Xiping Duan | Visual Tracking | Best Researcher Award

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Dr. Xiping Duan | Visual Tracking | Best Researcher Award

Associate Professor at  Harbin Normal University, China

Dr. Xiping Duan is a highly regarded Associate Professor with a Doctor of Engineering degree and a Master’s Thesis Advisor title. Her expertise spans critical areas in artificial intelligence, particularly in computer vision and evidence reasoning. Through an extensive academic journey, Dr. Duan has played a pivotal role in advancing knowledge in intelligent perception, decision-making models, and tracking technologies. Her interdisciplinary approach and continuous pursuit of innovative methodologies have placed her among the noteworthy researchers in her field. Known for both leadership and teamwork, she contributes significantly to academic progress through impactful research, dedicated mentorship, and strong collaboration across institutional and disciplinary boundaries.

Profile

Scopus

Education

Dr. Duan holds a Doctorate in Engineering, where her academic foundation was built upon rigorous training in information processing, machine learning, and pattern recognition. Her doctoral studies provided her with an in-depth understanding of high-performance computing and intelligent systems, which later became central to her academic pursuits. Her educational background is also marked by a consistent focus on integrating theory with practical application—particularly in areas such as object tracking and knowledge-based systems.

Experience

In her role as Associate Professor, Dr. Duan has led several influential projects and mentored graduate students across topics ranging from computer vision algorithms to intelligent diagnosis systems. She has served as the principal investigator and team member on multiple funded research projects supported by national and provincial institutions. Notably, she hosted the project “Key Technology Research on Video Object Tracking” funded by the Heilongjiang Provincial Education Fund. She also contributed to national-level research on soil and water conservation and mobile database consistency. Her multifaceted involvement in both teaching and research illustrates a career grounded in academic excellence and applied science.

Research Interest

Dr. Duan’s research interests lie at the intersection of artificial intelligence, image processing, and evidence reasoning. Her work has focused on developing algorithms that enhance object tracking performance and on building interpretable models for complex decision-making tasks. A particular emphasis has been placed on belief rule bases and multi-modal feature integration for intelligent prediction systems. Her current research includes pyramid channel attention mechanisms, interpretable deep belief systems for disease diagnosis, and advanced video tracking technologies. These endeavors reflect her commitment to solving real-world problems using cutting-edge AI technologies.

Award

Dr. Duan was honored with the Second Prize for Scientific and Technological Progress by the People’s Government of Heilongjiang Province in December 2010. This prestigious recognition was awarded for her contributions to the development of a non-contact, high-speed, and high-precision detection system for the outer diameter of tapered rollers. The accolade highlights her capability to translate research innovations into practical solutions with high industrial value. Her ability to bridge the gap between academic inquiry and technological application has earned her both peer respect and institutional accolades.

Publication

Dr. Duan has published several impactful papers in well-regarded international journals. A selection of her recent publications includes:

  1. “A Target Tracking Method Based on a Pyramid Channel Atten tion Mechanism,” Sensors, 2025; cited by 15 articles.

  2. “A Chronic Kidney Disease Diagnostic Model Based on an Interpretable Deep Belief Rule Base,” IEEE Access, 2025; cited by 11 articles.

  3. “A Tunnel Squeezing Prediction Model Based on the Hierarchical Belief Base,” IEEE Access, 2024; cited by 9 articles.

  4. “Improved ECO Object Tracking Algorithm Using GhostNet Convolutional Features,” Laser Technology, 2022; cited by 17 articles.

  5. “Video Object Tracking with Multi-Modal Features Joint Sparse Representation,” Journal of Harbin Engineering University, 2015; cited by 21 articles.

  6. “A Semantic-Level Text Collaborative Image Recognition Method,” Journal of Harbin Institute of Technology, 2014; cited by 24 articles.

Conclusion

In conclusion, Dr. Xiping Duan exemplifies a dedicated researcher and academic leader in the fields of artificial intelligence and computer vision. Her scholarly contributions, including peer-reviewed publications and successful project leadership, demonstrate a strong trajectory of academic achievement. Her recognized innovation in detection and tracking technologies has not only advanced theoretical research but also found relevance in practical engineering applications. With her dynamic combination of technical expertise, mentorship, and recognition through awards, Dr. Duan is an exemplary candidate for the “Best Researcher Award.”

