Raghi K R | Deep Learning | Research Excellence Award

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Ms. Raghi K R | Deep Learning | Research Excellence Award

Sathyabama University | India

Ms. Raghi K R is a distinguished researcher in the field of Computer Science and Engineering, with expertise spanning Artificial Intelligence, Deep Learning, Machine Learning, Cloud Security, and Web Mining. Her research primarily focuses on developing privacy-preserving and secure computing frameworks, innovative AI and IoT-based solutions for healthcare, smart surveillance, and environmental monitoring, and advancing cloud-based neural network applications. She has made significant contributions to privacy-preserving deep neural network classification over signature cryptosystems in cloud environments and has been recognized for her innovative work in smart healthcare systems, anomaly detection in CCTV surveillance, and real-time data analysis. With 29 citations, an h-index of 4, and an i10-index of 0 (Google Scholar), her research impact is further reflected in her scholarly publications and patents, encompassing AI-driven predictive modeling, blockchain-based data security, and deep learning applications in medical and industrial domains. Dr. Raghi has published extensively in IEEE and other international conferences, including landmark works on Huntington’s disease prediction, touch-free smart home systems, proactive detection of cybersecurity threats, and driver distraction detection. Her research is characterized by integrating theoretical rigor with practical applications, often combining AI, IoT, and cloud computing to solve complex real-world problems. She actively mentors student projects and has guided multiple innovative projects recognized by professional societies. Her work has been cited across numerous documents, demonstrating both the quality and relevance of her contributions in AI, cybersecurity, and cloud computing research. Dr. Raghi K.R has been honored with the Research Excellence Award for her outstanding contributions to advanced computing and AI applications.

Publication Profile

Orcid | Google Scholar

Featured Publications

  • Raghi, K.R., & Sudha, K. (2024). Software development automation using generative AI. International Conference on Emerging Research in Computational Science.

  • Thomas, R.K., Lemuel, C.P., Sanjay, G., Pandeeswaran, C., & Raghi, K.R. (2024). Advanced CCTV surveillance anomaly detection, alert generation and crowd management using deep learning algorithm. 3rd International Conference on Artificial Intelligence for Internet of Things.

  • Devi, S.R., Priya, S.G., Sathi, G., Kumar, S.N., & Raghi, K.R. (2024). Design and development of a touch free smart home controlling system based on virtual reality (VR) technology. International Conference on Intelligent Systems for Cybersecurity (ISCS 2024).

  • Vethavikashini, A.M., Jamal, S.M., & Raghi, K.R. (2024). Huntington’s disease prediction using Xception CNN. 2nd International Conference on Disruptive Technologies (ICDT 2024), 201-208.

  • Raghi, K.R., & Paramarthalingam, A. (2024). Proactive detection of Mirai botnet threats: Leveraging XGBoost for enhanced cybersecurity. IET Conference Proceedings CP900, 34-39.

Mingyue Zhang | Artificial Intelligence | Best Researcher Award

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Dr. Mingyue Zhang | Artificial Intelligence | Best Researcher Award

University of South China | China

Dr. Mingyue Zhang, Ph.D., is a dynamic researcher in computer vision, intelligent systems, and human–computer interaction, currently serving in the field of computer science with a focus on gesture recognition and lightweight deep learning models for edge devices. His research integrates advanced computer vision algorithms with human–machine collaboration, emphasizing intelligent gesture recognition for rehabilitation training, embedded AI, and Internet of Things (IoT)-enabled systems. Dr. Zhang has significantly contributed to developing efficient algorithms such as lightweight convolutional neural networks, adaptive Kalman filtering, and multi-sensor fusion frameworks, which enhance real-time performance in gesture estimation, object tracking, and assistive technologies. His innovative work bridges the gap between deep learning theory and practical deployment on embedded systems and mobile platforms. With over 25 publications in high-impact journals indexed in SCI and EI, including IEEE Internet of Things Journal, Expert Systems with Applications, IEEE Access, and Journal of Supercomputing, his research has achieved growing academic recognition. Dr. Zhang’s work has been widely cited across the global impact of his contributions in computer vision and artificial intelligence. His research is currently supported by the Hunan Provincial Department of Science and Technology, focusing on intelligent gesture recognition in rehabilitation. In recognition of his outstanding contributions to scientific innovation and scholarly excellence, Dr. Zhang is honored with the Best Researcher Award for his pioneering advancements in AI-driven human–computer interaction and lightweight network modeling.

