Yunxia Chen | Data Science | Best Researcher Award | 13362

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Prof. Yunxia Chen | Data Science | Best Researcher Award 

Prof. Yunxia Chen, School of Reliability and Systems Engineering, Beihang University, China

Prof. Yunxia Chen is a distinguished researcher and professor at the School of Reliability and Systems Engineering, Beihang University, China. Her pioneering work in system reliability has led to significant advancements in failure mechanism modeling, life prediction, and high-reliability design. With over 57 SCI publications, 43 patents, and leadership in multiple national projects, she has shaped both academic and industrial practices. Prof. Chen’s collaborations with top international researchers and her leadership roles in global conferences reflect her influence in the field. Her contributions have earned her two prestigious National Defense Science and Technology Progress Awards.

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Scopus

🌱 Early Academic Pursuits

Prof. Yunxia Chen’s academic journey began with a deep-rooted interest in systems engineering and mechanical reliability—fields that demand both precision and vision. Her early education laid a strong foundation in engineering principles, which she further solidified through her pursuit of a doctoral degree. Earning her Ph.D. equipped her with advanced knowledge and skills to tackle the complexities of system reliability. These formative years were marked by curiosity, discipline, and a relentless pursuit of knowledge—traits that would define her future contributions to engineering science.

🏛️ Professional Endeavors

Prof. Chen currently serves as a Professor and Research Dean at the School of Reliability and Systems Engineering, Beihang University, one of China’s premier research institutions. Over the years, she has built a robust portfolio of leadership roles in research and academia. Her professional scope extends beyond traditional academic duties to include shaping national and international engineering standards, managing high-impact research projects, mentoring emerging scholars, and fostering interdisciplinary collaborations.

Her commitment to innovation and academic excellence is evidenced by her role in the development of two national industry standards, showcasing her impact on policy as well as practice. Moreover, her ability to balance administrative, teaching, and research responsibilities highlights her dynamic and multifaceted academic persona.

🔬 Contributions and Research Focus

Prof. Chen has made groundbreaking contributions in the domain of complex system reliability, particularly in understanding failure mechanism evolution, failure behavior propagation, and data-physics-driven prognostics. Her research interests span:

  • Reliability modeling and simulation of complex systems

  • High-reliability and long-lifetime design techniques

  • Experimental methodologies for small-sample evaluation

  • Fault-physics based verification systems

  • Advanced prognostics and health management systems (PHM)

Notably, she has authored over 57 SCI-indexed journal papers, published a monograph, and holds 43 authorized invention patents. Her research has had over 1200 citations, including 31 publications in top-tier journals and one highly cited paper, demonstrating her work’s relevance and influence.

Prof. Chen’s research portfolio includes 12 major projects, 35 consultancy assignments, and numerous editorial responsibilities. Her active involvement as an Area Editor, Program Committee Member, and Organizing Chair for prestigious international conferences further underscores her commitment to the global scientific community.

🏆 Accolades and Recognition

Prof. Chen’s scholarly achievements have been recognized with two First Prizes in the National Defense Science and Technology Progress Awards—one of the highest honors in China’s scientific community. These awards celebrate her pioneering work in system reliability research and her impactful role in advancing national defense technologies.

In addition, she holds several editorial and leadership positions in major technical journals and societies, including:

  • Executive Committee Member, Reliability Engineering Branch (CSME)

  • Vice Chairman, Reliability Branch of the China Electronics Society

Her leadership and expertise are widely acknowledged within both academic and industrial circles, further validating her status as a thought leader in her field.

🌍 Impact and Influence

Prof. Chen’s influence extends beyond borders. She has engaged in high-impact collaborations with renowned scholars such as Professor Frank Lam, Professor Terje Haukaas, and Professor Gadala Mohamed S. at the University of British Columbia, Canada. These collaborations explore reliability system modeling based on fault physics, facilitating knowledge exchange and co-development of innovative solutions.

Her work has shaped engineering practices, industry standards, and higher education curricula, setting benchmarks for excellence in system reliability engineering. As a mentor, she has inspired and guided numerous young researchers who are now making their own contributions to the field.

🌟 Legacy and Future Contributions

As she continues to lead cutting-edge research and influence future generations, Prof. Chen’s legacy lies in her integrative approach to engineering challenges—combining theory, practice, data, and innovation. She envisions a future where smart, self-healing systems proactively adapt to environmental and operational stresses, thus minimizing failure and maximizing safety and efficiency.

In the coming years, her focus will include:

  • Enhancing AI-integrated reliability prediction systems

  • Developing intelligent, adaptive maintenance strategies

  • Expanding international research networks for collaborative problem-solving

Publication Top Notes

Causal graph-based spatial–temporal attention network for RUL prediction of complex systems

Author: S., Zheng, Shuwen, J., Liu, Jie, Y., Chen, Yunxia, Y., FAN, Yu, D., Xu, Dan
Journal: Computers and Industrial Engineering, 
Year: 2025

Meta-learning collaborative optimization for lifetime prediction of lithium-ion batteries considering label noise

Author: G., Wang, Guisong, C., Wang, Cong, Y., Chen, Yunxia, J., Liu, Jie

Journal: Energy Storage,

Year: 2025

Unsupervised dynamic prognostics for abnormal degradation of lithium-ion battery

Author: C., Wang, Cong, Y., Chen, Yunxia

Journal: Applied Energy,

Year: 2024

 

