptive coding. IEEE Internet of Things Journal.
    Citations: 1

  3. Huang, Z., Wang, F., Chen, X., & Chang, C.-C. (2024). Efficient blockchain-based data aggregation scheme with privacy-preserving on the smart grid. IEEE Transactions on Smart Grid.