Publication Profile

Orcid

Featured Publications

  • Jiang, C., Zhang, M., Wang, Y., & Zhang, A. (2025). AHMOT: Adaptive Kalman Filtering and Hierarchical Data Association for 3D Multi-Object Tracking in IoT-Enabled Autonomous Vehicles. IEEE Internet of Things Journal.

  • Zhang, M., Zhou, Z., Tao, X., & Deng, M. (2023). Hand pose estimation based on fish skeleton CNN: Application in gesture recognition. Journal of Intelligent & Fuzzy Systems, 44, 8029–8042.

  • Zhang, M., Zhou, Z., Wang, T., & Zhou, W. (2023). A lightweight network deployed on ARM devices for hand gesture recognition. IEEE Access, 11, 45493–45503.

  • Zhang, M., Zhou, Z., & Deng, M. (2022). Cascaded hierarchical CNN for 2D hand pose estimation from a single color image. Multimedia Tools and Applications, 81, 25745–25763.

  • Zhang, M., & Zhou, Z. (2025). Speed-accuracy trade-off in lightweight-based hand pose estimation. The Journal of Supercomputing, 81, 1212

Jinping Xue | Artificial Intelligence | Best Researcher Award

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Ms. Jinping Xue | Artificial Intelligence | Best Researcher Award

Renergy Overseas Limited | China

Ms. Jinping Xue is an emerging researcher and engineer specializing in the integration of Artificial Intelligence with sustainable urban environments. Her research focuses on Smart Cities, Industrial AI, Edge Intelligence, and Environmental AI—fields that explore how data-driven intelligence can transform urban infrastructure into more adaptive, efficient, and sustainable systems. She has made significant contributions to the development of a privacy-preserving AI framework for smart city environmental monitoring, integrating federated learning with LSTM and genetic algorithms to achieve high pollution source traceability accuracy while maintaining data privacy. Her interdisciplinary expertise bridges environmental modeling, urban systems optimization, and AI-driven perception technologies, contributing to innovative solutions in sustainable city management and smart mobility. Xue’s scholarly work demonstrates a strong interest in the application of distributed sensing and federated learning for pollution source analysis, contributing to the broader goal of achieving clean, data-secure, and intelligent urban ecosystems. She has collaborated with experts in environmental sensing and intelligent perception to enhance the real-time adaptability of urban monitoring systems. Her publications, indexed in Scopus and Google Scholar, reflect her growing impact in the domains of computational intelligence and environmental systems. With research outputs recognized in peer-reviewed international journals such as Sensors, her work has begun to gain citations across the environmental AI research community. Her citation records are progressively expanding, with verified documentation and indexing available through Scopus and Google Scholar, and her h-index count demonstrates her early but impactful research trajectory. Through her interdisciplinary approach, Xue continues to push the boundaries of AI applications for sustainable development and smart city transformation.

Publication Profile

Google Scholar

Featured Publications

Xue, J., Hu, X., Liu, Q., Yin, C., Ni, P., & Bo, X. (2025). Air pollutant traceability based on federated learning of edge intelligent perception agents. Sensors, 25(19), 6119.

 

 

Feudjio Ghislain | Deep Learning | Best Research Article Award

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Mr. Feudjio Ghislain | Deep Learning | Best Research Article Award

Academician at University of Dschang, Cameroon.

