Wei He | Object Detection | Best Researcher Award

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Assoc. Prof. Dr. Wei He | Object Detection | Best Researcher Award

Assoc. Prof. Dr. Wei He | Object Detection – Dean at Hunan Institute of Science and Technology, China

Dr. Wei He is an esteemed academic and researcher at the Hunan Institute of Science and Technology, where he has served in the School of Information Science and Engineering since 2009. With over a decade of experience in advanced computational imaging and intelligent systems, he has established himself as a key contributor to the fields of remote sensing, hyperspectral imaging, and object detection. Dr. He’s interdisciplinary expertise and commitment to cutting-edge innovation have positioned him as a thought leader in applied machine learning within Earth observation technologies.

Academic Profille

ORCID

Education

Dr. He earned his Ph.D. in Information and Communication Engineering from Hoseo University in South Korea in 2020. Prior to this, he completed his Master’s degree in Computer and Communication at Changsha University of Science and Technology in 2009. His academic journey began with a Bachelor’s degree in Computer Science from Hunan Institute of Science and Technology in 2006. This progressive education provided him with a strong foundation in both theoretical and applied aspects of intelligent systems, enabling his impactful research career.

Experience

Since joining the faculty at Hunan Institute of Science and Technology, Dr. He has been involved in teaching, mentoring, and pioneering research. His roles span curriculum development, guiding postgraduate research, and securing national and institutional research funding. His international education and research background allow him to engage in collaborations across academic borders, particularly in the domains of intelligent object tracking and hyperspectral image processing. His recent efforts have emphasized deploying AI-enhanced algorithms in real-time UAV tracking and high-resolution remote sensing classification systems.

Research Interest

Dr. Wei He’s research interests lie at the intersection of artificial intelligence, image analysis, and sensor data interpretation. He focuses on small-object detection in remote sensing, hyperspectral anomaly identification, and machine learning-based UAV tracking. His work blends deep learning, quaternion frequency analysis, and multilevel network architectures to extract meaningful insights from complex visual and spatial datasets. His methods emphasize not only accuracy and efficiency but also robustness in noisy and dynamic environments, which is critical for real-world deployment of intelligent vision systems.

Award

Dr. He is a strong candidate for the Best Researcher Award due to his consistent scholarly productivity, innovative methodology, and real-world impact in intelligent sensing technologies. His ability to merge theory with practical application has earned him increasing academic citations and recognition in top-tier IEEE and Scopus-indexed journals. He continues to raise the bar in remote sensing research and is regarded as a role model for young researchers in the field of applied artificial intelligence.

Publication

📘 From Weak Textures to Dense Arrangements: Leveraging Prior Knowledge for Small-Object Detection in Remote Sensing Images, IEEE Transactions on Geoscience and Remote Sensing, 2025 (Cited by 15+)
📗 GSINet: Gradual Semantic Interaction Network for Remote Sensing Object Detection, IEEE JSTARS, 2025 (Cited by 10+)
📙 Hyperspectral Anomaly Detection Using Quaternion Frequency Domain Analysis, IEEE TNNLS, 2024 (Cited by 22+)
📕 Break the Shackles of Background: UAV Tracking Based on Eccentric Loss, IEEE TIM, 2024 (Cited by 12+)
📒 Background Subtraction via Regional Multi-Feature-Frequency Model in Complex Scenes, Soft Computing, 2023 (Cited by 8+)
📘 Hyperspectral Image Classification Using Superpixel–Pixel–Subpixel Multilevel Network, IEEE TIM, 2023 (Cited by 14+)
📗 Feature Extraction Using Spectral Regression Whitening, IEEE JSTARS, 2021 (Cited by 19+)

Conclusion

Dr. Wei He exemplifies the qualities sought in the recipient of the Best Researcher Award. His contributions to remote sensing and intelligent image interpretation continue to address critical global challenges in Earth monitoring and autonomous systems. Through his prolific publications, deep theoretical insights, and application-driven research, he has advanced the state-of-the-art in machine learning for geospatial intelligence. With strong international collaborations, a growing citation record, and clear leadership potential, Dr. He is poised to make even greater contributions to academia and industry in the coming years.

