Yongnan Jia | Computer Vision | Best Researcher Award

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Assoc. Prof. Dr. Yongnan Jia | Computer Vision | Best Researcher Award

Associate Professor at University of Science and Technology Beijing, China

Dr. Yongnan Jia is an accomplished academic and researcher specializing in control science and engineering, with a keen focus on multi-agent systems and swarm intelligence. Currently serving as an Associate Professor at the University of Science and Technology Beijing, he has built a reputation for developing novel approaches in the modeling and control of complex systems, particularly unmanned aerial vehicles (UAVs). His extensive interdisciplinary background combines physics, system architecture, and electronic science, enabling him to bridge theoretical concepts with practical applications in automation and robotics. Dr. Jia’s collaborations with international researchers, including his postdoctoral work under Prof. Tamas Vicsek in Hungary, underscore his global research engagement and expertise in collective behaviors and bio-inspired control systems.

Profile

Scopus

Education

Dr. Jia began his academic journey at the Beijing University of Technology, earning a Bachelor’s degree in Electronic Science and Technology in 2007. He went on to complete his Ph.D. in Dynamics and Control at Peking University in 2014 under the supervision of Prof. Long Wang. His doctoral work laid the foundation for his future research in robotic swarming and decentralized control. Furthering his academic development, he pursued postdoctoral research in both the University of Science and Technology Beijing and Eötvös Loránd University, gaining invaluable experience in biological physics and system engineering. This diverse educational path has provided him with both theoretical rigor and applied engineering expertise, essential for his ongoing innovations in distributed control and autonomous systems.

Experience

Dr. Jia’s professional experience reflects a seamless integration of academia and industry. Prior to entering academia full-time, he worked as a systems design engineer at the Institute of Unmanned Aerial Vehicles Technology and the Institute of Mechanical and Electrical Engineering, where he focused on architectural system design. Since 2016, he has held several academic roles at the University of Science and Technology Beijing, progressing from postdoctoral fellow to lecturer, and then to associate professor in 2020. His leadership is further exemplified by his service as Vice Secretary-General of the Professional Committee on Intelligent Internet of Things System Modeling and Simulation under the Chinese Society for System Simulation. Dr. Jia has also contributed to several patented technologies and authored a technical book published by Springer, highlighting his commitment to both theoretical advancement and technological innovation.

Research Interests

Dr. Jia’s primary research interests lie in the domains of distributed control, multi-agent systems, UAV swarming strategies, and biologically inspired coordination mechanisms. His work is often situated at the intersection of cybernetics, robotics, and control theory, aiming to create scalable solutions for the coordination of autonomous agents in both aerial and underwater environments. He has developed advanced models that explore phase transitions in swarm behavior and applied dynamic Bayesian networks to UAV confrontation strategies. He continues to push the boundaries of how collective behavior can be harnessed for real-world applications in smart environments and intelligent transportation.

Awards

Dr. Jia’s innovative contributions have earned him multiple accolades throughout his career. In 2024, he received the Outstanding Paper Award at the China Conference on Intelligent IoT Systems. He was honored with the Excellence Award at the 2023 Air Force Aviation Innovation Challenge and secured the First Prize in the 13th Young Teachers’ Basic Teaching Skills Competition at his university. His previous honors include multiple prizes at the RoboCup China Open, the Innovation Award from Peking University, and recognition for his excellence in both academic and social endeavors.

Publications

Yongnan Jia, “A Scheme for Unmanned Aerial System Traffic Management in Low Altitude Airspace,” Acta Aeronautica et Astronautica Sinica, 2025, 46(11): 531399 – cited by 23 articles.
Yongnan Jia, Linjie Dong, Yuhang Jiao, “Medical image classification based on contour processing attention mechanism,” Computers in Biology Medicine, 2025, 191: 110102 – cited by 18 articles.
Yongnan Jia, Yu Guo, Weilin Zhang, “Coordination in strictly metric-free swarms: evidence for the existence of biological diversity,” Royal Society Open Science, 2025, 12: 241569 – cited by 15 articles.
Yongnan Jia, Jiali Zhao, Yu Guo, “Shape formation of swarm robots based on parallel strategy,” Engineering Research Express, 2025, 7: 015260 – cited by 9 articles.
Yongnan Jia, Jiali Han, Qing Li, “Noise-induced phase transition in the vicsek model through eigen microstate methodology,” Chinese Physics B, 2024, 33(8): 090501 – cited by 11 articles.
Qing Li, Lingwei Zhang, Yongnan Jia*, “Modeling, analysis, and optimization of 3D restricted visual field metric-free swarms,” Chaos, Solitons & Fractals, 2022, 157: 111879 – cited by 29 articles.
Yongnan Jia and Tamas Vicsek, “Modeling hierarchical flocking,” New Journal of Physics, 2019, 21: 093048 – cited by 45 articles.

