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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
For those interested in visiting our group during the 2025 open school session (July 30 and 31), please check the flyer below.
News
News
7/26/2025: [Event] Kai F attended the Fujiwara award meeting at Kojunsha, Ginza, Japan, as an AY2020 awardee for his studies during the Master's degree course at Keio University. [Pictures]
7/17/2025: [Out now!] H. Odaka, K. Fukami, K. Taira, “Plunging airfoil wakes in low-order latent space coordinates,” in AIAA Aviation Forum 2025, Las Vegas, Nevada, USA, July 2025, AIAA paper 2025-3869.
7/10/2025: [Out now!] Our contribution to the 2nd Lagrangian Particle Tracking and Data Assimilation Challenges, presented at the ISFV21 and ISPIV2025 conference (a collaborative effort with TU Berlin and TU Delft; Rohlfs, Pelz, Doan, Fukami, & Steinfurth), has been released on the ONERA Flow Reconstruction Benchmark website.
7/9/2025: [Media] Our studies have been introduced on the Research Profile website of the head office of enterprise partnerships at Tohoku University.
7/3/2025: [Event] David Rival at TU Braunschweig visited us and gave a seminar talk on data-driven analysis for gusty aerodynamic flows. [Picture1] [Picture2]
6/27/2025: [Out now!] K. Fukagata, K. Fukami, “Compressing fluid flows with nonlinear machine learning: mode decomposition, latent modeling, and flow control," Fluid Dynamics Research, 57, 041401 (invited), 2025
6/23-27/2025: [Event] Sam Taira at UCLA visited us and gave a seminar talk on model-based flow control. [Picture]
6/17/2025: [Preprint] K. Yawata, R. Sakuma, K. Fukami, K. Taira, H. Nakao, “Phase autoencoder for rapid data-driven synchronization of rhythmic spatiotemporal patterns," arXiv:2506.12777 [nlin.AO], 2025
6/2/2025: [Preprint] K. Fukami, R. Araki, “Information-theoretic machine learning for time-varying mode decomposition of separated airfoil wakes," arXiv:2505.24132 [physics.flu-dyn], 2025
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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