Zhaoxiang Zhang | Object Tracking | Best Researcher Award

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Prof. Dr. Zhaoxiang Zhang | Object Tracking | Best Researcher Award

Professor at Unmanned System Research Institute, Northwestern Polytechnical University, China

Professor Zhaoxiang Zhang is a distinguished researcher at the Unmanned System Research Institute of Northwestern Polytechnical University. His academic career is characterized by profound contributions to the fields of aerospace engineering, computer vision, and autonomous systems. With a strong foundation in remote sensing and artificial intelligence, Prof. Zhang has emerged as a thought leader in processing point cloud data, developing robust unsupervised learning models, and advancing autonomous navigation technologies. His research has not only contributed to the theoretical development of these fields but also addressed critical real-world challenges in aerospace and defense sectors.

Profile

Scopus

Education

Prof. Zhang pursued his academic training with a strong focus on aerospace technologies, remote sensing, and computational intelligence. His higher education and doctoral research revolved around spaceborne sensing systems, satellite navigation, and sensor fusion. This background equipped him with the analytical and technical foundation to bridge aerospace engineering with cutting-edge AI techniques. His graduate work emphasized image registration and attitude estimation, laying the groundwork for his later innovations in visual navigation and deep learning-based object tracking.

Experience

With years of experience leading both academic and applied research, Prof. Zhang has played a pivotal role in projects funded by the National Natural Science Foundation of China and multiple defense-sector institutions. He has successfully led a Youth Program grant and steered three vertical defense research subjects and two provincial-level initiatives. His research leadership spans the development of advanced deep learning architectures, unsupervised domain adaptation techniques, and lightweight models suitable for embedded aerospace systems. Prof. Zhang also contributes significantly to mentorship, guiding student teams that have earned national innovation awards and top honors at competitions like the Challenge Cup and Internet+ National Games.

Research Interests

Prof. Zhang’s research interests are multidisciplinary, encompassing aerospace target detection and recognition, attitude estimation, point cloud segmentation, multimodal data integration, and unsupervised model transfer. He focuses particularly on non-cooperative target tracking and cross-domain visual matching, crucial for autonomous navigation in dynamic or GPS-denied environments. His work also delves into scene change detection, pixel-level anomaly recognition, and the development of efficient, lightweight neural architectures for real-time applications on UAVs and small satellites. The fusion of AI with aerospace engineering in his work exemplifies a high-impact intersection of disciplines.

Awards

Prof. Zhang’s dedication to innovation and excellence has earned him national recognition. Notably, he has been honored with the Internet+ National Games Silver Award (twice) and the first prize in the prestigious Challenge Cup competition. Under his guidance, research group students have produced outstanding innovation outcomes recognized at the national level. These accolades underline his ability not only to conduct pioneering research but also to cultivate the next generation of innovators in aerospace AI technologies.

Publications

Prof. Zhang has authored over ten SCI-indexed publications as first or corresponding author. Seven of his most notable works include:

  1. Zhang Z, Ji A, Zhang L, et al. (2023). Unsupervised seepage segmentation pipeline based on point cloud projection with large vision model. Tunnelling and Underground Space Technology — cited by 25 articles.

  2. Zhang Z, Xu Y, Song J, et al. (2023). Robust pose estimation for non-cooperative space objects. Scientific Reports — cited by 18 articles.

  3. Zhang Z, Xu Y, Song J, et al. (2023). Planet craters detection using unsupervised domain adaptation. IEEE Transactions on Aerospace and Electronic Systems — cited by 30 articles.

  4. Zhang Z and Zhang L (2023). Rail Surface Defects Detection Using Multistep Domain Adaptation. IEEE Transactions on Systems, Man, and Cybernetics: Systems — cited by 22 articles.

  5. Zhang Z, Ji A, Zhang L, et al. (2023). Deep learning for large-scale point cloud segmentation with causal inference. Automation in Construction — cited by 27 articles.

  6. Zhang Z, Xu Y, Cui Q, et al. (2022). Unsupervised SAR and Optical Image Matching. IEEE Transactions on Geoscience and Remote Sensing — cited by 41 articles.

  7. Song J, Zhang Z, Iwasaki A, et al. (2021). Augmented H∞ Filter for Satellite Jitter Estimation. IEEE Transactions on Aerospace and Electronic Systems — cited by 36 articles.

Conclusion

Professor Zhaoxiang Zhang stands at the forefront of integrating artificial intelligence with aerospace engineering. His extensive contributions in the domains of remote sensing, point cloud processing, and autonomous navigation have significantly advanced both theoretical frameworks and practical applications. As a mentor and leader, his influence extends beyond his own research to shaping the future of technological innovation through his students and collaborations. With a track record of impactful publications, national awards, and strategic project leadership, Prof. Zhang exemplifies the qualities of a transformative scientific thinker deserving of recognition in AI data science.