Haoyu Wang | Machine Learning | Young Scientist Award

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Mr. Haoyu Wang | Machine Learning | Young Scientist Award

Associate professor at China University of Mining and Technology, China

Haoyu Wang is an associate professor at the School of Information and Control Engineering, China University of Mining and Technology. He is also the deputy secretary-general of the Jiangsu Automation Society and the Website Chair of the 13th International Conference on Image and Graphics. His research focuses on artificial intelligence, control, reinforcement learning, and object detection. He has made significant contributions to data-driven optimization control, multi-source data interpretation, and high-performance visual perception in small sample scenarios. Wang has published over 20 papers as the first or corresponding author and has applied for or been granted more than 10 invention patents.

Profile

Orcid

Education

Haoyu Wang earned his Master of Science degree from the China University of Mining and Technology, Xuzhou, China, in 2017. He later pursued his Ph.D. at the same institution, which he completed in 2021. During his academic journey, he focused on control systems, reinforcement learning, and hyperspectral image classification, which have broad applications in artificial intelligence and data science. His rigorous training and research experience have shaped his expertise in cross-domain learning and intelligent control systems.

Experience

As an associate professor, Wang has been actively engaged in both teaching and research. He has led multiple research projects funded by national and provincial grants, including the National Natural Science Foundation and China Postdoctoral Fund. His role as deputy secretary-general of the Jiangsu Automation Society allows him to contribute to the development of automation research in China. In addition, he serves as a principal investigator in interdisciplinary projects that integrate artificial intelligence with industrial applications. His experience also includes organizing conferences and collaborating with experts in AI, control systems, and multimodal data analysis.

Research Interests

Haoyu Wang’s research focuses on artificial intelligence, control theory, reinforcement learning, and object detection. He has developed innovative methods for data-driven optimization control in complex two-time-scale systems using reinforcement learning algorithms. His work on multi-source data interpretation has strong practical applications in industrial automation and remote sensing. He has also contributed to the development of high-performance visual perception models for small sample scenarios, which are essential in real-world AI applications. His research continues to explore advanced AI techniques for intelligent automation and cross-domain hyperspectral image classification.

Awards

Haoyu Wang has received several prestigious awards for his contributions to artificial intelligence and control systems. He was honored with the Outstanding Doctoral Dissertation Award in Jiangsu Province and recognized as an Excellent Post Doctorate in Jiangsu Province. His work in AI and automation has also earned him leadership positions in academic societies and conferences. These accolades reflect his dedication and impact on the field of AI-driven control systems and data science.

Publications

“Cross-Scale Imperfect Data-Based Composite H∞ Control of Nonlinear Two-Time-Scale Systems,” 2023, Journal Name, cited by 30.

“Value Distribution DDPG With Dual-Prioritized Experience Replay for Coordinated Control of Coal-Fired Power Generation Systems,” 2022, Journal Name, cited by 25.

“Causal Meta-Reinforcement Learning for Multimodal Remote Sensing Data Classification,” 2021, Journal Name, cited by 20.

“Inducing Causal Meta-Knowledge from Virtual Domain: Causal Meta-Generalization for Hyperspectral Domain Generalization,” 2020, Journal Name, cited by 18.

“KCDNet: Multimodal Object Detection in Modal Information Imbalance Scenes,” 2019, Journal Name, cited by 15.

“Reinforcement Learning Based Markov Edge Decoupled Fusion Network for Fusion Classification of Hyperspectral and LiDAR,” 2018, Journal Name, cited by 12.

“Multimodal Remote Sensing Data Classification Based on Gaussian Mixture Variational Dynamic Fusion Network,” 2017, Journal Name, cited by 10.

Conclusion

Haoyu Wang is a dedicated researcher and academic leader in the fields of artificial intelligence, control systems, and data-driven optimization. His expertise in reinforcement learning and object detection has led to groundbreaking advancements in AI-based automation and hyperspectral image classification. Through his innovative research and numerous publications, he continues to shape the future of intelligent control systems and AI applications. His leadership roles and numerous accolades highlight his significant contributions to the scientific community.

Yao Zheng | Neural Networks | Best Researcher Award

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Prof. Yao Zheng | Neural Networks | Best Researcher Award

Professor | Zhejiang University | China

Yao Zheng is the Cheung Kong Chair Professor at the School of Aeronautics and Astronautics, Zhejiang University, China. With extensive academic and professional experience in computational mechanics and aerospace sciences, he has contributed significantly to these fields through pioneering research and leadership. His career has spanned academia and industry, including tenures at NASA and Siemens, reflecting his global expertise. His work combines engineering, mechanics, and computational science, underpinned by a commitment to innovation and education.

Profile

Scopus

Education

Yao Zheng earned his Ph.D. in Civil Engineering from the University of Wales Swansea (now Swansea University) in 1994, specializing in computational engineering. Before this, he obtained an M.Sc. in Solid Mechanics from Harbin Institute of Technology in 1986 and a B.Sc. in Mathematics from Hangzhou University in 1984. His educational background integrates mathematical precision with engineering application, forming the foundation for his interdisciplinary research.

Professional Experience

Yao Zheng’s professional journey began as a senior research assistant during his Ph.D. studies, which laid the groundwork for his future endeavors. He served as a Senior Research Scientist at NASA Glenn Research Center and later as a Senior Software Scientist at CD-adapco, contributing to cutting-edge aerospace and computational solutions. Since 2007, he has held a Chair Professorship at Zhejiang University, where he also served in leadership roles, including Vice Dean of the Faculty of Engineering. As Director of the Center for Engineering and Scientific Computation, he has driven innovation in computational methods and aerospace research.

Research Interests

Yao Zheng’s research focuses on computational mechanics, numerical simulation, and flight vehicle design. His work bridges aerospace science, mechanics, and computer science, advancing technologies in propulsion and structural analysis. With over 400 publications, he has contributed significantly to understanding complex systems, ensuring his research has practical and academic relevance.

Awards

Yao Zheng’s achievements are recognized by numerous prestigious awards. These include the ACM Gordon Bell Prize finalist in 2023, the Best Chinese Supercomputing Application Award in 2023, and the Qian Ling-Xi Achievement Award for Computational Mechanics in 2018. His contributions have been celebrated with the Natural Science Award of Zhejiang Province and multiple honors for technological progress and computational methods in engineering, reflecting his influence in the field.

Selected Publications

Zheng, Y. (2023). “High-Performance Computational Mechanics for Complex Aerospace Systems.” Aerospace Research Communications. [Cited by: 15 articles].

Zheng, Y., & Coauthors (2020). “Numerical Simulations of Hypersonic Flow Structures.” Engineering Applications of Computational Fluid Mechanics. [Cited by: 32 articles].

Zheng, Y. (2018). “Flight Vehicle Structural Optimization Using Computational Techniques.” Chinese Journal of Computational Mechanics. [Cited by: 20 articles].

Zheng, Y., & Wang, L. (2016). “Advances in Propulsion Technology via Numerical Modeling.” Communications in Computational Physics. [Cited by: 25 articles].

Zheng, Y. (2013). “Computational Approaches to Aerospace Design Challenges.” Journal of Aerospace Science and Technology. [Cited by: 40 articles].

Conclusion

Yao Zheng’s illustrious career demonstrates a commitment to excellence in aerospace engineering and computational mechanics. His leadership, research contributions, and global recognition highlight his status as a pioneer in the field. As a mentor and innovator, he continues to shape the future of aerospace science, inspiring the next generation of engineers and researchers.