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Kai Fukami Lab: Data Oriented Fluid Dynamics Group @ Tohoku University
We are the Data Oriented Fluid Dynamics Group at Tohoku University, launched in January 2025. The principal investigator is Kai Fukami, Ph.D., an Associate Professor in the Department of Aerospace Engineering, Tohoku University. Our group belongs to the Advanced Aerospace Engineering field in the Aerospace Engineering department.
Our group studies a range of unsteady flow phenomena leveraging data science, nonlinear machine learning, complex network theory, information theory, and computational fluid dynamics. Our ultimate goal is to build a data-oriented foundation for real-time analysis, modeling, and control of unsteady flows ubiquitously appearing in various situations around small air vehicles, airplanes, motor vehicles, and fluid-based industrial machines.
Address: 6-6-01, Aramaki-Aza-Aoba, Aoba-Ku, Sendai, Miyagi, 980-8579, Japan
Office: Room 403, Research Building No.1, Division of Mechanical Engineering, Tohoku University
News
News
10/3/2025: [New Member!] Yukiko Watanabe has joined our roster as a lab administrator. Welcome Yukiko!
10/1/2025: [Project] The project for JST PRESTO, “Establishing a low-rank manifold village toward mathematic prediction and control of unsteady flows," (PI: Kai Fukami) has been initiated.
10/1/2025: [Project] The project for MEXT Coordination Funds for Promoting AeroSpace Utilization, “Japan-originated compactification project for nonlinear aerodynamic phenomena with an ultra-high degree of freedom," (PI: Kai Fukami) has been initiated.
9/24/2025: [Out now!] K. Fukami, K. Fukagata, K. Taira, [SI] Next Generation Fluid Flow Analysis “Super-resolution analysis of turbulence with machine learning,” Nagare-Journal of Japan Society of Fluid Mechanics, 44 (3), 216-221 (invited), 2025
9/23/2025: [Preprint] K. Fukami, Y. Iwatani, S. Maejima, H. Asada, S. Kawai, “Compact representation of transonic airfoil buffet flows with observable-augmented machine learning,” arXiv:2509.17306 [physics.flu-dyn], 2025 (To appear in Journal of Fluid Mechanics)
9/17/2025: [Out now!] K. Taira, G. Rigas, K. Fukami, “Machine learning in fluid dynamics: A critical assessment," Physical Review Fluids, 10, 090701 (invited), 2025
9/13/2025: [Conference] Kai F's abstract at APS-DFD2025 (about Fukami & Araki, AIAA J., 2025) has been chosen as an interact session talk on Machine Learning for Fluid Mechanics.
Previous news can be found here.
For those interested in our group (Advanced Aerospace Engineering Field, Department of Aerospace Engineering, Tohoku University), please visit Join us! page and carefully read the requirements before taking any action.
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