Khalil Abdelnaby | Computer Science | Research Excellence Award

Published on by Environmental Scientists

Mr. Vivek Dwivedi | Computer Science | Research Excellence Award

Al-Ahliyya Amman university | Jordan

Dr. Khalil Mohamed Khalil AbdElnaby is a researcher in Systems and Computers Engineering with expertise in Artificial Intelligence, cloud robotics, cybersecurity, embedded systems, IoT, and intelligent communication technologies. His research contributions focus on deep learning, network intrusion detection, hardware trojan detection, cloud computing, FPGA systems, and optimization techniques for intelligent engineering applications. He has authored and co-authored more than 10 scientific publications in reputable international journals and conferences. His research profile has achieved over 100 citations with an h-index of 5, reflecting the growing academic impact and relevance of his contributions to advanced engineering and AI-driven technologies.

Professional Profiles 

Education Background

Tuniyazi Abudoureheman | Intelligent Systems | Research Excellence Award

Published on by Environmental Scientists

Dr. Tuniyazi Abudoureheman | Intelligent Systems | Research Excellence Award

Dr. Tuniyazi Abudoureheman | Intelligent Systems | Hiroshima University | Japan

Dr. Tuniyazi Abudoureheman is a dedicated researcher and Ph.D. student at Hiroshima University whose work focuses on advanced sensing, machine vision, and robotic system diagnostics, contributing meaningfully to the fields of high-frame-rate (HFR) imaging, vibration analysis, and automated detection systems. Dr. Tuniyazi Abudoureheman began his academic journey with foundational studies that eventually led him to pursue graduate-level research, culminating in his current doctoral studies where he continues to expand his expertise in robotics and intelligent sensing technology. Throughout his professional experience, Dr. Tuniyazi Abudoureheman has actively engaged in collaborative research projects, working alongside multidisciplinary teams to design, implement, and validate methods involving HFR video, wing-beat frequency detection, and robot health monitoring across multiple postures. His early work also includes contributions to multi-target tracking using Kalman Filtering in complex environments, demonstrating both versatility and technical depth even before entering advanced doctoral research. The core research interests of Dr. Tuniyazi Abudoureheman include high-speed imaging, robotic vibration analysis, automated industrial inspection, bio-inspired detection systems, and machine vision algorithms, all of which align with the evolving demands of next-generation intelligent robotics. His research skills span HFR camera-based data acquisition, signal processing, vibration modeling, robotic motion evaluation, and applied machine learning, supported by strong analytical ability and experience with experimental system design. Dr. Tuniyazi Abudoureheman has also developed valuable competencies in publishing scientific results, presenting at conferences, and contributing to collaborative engineering investigations, which collectively strengthen his academic and professional profile. Although early in his academic career, Dr. Tuniyazi Abudoureheman has already earned recognition through peer-reviewed publications, citations, and participation in reputable conferences such as IEEE SENSORS, positioning him as an emerging scholar in robotics and sensing technology. His work has received growing scholarly attention, reflected in increasing citation counts and inclusion in respected journals covering robotics and mechatronics. In conclusion, Dr. Tuniyazi Abdurrahman continues to advance as a promising researcher whose technical contributions, methodological rigor, and commitment to innovation place him on a strong path toward future academic excellence and impactful scientific discovery.

Academic Profile: ORCID | Google Scholar

Featured Publications:

  1. Li, J., Shimasaki, K., Tuniyazi, A., Ishii, I., & Ogihara, M. (2023). HFR video-based hornet detection approach using wing-beat frequency analysis. 3 citations.

  2. Abudoureheman, T., Wang, F., Shimasaki, K., & Ishii, I. (2025). HFR-video-based vibration analysis of a multi-jointed robot manipulator. 1 citation.

  3. Abudoureheman, T., Otsubo, H., Wang, F., Shimasaki, K., & Ishii, I. (2025). High-frame-rate camera-based vibration analysis for health monitoring of industrial robots across multiple postures.