Feudjio Ghislain, born on March 24, 1986, in Batcham, Cameroon, is a dedicated educator and researcher in electronics and applied physics. He is a Technical and Professional Education Teacher at Government Technical High School of Bangou and a Part-time Lecturer at Fotso Victor University Institute of Technology, University of Dschang. With a strong background in electronics, he has mentored students in various technical domains and supervised numerous academic projects. His research focuses on image classification, segmentation, deep learning, and machine learning. Ghislain has actively participated in multiple academic conferences and seminars. His passion for education, research, and technological advancement drives his contributions to academia and industry. Beyond academia, he is actively involved in community development initiatives and enjoys reading, music, and sports.

Professional Profiles📖

Scopus 

Education 🎓

Feudjio Ghislain is currently in his third year of a Doctorate/Ph.D. in Physics, specializing in Electronics at the University of Dschang, Cameroon. He holds a Master of Science in Physics (2019–2020) from the same university, where he specialized in Electronics with a ‘Good’ grade. His academic journey includes a DIPET II (2011) from HTTTC Douala, University of Douala, specializing in Electronics, a Bachelor of Science in Physics (2007) from the University of Dschang with a ‘Fairly good’ grade, and a Baccalaureate in Science (2004) from Lycée de Batcham. His academic progression showcases a consistent focus on electronics and applied physics, equipping him with in-depth expertise in his field.

work Experience💼

Feudjio Ghislain has been a part-time and professional teacher at the Fotso Victor University Institute of Technology (IUT-FV of Bandjoun) at the University of Dschang since 2018, teaching courses in Electrotechnics, Electronic Systems Maintenance, and Electrical Engineering. His subjects range from electronic construction to telecommunications and microcontroller applications. Since 2012, he has also served as an Electronics Teacher at the Government Technical High School of Bangou, teaching digital circuits, solar energy, and maintenance troubleshooting. His responsibilities extend to supervising final-year projects and serving on examination committees. Between 2020 and 2022, he was a part-time lecturer at the Evangelical University of Cameroon, teaching Biomedical Engineering. His expertise in teaching spans various educational levels, contributing significantly to the professional and technical development of students.

Research Focus

Feudjio Ghislain‘s research interests encompass image classification and segmentation, deep learning, and machine learning. His Ph.D. research focuses on the real-time analysis of medical images using second-generation wavelets, under the guidance of Professor TCHIOTSOP Daniel at the University of Dschang. His Master’s thesis explored embedded image processing systems for medical diagnostics, while his DIPET II research delved into spectral texture analysis using wavelets. His projects reflect a strong inclination toward practical and impactful applications of artificial intelligence in medical imaging and electronics. Through participation in conferences and research collaborations, he remains at the forefront of innovation in AI-based image processing.

Awards & Honors🏆 

Feudjio Ghislain has been recognized for his outstanding contributions to technical education and research. His dedication to advancing electronics education has earned him several professional affiliations, including membership in the SciPinion Scientific Community since 2024. He has also played a significant role in academic committees, acting as a referee for esteemed international journals like Heliyon and Computers in Biology and Medicine. His influence extends beyond the classroom, where he has contributed to organizing and evaluating national examinations. His research and teaching contributions have solidified his reputation as a committed educator and researcher in applied electronics and image processing.

Conclusion✅

Feudjio Ghislain is a strong candidate for the Best Researcher Article Award due to his expertise in electronics, image processing, and machine learning, alongside his teaching, peer-review, and project supervision roles. However, expanding his publication record in indexed journals, securing research funding, and increasing global collaborations would further strengthen his application for such a prestigious award.

Publications to Noted 📚

Title: “An improved semi-supervised segmentation of the retinal vasculature using curvelet-based contrast adjustment and generalized linear model”

Authors: Feudjio Ghislain​, Saha Tchinda Beaudelaire​, Tchiotsop Daniel