 

Huilin YIN | AI Security | Best Researcher Award | 13346

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Prof. Huilin YIN | AI Security | Best Researcher Award 

Prof. Huilin YIN, Tongji University, China

Professor Huilin Yin of Tongji University is a distinguished researcher specializing in intelligent vehicle environmental perception and autonomous driving safety. With an H-index of 8 and over 430 citations, Prof. Yin has led groundbreaking projects, including a major NSFC-funded study on collaborative decision-making in industrial systems and consultancy for Continental Holding China. Her research spans visual-inertial SLAM, multi-object tracking, and trajectory prediction. Widely published in top-tier SCI/Scopus-indexed journals and conferences, she continues to pioneer advanced solutions that shape the future of intelligent transportation systems.

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Google Scholar

🎓 Early Academic Pursuits

Prof. Huilin Yin began her academic journey with a keen interest in the convergence of technology, artificial intelligence, and transportation. Her early education was marked by a solid foundation in engineering and computer science, which fueled her fascination with intelligent systems and autonomous technologies. Driven by curiosity and a passion for innovation, she pursued advanced degrees focusing on robotics, machine learning, and perception technologies—all of which laid the groundwork for her future endeavors in autonomous driving and smart mobility.

Her early academic milestones reflect a strong commitment to addressing real-world challenges through research. By the time she transitioned into academia as a professor, she had already distinguished herself through her academic diligence and innovative thinking.

💼 Professional Endeavors

Currently a professor at Tongji University, China, Prof. Yin leads cutting-edge research in environmental perception for intelligent vehicles and autonomous driving safety. Her professional journey is characterized by a seamless blend of academic excellence and industrial collaboration. One of her most prominent projects, titled “Interactive Learning and Collaborative Decision-Making of the Full-Element Integration in Industrial Production Systems,” was funded by the National Natural Science Foundation of China (Grant No. 62133011). This project underscores her role in advancing AI-driven decision systems in complex industrial and vehicular contexts.

Her consultancy work with Continental Holding China Co., Ltd. on multi-target trajectory prediction further highlights her technical expertise and industry relevance. In this capacity, she acted as a technical consultant, guiding the development of predictive technologies based on roadside data from 2023 to 2024.

🔍 Contributions and Research Focus

Prof. Yin’s contributions are at the intersection of robotics, autonomous navigation, perception systems, and deep learning. Her primary research interests include:

  • SLAM (Simultaneous Localization and Mapping) technologies

  • Object tracking and detection using LiDAR and camera fusion

  • Deep learning applications for trajectory prediction

  • Visual-inertial navigation systems (VINS)

  • Path planning with reinforcement learning

She has published extensively in SCI/Scopus-indexed journals and conferences, with standout contributions such as:

  • DP-VINS: A dynamic plane-based visual-inertial SLAM for autonomous vehicles

  • Ground-optimized SLAM using hierarchical loop closure detection

  • Zero-shot robustness in autonomous driving using Segment-Anything models

  • Curiosity-driven deep reinforcement learning for AGV path planning

Her works often bridge theoretical models with real-world applications, contributing both to academic literature and industrial innovation.

🏆 Accolades and Recognition

Prof. Yin has achieved commendable recognition within the scientific and academic community. Her H-index of 8 and 433 total citations reflect the growing impact of her research in the domains of intelligent transportation and autonomous systems. Though still in the earlier phase of her academic career, she has rapidly become a respected voice in the field through both national-level research projects and international conference presentations.

Her active participation in premier platforms like the IEEE International Conference on Intelligent Transportation Systems (ITSC) and CASE 2023 in New Zealand demonstrates her engagement with global academic communities.

🌍 Impact and Influence

Prof. Yin’s research plays a vital role in advancing smart mobility and safety technologies. By contributing robust, scalable solutions for environmental perception and trajectory prediction, her work influences how modern autonomous systems navigate complex environments. Her collaborative work with industry leaders like Continental underscores the real-world applicability of her research. Moreover, the tools and frameworks she develops are highly adaptable, positioning them as foundational blocks for future AI-integrated mobility systems worldwide.

🔮 Legacy and Future Contributions

Looking ahead, Prof. Yin is poised to continue leading innovative research that transforms the landscape of autonomous transportation. Her future focus includes:

  • Enhancing human-vehicle interaction via AI models

  • Developing universally adaptable SLAM systems for global deployment

  • Deepening the fusion of LiDAR and camera data for richer environmental perception

  • Pioneering ethical and secure AI-driven decision-making systems

With her strategic vision and a solid track record, Prof. Huilin Yin is set to become a pivotal figure in shaping the next generation of intelligent vehicles and autonomous systems.

Publication Top Notes

Multi-agent reinforcement learning for cooperative lane changing of connected and autonomous vehicles in mixed traffic

Author: W Zhou, D Chen, J Yan, Z Li, H Yin, W Ge
Journal: Autonomous Intelligent Systems
Year: 2022

Trajectory prediction for intelligent vehicles using spatial‐attention mechanism

Author: J Yan, Z Peng, H Yin, J Wang, X Wang, Y Shen, W Stechele, D Cremers
Journal: Intelligent Transport Systems
Year: 2020