 

Nitin Goyal | Computer Science | Best Researcher Award

Published on by Environmental Scientists

Dr. Nitin Goyal | Computer Science | Best Researcher Award

Assistant Professor | Central University of Haryana | India

Dr. Nitin Goyal is a distinguished academic and researcher in the field of Computer Science and Engineering, recognized for his extensive contributions to advanced computing technologies, underwater wireless sensor networks (UWSN), and intelligent communication systems. With a robust academic foundation and over sixteen years of professional experience, he has established a prolific research profile encompassing artificial intelligence, machine learning, deep learning, Internet of Things (IoT), and wireless sensor networks (WSN). Dr. Nitin Goyal has authored more than 175 research papers, including 90 SCI-indexed, 15 Scopus-indexed, 15 book chapters, and numerous conference proceedings, reflecting his commitment to high-impact scientific dissemination. His innovative work has led to the filing of 30 patents, with 20 already granted, demonstrating his drive for technological advancement and innovation. As an editor and contributor to multiple international books published by CRC Press, IGI Global, and Cambridge Scholars, he plays a vital role in bridging research and industry applications. His active engagement as a reviewer, editorial board member, and guest editor for renowned SCI journals such as Scientific Reports (Nature) and CMC – Computers, Materials & Continua further emphasizes his scholarly leadership. Dr. Nitin Goyal research excellence has been recognized globally through awards such as the Best Researcher Award and his inclusion in the list of the world’s top 2% scientists by Elsevier. His recent works on AI-driven pest classification, privacy-preserving frameworks, and intelligent anti-phishing models underscore his continuous pursuit of innovation for sustainable and secure technological ecosystems. 3,747 Citations by 2,904 documents, 128 Documents, 35 h-index.

Profiles: Scopus | Orcid | Google Scholar | Researchgate | LinkedIn 

Featured Publications

Trivedi, N. K., Gautam, V., Anand, A., Aljahdali, H. M., Villar, S. G., Anand, D., … (2021). Early detection and classification of tomato leaf disease using high-performance deep neural network. Sensors, 21(23), 7987.

Kumar, A., Sharma, S., Goyal, N., Singh, A., Cheng, X., & Singh, P. (2021). Secure and energy-efficient smart building architecture with emerging technology IoT. Computer Communications, 176, 207–217.

Lilhore, U. K., Imoize, A. L., Li, C. T., Simaiya, S., Pani, S. K., Goyal, N., Kumar, A., … (2022). Design and implementation of an ML and IoT based adaptive traffic-management system for smart cities. Sensors, 22(8), 2908.

Chaudhary, M., Goyal, N., Benslimane, A., Awasthi, L. K., Alwadain, A., & Singh, A. (2022). Underwater wireless sensor networks: Enabling technologies for node deployment and data collection challenges. IEEE Internet of Things Journal, 1.

Goyal, N., Dave, M., & Verma, A. K. (2020). SAPDA: Secure authentication with protected data aggregation scheme for improving QoS in scalable and survivable UWSNs. Wireless Personal Communications, 113(1), 1–15.

Hyeryung Jang | Machine Learning | Best Researcher Award

Published on by Environmental Scientists

Assist. Prof. Dr Hyeryung Jang | Machine Learning | Best Researcher Award

Assistant Professor, Dongguk University, South Korea 🧑‍🏫

Hyeryung Jang is an Assistant Professor at the Division of AI Software Convergence at Dongguk University, Seoul, South Korea. His research interests lie at the intersection of communication systems, probabilistic graphical models, and networked machine learning. He has contributed significantly to the development of algorithms for large-scale communication networks, with applications in healthcare, manufacturing, and beyond. He has held academic and research positions at prestigious institutions, including King’s College London and KAIST.

Profile

Google Scholar

🎓 Education

Hyeryung Jang earned his Ph.D. in Electrical Engineering from the Korea Advanced Institute of Science and Technology (KAIST), South Korea, from March 2012 to February 2017. His doctoral thesis, titled Optimization and Learning of Graphical Models: A Stochastic Approximation Approach, was supervised by Prof. Yung Yi and co-advised by Prof. Jinwoo Shin. He also holds a Master’s degree in Electrical Engineering from KAIST, completed between March 2010 and February 2012, with a thesis on the Economic Benefits of ISP-CDN and ISP-ISP Cooperation, under the guidance of Prof. Yung Yi. Hyeryung Jang completed his Bachelor’s degree in Electrical Engineering at KAIST in February 2010.

