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2025年11月17日学术报告

编辑:赵顺毅    时间:2025-11-17    点击数:    来源:彭力    文、图:彭力

报告人 Masaki Ogura, Professor, Hiroshima University 讲座题目 Towards Operational and Scalable Control Strategies for Complex Systems

Time: 9:30-11:00 (Morning), Monday, November 17

Place: B222, School of Internet of Things Engineering


Abstract: This talk outlines a practical path toward operational and scalable control of complex, large-scale systems by drawing on three active research threads. First, I will show how cyborg insects fitted with neural–electrical interfaces can be guided safely and reliably without centralized coordination, providing a living test-bed for low-power, agile mobility. Second, I will examine swarm shepherding, presenting methods that let a few “sheepdog” agents gather and steer large, diverse groups even under severe sensing and communication limits. Third, I will describe recent work on weather intervention, where black-box search combined with model-predictive control selects atmospheric adjustments that can moderate heavy rainfall while respecting operational constraints. Together, these studies suggest that practical tools for managing highly networked, uncertain systems are within reach, yet they also highlight persistent questions about scalability, safety assurance, and the transition from simulation to real-world deployment. I will conclude with brief reflections on possible avenues for future exploration.



Vita:Masaki Ogura is a Professor in the Graduate School of Advanced Science and Engineering at Hiroshima University, Japan, following appointments as Postdoctoral Researcher in the Department of Electrical and Systems Engineering at the University of Pennsylvania (2014–2017), Assistant Professor in the Graduate School of Information Science at the Nara Institute of Science and Technology (2017–2019), Associate Professor in the Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University (2019–2024). His research spans swarm control, self-organization, artificial intelligence, and complex systems, integrating control theory with machine learning to elucidate and steer collective behavior in networked multi-agent systems. Ogura has authored four books and more than one hundred peer-reviewed papers that are frequently cited across control engineering and network science. He serves as Associate Editor for the Journal of the Franklin Institute (2020–present), IET Control Theory & Applications (2022–present), and Franklin Open (2022–present), and was Associate Editor for NecSys’15, while routinely reviewing for leading control journals and organizing international conferences. His recognitions include Runner-up for the 2019 Best Paper Award of the IEEE Transactions on Network Science and Engineering, the 2012 SICE Best Paper Award, the Cash Family Endowed Fellowship (2013), and the Summer Dissertation/Thesis Research Award (2014) from Texas Tech University.


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