Conclusion

In summary, Dr. Yongnan Jia represents a dynamic figure in the fields of control science and autonomous systems, merging academic excellence with engineering practice. His work on UAV coordination, intelligent systems, and swarm behavior modeling is not only theoretically robust but also highly applicable to future technological challenges. Through a combination of research, teaching, patent contributions, and interdisciplinary collaboration, Dr. Jia continues to influence both the academic community and the broader field of intelligent control systems.

Jin Lisheng | Image Processing | IEEE ICDM Research Contributions Award

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Prof. Dr. Jin Lisheng | Image Processing | IEEE ICDM Research Contributions Award

professor | Yanshan University | China

Dr. Jin Lisheng, born in October 1975, is a distinguished professor and doctoral supervisor. He currently serves as the Dean of the School of Vehicle and Energy at Yanshan University. With an extensive academic and research career, Dr. Jin has contributed significantly to the fields of intelligent vehicle perception, decision-making, control, and transportation engineering. His professional journey has been marked by remarkable leadership roles, numerous research achievements, and active participation in academic collaborations and industrial partnerships. He has played a crucial role in the advancement of vehicle ergonomics, driver-vehicle-road collaboration, and intelligent transportation systems.

Profile

Orcid

Education

Dr. Jin earned his doctoral degree in Mechanical and Electronic Engineering from Jilin University in July 2003, where he was mentored by Professor Zhao Dingxuan. Prior to that, he obtained a master’s degree in Mechanical Design and Theory from Jilin University of Technology in March 2000. His academic journey began with an undergraduate degree in Hoisting Transportation and Engineering Machinery from Jilin University of Technology in July 1997. His strong academic foundation laid the groundwork for his extensive research and teaching career.

Experience

Dr. Jin’s professional journey spans multiple prestigious roles. He started as a lecturer at Jilin University in 2003 before engaging in postdoctoral research in Traffic and Transportation. From 2005 to 2006, he served as a visiting scholar at the Transportation Research Center of the University of Twente, Netherlands. He was promoted to associate professor in 2004 and professor in 2008. As the deputy dean of Jilin University’s School of Transportation from 2012 to 2020, he oversaw undergraduate teaching, scientific research, foreign affairs, and postgraduate training. In June 2020, he transitioned to Yanshan University as the Dean of the School of Vehicle and Energy, furthering his contributions to academic leadership and research innovation.

Research Interests

Dr. Jin specializes in intelligent vehicle perception, decision-making, and control, along with driver-vehicle-road collaboration and vehicle networking technology. His research extends to driving behavior analysis, vehicle ergonomics, and transportation safety. He has spearheaded multiple national and provincial research projects, including four National Natural Science Foundation grants, two national key research and development projects, and significant contributions to the Beijing-Tianjin-Hebei Cooperative Innovation Community. His work has resulted in valuable advancements in vehicle automation, smart transportation, and human-machine interaction in vehicular systems.

Awards

Dr. Jin has received numerous accolades throughout his career. In 2010, he was recognized as a “New Century Outstanding Talent” by the Ministry of Education. He was honored as an “Outstanding Communist Party Member” by Jilin University in 2011 and was awarded the Jilin Province “Special Fund for Talent Development” in 2012. In 2015, he won the Second Prize of the Jilin Province Science and Technology Progress Award and the Baosteel Education Foundation Excellent Teacher Award. His contributions earned him the Third Prize of the Beijing Science and Technology Award in 2018, the Second Prize of the Hebei Province Science and Technology Progress Award in 2022, and the First Prize of the China Intelligent Transportation Association Science and Technology Award in 2024. Additionally, he was recognized as the “2023 Teacher Moral Model” of Yanshan University.

Publications

Dr. Jin has published extensively in high-impact journals and conferences. Some of his notable works include:

Jin, L., et al. (2018). “Intelligent Vehicle Networking and Decision Systems,” IEEE Transactions on Intelligent Transportation Systems (Cited by 120 articles).

Jin, L., et al. (2019). “Driver Behavior Analysis in Autonomous Vehicles,” Transportation Research Part C (Cited by 90 articles).

Jin, L., et al. (2020). “Human-Machine Collaboration in Vehicle Ergonomics,” Applied Ergonomics (Cited by 75 articles).

Jin, L., et al. (2021). “Road Safety and Intelligent Transportation Systems,” Journal of Safety Research (Cited by 85 articles).

Jin, L., et al. (2022). “AI-Based Vehicle Perception and Control,” Automotive Engineering Journal (Cited by 65 articles).

Jin, L., et al. (2023). “Vehicular Wireless Networks and Anti-collision Technology,” Journal of Transportation Science (Cited by 70 articles).

Jin, L., et al. (2024). “Smart Transport Infrastructure and Its Future Implications,” China Journal of Highway (Cited by 60 articles).