💼 Experience

Hyeryung Jang currently serves as an Assistant Professor in the Division of AI Software Convergence at Dongguk University, where he has been leading the Intelligence and Optimization in Networks (ION) lab since March 2021. Before this, he was a Research Associate at King’s College London, in the Centre for Telecommunications Research, Department of Engineering, from March 2018 to February 2021. His post-doctoral research was conducted at KAIST from March 2017 to February 2018. Hyeryung also gained valuable experience as a Research Intern at Los Alamos National Laboratory in the USA during the summer of 2015.

🔬 Research Interests

Hyeryung Jang’s research interests are centered on mathematical modeling and communication systems, with a particular emphasis on networked machine learning. He explores innovative learning algorithms for probabilistic graphical models, deep learning, and reinforcement learning. His work aims to improve the stability and representation quality of generative models such as GANs, VAEs, and diffusion models. Jang is also focused on the learning and inference of graphical models, specifically for applications like robust recommendation systems and communication-efficient algorithms. Moreover, his research delves into efficient learning methods to address noisy data and real-world challenges in fields like healthcare, highlighting his broad interdisciplinary approach to solving complex problems in communication networks.

🏆 Awards

Hyeryung Jang has received recognition for his groundbreaking work in networked machine learning, contributing to innovative applications in healthcare and telecommunications. His research has been published in top-tier journals such as IEEE Transactions on Communications, IEEE Transactions on Neural Networks and Learning Systems, and Journal of Medical Internet Research (JMIR).

📚 Publications Top Notes

LinkFND: Simple Framework for False Negative Detection in Recommendation Tasks with Graph Contrastive Learning, IEEE Access, Dec. 2023.

In-Home Smartphone-based Prediction of Obstructive Sleep Apnea in Conjunction with Level 2 Home Polysomnography, JAMA Otolaryngology-Head & Neck Surgery, Nov. 2023.

Prediction of Sleep Stages via Deep Learning using Smartphone Audio Recordings in Home Environments, Journal of Medical Internet Research, June 2023.

Real-time Detection of Sleep Apnea based on Breathing Sounds and Prediction Reinforcement using Home Noises, Journal of Medical Internet Research, Feb. 2023.

Conclusion

Given his strong academic credentials, innovative contributions, and high-impact research, Hyeryung Jang is undoubtedly a strong contender for the Best Researcher Award. His work not only advances theoretical knowledge but also drives practical applications that address critical real-world challenges, particularly in communication systems and healthcare. Jang’s passion for interdisciplinary research and teaching further solidifies his suitability for this prestigious recognition.

Haichang Jiang | AI | Best Researcher Award

Published on by Environmental Scientists

Mr Haichang Jiang | AI | Best Researcher Award

lecturer, jingdezhen university, China  📚

Haichang Jiang is a lecturer at the School of Information Engineering, Jingdezhen University, with over 10 years of experience in artificial intelligence technology, project management, and research. He completed his Master’s in Software Engineering at the University of Electronic Science and Technology of China in 2013 and earned his Ph.D. in Educational Management from the University of Perpetual Help System DALTA in the Philippines in 2023. Jiang has successfully managed large-scale AI projects, such as AI public opinion platforms for the Cyberspace Administration of China and the Ministry of Education.

Profile

Google Scholar

Education 🎓

Haichang Jiang holds a Master’s degree in Software Engineering from the University of Electronic Science and Technology of China (2013). In 2023, he received his Ph.D. in Educational Management from the University of Perpetual Help System DALTA, Philippines, where he honed his expertise in artificial intelligence and educational technologies.

Experience 💼

Jiang has extensive experience in both academia and industry. He has been a lecturer at Jingdezhen University since 2023, teaching AI and related subjects. His professional career includes managing and researching AI-based projects such as the development of AI-driven platforms for the Chinese government and the design of smart healthcare and financial systems. He has collaborated with various top Chinese universities and institutions on AI and health-related research.

