Tuniyazi Abudoureheman | Information Technology | Research Excellence Award

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Dr. Tuniyazi Abudoureheman | Information Technology | Research Excellence Award

Hiroshima University | Japan

Dr. Tuniyazi Abudoureheman is an emerging researcher in intelligent imaging technologies whose work integrates high-frame-rate (HFR) video processing, digital signal processing, and intelligent systems to address complex challenges in robotics, motion analysis, and biological detection. His research focuses on developing advanced computational frameworks capable of extracting subtle temporal and spatial features from high-speed visual data, with applications spanning vibration monitoring, multi-joint robotic manipulators, and biological motion recognition. Tuniyazi’s contributions involve creating novel image- and signal-processing algorithms designed to improve the accuracy, stability, and efficiency of automated systems operating in dynamic environments. His work on HFR-video-based vibration analysis offers enhanced diagnostic capabilities for flexible robotic structures, while his research on hornet detection using wing-beat frequency analysis demonstrates the potential of high-speed imaging for environmental and biological applications. Furthermore, his earlier work on multi-person tracking in complex backgrounds reflects his strong foundation in computer vision and predictive filtering. Tuniyazi’s scholarly visibility continues to grow, with citations indexed in Google Scholar and Scopus, reflecting early-stage but steadily increasing academic impact. According to Google Scholar metrics, his work has accumulated citations, maintaining an h-index of 1 and an i10-index of 0, which is consistent with researchers developing specialized expertise in a rapidly advancing technical domain. His research outputs contribute to international conferences and peer-reviewed journals, demonstrating a commitment to scientific rigor and innovation. Tuniyazi’s ongoing research trajectory aligns strongly with the objectives of the Research Excellence Award, showcasing high-impact potential in intelligent video processing, adaptive computational models, and robotics-oriented signal analysis, reinforcing his role as a promising contributor to next-generation smart robotic and imaging systems.

Publication Profile

Google Scholar

Featured Publications

  • Li, J., Shimasaki, K., Tuniyazi, A., Ishii, I., Ogihara, M., & Yoshiyama, M. (2023). HFR video-based hornet detection approach using wing-beat frequency analysis. IEEE Sensors, 1–4.

  • Abudoureheman, T., Wang, F., Shimasaki, K., & Ishii, I. (2025). HFR-video-based vibration analysis of a multi-jointed robot manipulator. Journal of Robotics and Mechatronics, 37(5), 1205–1218.

  • Tuniyazi Abudoureheman, T., & Abousharara, E. (2018). Multiple people tracking based on Kalman filter in complex background. Proceedings of the Shikoku-Section Joint Convention of Institutes of Electrical and Related Engineers.

Weidong Ji | Computer Science | Editorial Board Member

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Dr. Weidong Ji | Computer Science | Editorial Board Member

Harbin Normal University | China

Dr. Weidong Ji is a distinguished Chinese scholar known for his innovative contributions to artificial intelligence in education, learning analytics, and intelligent recommendation technologies, with a strong research presence reflected across international journals and conferences. His work integrates machine learning, knowledge graphs, deep learning models, and cognitive theories to enhance personalized learning, online education systems, student engagement assessment, and data-driven educational decision-making. With a Scopus record of 39 documents, 102 citations from 100 citing documents, and an h-index of 6, Dr. Ji’s scholarly influence continues to grow as his recent works advance emerging domains such as quantum-constructivism-based knowledge tracing, lightweight human–computer interaction models, and user-preference-driven recommendation algorithms. Google Scholar metrics (if available) would further extend his citation visibility, demonstrating the expanding global use of his models in adaptive learning, course recommendations, and real-time student behavior analysis. He also contributes to the academic community through participation in peer-review processes and editorial activities that support the development of high-quality research in AI-driven educational technology. Dr. Ji’s recent publications showcase cutting-edge computational frameworks such as neural knowledge graph reasoning, lightweight vision models for engagement analytics, and personalized prediction architectures for sparse learning environments. His contributions position him as an emerging leader at the intersection of educational psychology and computational intelligence, emphasizing practical applicability, algorithmic efficiency, and innovative pedagogical design, demonstrating excellence aligned with this award category as an Editorial Board Member.

Publication Profile

Scopus

Featured Publications

  • Authors unavailable. (2025). Knowledge graph convolutional networks with user preferences for course recommendation. Scientific Reports.

  • Authors unavailable. (2025). CQSA-KT: Research on personalized knowledge tracing based on quantum-constructivism in sparse learning environments. Knowledge Based Systems.

  • Authors unavailable. (2025). LightNet: A lightweight head pose estimation model for online education and its application to engagement assessment. Journal of King Saud University Computer and Information Sciences.