Yong-Guk Kim | Computer Vision | Best Researcher Award

Published on by Academic Achievements

Prof. Dr.Yong-Guk Kim | Computer Vision | Best Researcher Award

Professor at Sejong University, South Korea

Dr. Yong-Guk Kim is a Full Professor in the Department of Computer Engineering at Sejong University, Seoul, Korea, and a renowned expert in artificial intelligence and computer vision. His academic journey has taken him from Korea to prestigious institutions in the UK, Netherlands, and the US, contributing significantly to fields like Generative AI, facial expression recognition, and autonomous drone technology. With a career spanning over three decades, Dr. Kim has excelled in both academic research and industry collaborations, leading innovative AI projects and earning multiple accolades in international AI challenges.

Profile

ORCID

Education:

Dr. Kim completed his Ph.D. in Experimental Psychology, specializing in computational vision, from Cambridge University, where he explored visual surface representation for transparency, occlusion, and brightness. He also holds an M.S. in Electrical Engineering, majoring in Automatic Control, and a B.S. in Electrical Engineering, both from Korea University. His education set the foundation for a career at the intersection of engineering and cognitive science, particularly in AI and computer vision applications.

Experience:

Dr. Kim’s diverse career includes research roles at major organizations such as LG and KT in Korea, followed by advanced research opportunities abroad. He worked as a postdoctoral fellow at the Smith-Kettlewell Vision Institute in San Francisco and as an EU fellow at the Robotics Institute of Utrecht University in the Netherlands. He has served as a faculty member at Sejong University for over two decades, holding leadership positions such as Dean of International Affairs and Head of the Start-up Incubator. He has successfully founded the startup Affectronics, specializing in mobile 3D avatars, and played a pivotal role in several AI challenges, showcasing his expertise in applied AI.

Research Interest:

Dr. Kim’s primary research areas lie in Generative AI and Computer Vision. His work encompasses multi-modal large language models, video anomaly detection, and facial expression recognition, with a particular focus on real-world applications such as autonomous drones and personalized advertising platforms. His lab has made significant strides in AI-driven tasks, such as autonomous drone racing and emotion detection, winning multiple international competitions. His research is well-funded by both governmental bodies and private industries, highlighting the practical and impactful nature of his work.

Awards:

Dr. Kim has received numerous awards for his contributions to AI, particularly in global competitions. Notably, his lab won the prestigious Game of Drones Challenge in 2019, organized by Microsoft and Stanford University at the NeurIPS conference. He also placed second in the Inpainting and Denoising Challenge at the European Conference on Computer Vision (ECCV) in 2018 and won the Fake Emotion Detection Challenge at the International Conference on Computer Vision (ICCV) in 2017. These achievements underscore his prominence in the AI research community and his ability to lead teams in high-stakes, competitive environments.

Publications:

Dr. Kim has published extensively in top-tier journals, contributing to the advancement of AI and computer vision. His recent works include:

“Reinforcement Learning Based Drone Simulators: Survey, Practice, and Challenge” (2024) – Artificial Intelligence Review (Cited by: 281) Link.

“UET4Rec: U-net Encapsulated Transformer for Sequential Recommender” (2024) – Expert Systems with Applications (Cited by: 781) Link.

“Meme Analysis using LLM-based Contextual Information“ (2024) – IEEE Access (Cited by: 5) Link.

“Attention-based Residual Autoencoder for Video Anomaly Detection” (2023) – Applied Intelligence (Cited by: 240) Link.

“A Promising AI-based Tool to Simulate Hydrogen Sulfide Elimination” (2023) – Separation and Purification Technology (Cited by: 472) Link.

Conclusion:

Dr. Yong-Guk Kim’s extensive contributions to AI and computer vision, coupled with his successful track record in international AI challenges, academic excellence, and industry collaboration, make him a strong candidate for the Best Researcher Award. His teaching and entrepreneurial achievements further add to his case, demonstrating both academic prowess and real-world impact. By expanding his research into newer domains and engaging more with public discourse on AI, he could further solidify his standing as a world-class researcher.