Research Interests 🔬

Haichang Jiang’s research primarily focuses on artificial intelligence, smart healthcare, intelligent finance, and sentiment analysis. His projects involve the application of deep learning in medical diagnostics, the development of smart financial systems, and the integration of multimodal views based on natural language for public opinion monitoring.

Awards 🏆

Jiang has contributed significantly to various research projects, with notable achievements including his involvement in AI public opinion platforms, AI-driven smart healthcare systems, and environmental monitoring technologies. His work has been recognized by the Ministry of Education of China, the Jiangxi Provincial Higher Education Society, and several leading academic organizations.

Publications Top Notes 📑

“Research on Real-time Psychological Crisis Early Warning System Based on Natural Language and Deep Learning”, Journal of Artificial Intelligence, 2024. Cited by 15 articles.

“Innovation and Practice of Teaching Methods Under New Engineering Background”, Educational Technology and Society, 2024. Cited by 10 articles.

Conclusion

Haichang Jiang is a highly deserving candidate for the Best Researcher Award due to his extensive and impactful contributions to AI, healthcare, finance, and public opinion analysis. His innovative projects, ongoing research, and leadership in cutting-edge AI applications demonstrate his potential to drive future technological advancements. With continued collaboration and greater international visibility, Haichang Jiang is poised to further elevate the scope of his research, making him a suitable recipient of this prestigious award.

Xiaojun Li | Control Science and Engineering | Best Researcher Award

Published on by Environmental Scientists

Dr Xiaojun Li | Control Science and Engineering | Best Researcher Award

PHD Candidate, School of Aerospace Science and Technology, Xidian University, China  🌟

Xiaojun Li is a dedicated Ph.D. candidate at the School of Aerospace Science and Technology, Xidian University. With a solid academic foundation and research acumen, he has been exploring innovative approaches to detection and tracking technologies. His commitment to advancing radar signal processing and LiDAR data analysis highlights his contributions to modern aerospace technologies.

Profile

Orcid

Education 📚

Xiaojun Li completed his B.S. in Detection, Guidance, and Control Technology at Xidian University, Shannxi, China, in 2023. He is currently pursuing his Ph.D. in Control Science and Technology at the same institution, focusing on cutting-edge advancements in aerospace engineering.

Experience 🛠️

As a student researcher, Xiaojun has been actively involved in developing innovative solutions for low, small, and slow target detection. He has contributed to significant radar signal processing projects and worked on consultancy assignments related to LiDAR data applications in aerospace.

Research Interests 🔍

Xiaojun Li’s research focuses on advancing detection and tracking technologies, particularly for low, small, and slow targets. His work delves into radar signal processing and LiDAR data analysis, exploring innovative approaches to enhance accuracy and efficiency in challenging environments. By bridging theoretical concepts with practical applications, Xiaojun addresses real-world challenges in aerospace engineering, contributing to the development of cutting-edge technologies that redefine detection and mapping systems.

Awards 🏆

While primarily focused on academic and research pursuits, Xiaojun Li has been recognized for his contributions to radar signal and LiDAR data processing technologies. His achievements reflect his dedication to innovation in the field.

Publications  Top Notes🖋️

Wang, W., Yan, B., Li, X., et al. (2024). “Multiple Pedestrian Tracking Using LiDAR Network in Complex Indoor Scenarios,” IEEE Sensors Journal, 24(8), pp. 13175–13192. DOI: 10.1109/JSEN.2024.3369947.

Cited by: 5 articles

Li, X., Hu, G., et al. (2024). “A Low-Cost 3D Mapping System for Indoor Scenes Based on 2D LiDAR and Monocular Cameras,” Remote Sensing, 16, 4712. DOI: 10.3390/rs16244712.

Cited by: 3 articles

Conclusion

Xiaojun Li is a promising candidate for the Best Researcher Award, with a solid foundation in innovative technologies and high-impact publications. Strengthening his profile through diversified outputs and applied research could further establish his eligibility. His demonstrated contributions and potential for impactful advancements in aerospace and tracking technology make him a strong contender for this recognition.