Prof. Chong Hyun Lee | Deep Learning | Best Researcher Award

Published on 28/10/202528/10/2025 by Global Mechanics Awards

Prof. Chong Hyun Lee | Deep Learning | Best Researcher Award

Professor | Jeju National University | South Korea

Dr. Chong Hyun Lee is a distinguished researcher and academic in the fields of electronics, power transfer systems, ocean system engineering, and applied signal processing, with a prolific research record and recognized scientific excellence. As a long-standing IEEE member, Dr. Lee has made significant contributions to the advancement of electronic and communication technologies through innovation, leadership, and collaborative research. His work has been recognized with prestigious honors, including the Best Science and Technology Paper Award from the Korean Federation of Science and Technology Societies (KOFST) and the Best Paper Award in Ocean System Engineering from the Institute of Electronics and Information Engineers in South Korea, reflecting his high academic impact and technical expertise. Dr. Lee’s research encompasses a wide range of advanced topics, including compact impedance matching circuits for wideband power transfer in Janus Helmholtz transducers, weakly supervised graph neural networks for line spectrum extraction, and DC power boosting circuits for triboelectric nanogenerators with high intrinsic impedance and multi-harmonic output. His interdisciplinary work bridges marine engineering, electronics, and nanogenerator technologies, offering practical applications in sustainable energy systems, signal processing, and sensor innovation.

Profile: Scopus | Orcid | Google Scholar

Featured Publications:

Lee, C. H., & co-authors. (2024). DC power boosting circuit for freestanding-sliding triboelectric nanogenerators with high intrinsic impedance and multi-harmonic output. Advanced Materials Technologies.

Lee, C. H., & co-authors. (2024). Passive sonar signal classification using graph neural network based on image patch. Journal of the Acoustical Society of Korea.

Lee, C. H., & co-authors. (2023). Encoding and decoding-based normalizing flows for image anomaly localization. Electronics Letters.

Lee, C. H., & co-authors. (2023). Abnormal sonar signal detection using recurrent neural network and vector quantization. Journal of the Acoustical Society of Korea.

Dynhora Danheyda Ramirez Ochoa | Inteligencia de enjambre | Best Researcher Award

Published on 17/10/2025 by Global Mechanics Awards

Dr. Dynhora Danheyda Ramirez Ochoa | Inteligencia de enjambre | Best Researcher Award

Universidad Tecnológica de Chihuahua | Mexico

Dynhora Danheyda Ramírez Ochoa is a distinguished full-time professor at Universidad Tecnológica de Chihuahua, specializing in automation, data storage and analysis, project management, and digital innovation. With a Doctorate in Technology, a Master’s in Computer Systems Engineering, and a Bachelor’s in Computer Systems with a Hardware specialization, she has cultivated extensive expertise in multidisciplinary academic and technological environments. Since beginning her tenure at the university, she has advised over seventy students, facilitated seventeen graduations, and coordinated the development and monitoring of curricula for the Information Technologies and Digital Innovation program. Her leadership spans chairing and serving on committees for ethics, research, software, and tutoring, and she actively oversees STEM mentorship initiatives through the MC3T project. Dynhora has contributed to national and international conferences, focusing on swarm intelligence, decision-making processes, and emerging technologies, while publishing in specialized journals. Her dedication to fostering collaborative research teams, integrating immersive technologies, and promoting educational innovation reflects her commitment to developing both academic excellence and applied technological solutions, positioning her as an exemplary candidate for the Best Researcher Award.

Profile: Google Scholar

Featured Publications:

Ramírez-Ochoa, D. D., Pérez-Domínguez, L. A., Martínez-Gómez, E. A., & others. PSO, a Swarm Intelligence-Based Evolutionary Algorithm as a Decision-Making Strategy: A Review. Symmetry, 14(3), 455.

Ramírez-Ochoa, D. D., Pérez-Domínguez, L., & Martínez-Gómez, E. A. Supplier selection process based on CODAS method using q-rung orthopair fuzzy information. In q-Rung Orthopair Fuzzy Sets: Theory and Applications (pp. 219–240).

Royo-León, M., Hedley, D., Gal, E., Katz, N., Nitzan, M. W., Schreuer, N., & others. eWPQ: Development of a Computer-Based Work Performance Review Applications for Persons with Autism Spectrum Disorder. Revista ELECTRO, 40(1), 101–1.

Ramírez-Ochoa, D. D., Villagran-Vizcarra, D. C., & Zamarrón, V. T. TIC e IA, el futuro de la educación: mejorando el acceso y la efectividad del aprendizaje. RECIE. Revista Electrónica Científica de Investigación Educativa, 8, e2309–e2309.

Ramírez-Ochoa, D. D., Pérez-Domínguez, L. A., & Gómez-Martínez, E. Diseño de herramienta para la toma de decisiones avanzada con inteligencia de enjambre en un ambiente multicriterio: 6CP23-10. Memorias Científicas y Tecnológicas, 2(3), 16–17.

Pérez-Domínguez, L. A., Ramírez-Ochoa, D. D., & Luviano-Cruz, D. Implementing Sensible Algorithmic Decisions in Manufacturing. Applied Sciences, 15(16), 8885.

Cortés, T. J. G., Ramírez-Ochoa, D. D., & Ortega, E. C. P. Inspirando vocaciones científicas: estrategias de mentoría para niñas en STEM. In Transformando la educación: pensamiento computacional y robótica como …

Pérez-Domínguez, L. A., Luviano-Cruz, D., Hernández-Hernández, J. I., & Ramírez-Ochoa, D. D. An Integrated Approach to Decision-Making that Maximizes the Plastic Injection Molding Process. In Systems and Decision Processes in Management, Innovation and Sustainability

Prof. Jing Wang | Brain-inspired Intelligent Algorithms | Best Research Award

Published on 28/04/202528/04/2025 by Global Mechanics Awards

Prof. Jing Wang | Brain-inspired Intelligent Algorithms | Best Research Award

professor, fudan university, China

Prof. Jing Wang is an Associate Researcher at the Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University. With expertise in brain-inspired intelligent algorithms, flexible wearable devices, and intelligent medical equipment, she has made significant contributions to academia and industry.

Profile

scholar

🎓 Education

Although specific educational details are not provided, her achievements suggest a strong foundation in science and technology.

👨‍🔬 Experience

– Associate Researcher at Fudan University- Jointly Appointed Scientist at Sinopharm Medical- Entrepreneurship Mentor at CEIBS- Led various national and regional projects- Collaborated with industry partners to develop innovative medical devices

🔍 Research Interest

🏆Awards and Honors

– Global Outstanding Contribution to Tech Innovation- Int’l Innovation Gold Medal (¥2M prize)- World High-Level Entrepreneur Leader- China Industry-University-Research Innovation Award- Shanghai Youth Entrepreneurship Elite

📚 Publications

– Published 35 SCI papers in top journals like Nature Electronics 📄
– Co-authored monograph “Flexible Wearable Medical Devices” 📚
– Granted 14 international/Chinese invention patents 📝

Conclusion

Prof. Jing Wang’s impressive publication record, innovative research, and significant industrial translation make her a strong candidate for the Best Researcher Award. Her prestigious awards and industry-academia contributions further demonstrate her expertise and impact. With some additional emphasis on societal impact and research methodology, she could further strengthen her application. Overall, she is a highly suitable candidate for this award.