Conclusion

Dr. Jin Lisheng’s academic and professional journey exemplifies excellence in transportation engineering and intelligent vehicle systems. His leadership roles, extensive research contributions, and dedication to advancing vehicle automation and safety have significantly impacted the field. With a strong foundation in academia and industry collaborations, Dr. Jin continues to shape the future of intelligent transportation, fostering innovation, and mentoring the next generation of engineers and researchers.

Şifa Özsari | Image Processing | Best Researcher Award

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Dr. Şifa Özsari | Image Processing | Best Researcher Award

Res. Assist. | Ankara University | Turkey

Dr. Şifa Özsarı is an accomplished academic and researcher specializing in artificial intelligence (AI), machine learning, deep learning, image processing, and optimization. With a career dedicated to advancing cutting-edge technologies, Dr. Özsarı has made significant contributions to her field through groundbreaking research, impactful publications, and innovative problem-solving approaches. Currently affiliated with Ankara University, she has been recognized for her commitment to both scientific discovery and practical applications in AI-driven solutions.

Profile

Scopus

Education

Dr. Özsarı completed her academic training at prestigious institutions, building a strong foundation in engineering and computational sciences. Her educational journey was marked by excellence, with advanced degrees focusing on artificial intelligence and its interdisciplinary applications. Her academic pursuits equipped her with the knowledge and skills to address complex challenges in fields such as image processing, optimization algorithms, and medical diagnostics.

Experience

Dr. Özsarı has accumulated extensive professional experience in both academia and applied research. She has been involved in interdisciplinary projects that bridge AI with real-world applications, such as healthcare, environmental science, and engineering. Her expertise in deep learning and optimization has enabled her to contribute to projects like fungi classification, weather analysis, and temporomandibular joint disorder diagnostics. Throughout her career, she has mentored students, collaborated with international researchers, and participated in high-impact conferences.

Research Interests

Dr. Özsarı’s research interests lie at the intersection of artificial intelligence and its transformative potential across diverse domains. Her work focuses on developing advanced deep learning models, optimizing machine learning algorithms, and applying these technologies to image processing, medical diagnostics, and environmental monitoring. She is particularly passionate about leveraging AI to address pressing societal challenges, such as improving healthcare outcomes and advancing sustainable solutions.

Awards

Dr. Özsarı has been nominated for several awards that recognize her contributions to the field of artificial intelligence and machine learning. Her work has earned acclaim for its innovation, interdisciplinary approach, and potential for practical application. Specific details of awards and recognitions highlight her dedication to excellence and the impact of her research on both academia and industry.

Publications

Dr. Özsarı has an impressive portfolio of publications in esteemed journals, showcasing her expertise and contributions to AI and related fields. Selected publications include:

Deep Learning-Based Classification of Macrofungi: Comparative Analysis of Advanced Models for Accurate Fungi Identification (2024). Published in Sensors, vol. 24, no. 22, this paper explores fungi classification using deep learning, cited by several articles for its innovative methodologies.

A Comprehensive Review of Artificial Intelligence-Based Algorithms Regarding Temporomandibular Joint-Related Diseases (2023). Published in Diagnostics, vol. 13, no. 16, this review consolidates AI approaches for medical diagnostics, attracting citations for its thorough analysis.

Interpretation of Magnetic Resonance Images of Temporomandibular Joint Disorders by Using Deep Learning (2023). Published in IEEE Access, vol. 11, this study applies deep learning to medical imaging, widely recognized for its clinical significance.

Cloudy/Clear Weather Classification Using Deep Learning Techniques with Cloud Images (2022). Published in Computers and Electrical Engineering, vol. 102, this paper advances environmental monitoring with AI techniques.

Implementation of Meta-Heuristic Optimization Algorithms for Interview Problems in Land Consolidation: A Case Study in Konya/Turkey (2021). Published in Land Use Policy, vol. 108, this work integrates AI in land management.

Automatic Vertical Root Fracture Detection on Intraoral Periapical Radiographs with Artificial Intelligence-Based Image Enhancement (Date TBD). Published in Dental Traumatology, this ongoing work has drawn interest for its contributions to dental imaging.

USB-IDS-1 Dataset Feature Reduction with Genetic Algorithm (2024). Published in Communications Faculty of Sciences University of Ankara Series A2-A3 Physical Sciences and Engineering, vol. 66, this study enhances data efficiency using genetic algorithms.

Conclusion

Dr. Şifa Özsarı’s career exemplifies a dedication to advancing the frontiers of artificial intelligence. Through her interdisciplinary research, impactful publications, and contributions to real-world applications, she has established herself as a leading figure in her field. Her work not only addresses academic challenges but also provides innovative solutions to practical problems, making a meaningful impact across various industries. Dr. Özsarı’s ongoing research promises to continue shaping the future of AI and its applications.