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English version is here. 
(2021ǯ)
 ظ 콤Ǥϳءϳ콤
 ظʰѰ
 ز 鸡ƤѰ ѰĹ
 ز 踡ƤѰ Ѱ
 ز ήϳطϾѰ ѰĹ
 ز ֵ¸ ô
 βǥץ֥ХĶƥץ ץô
س2021ǯ١ˡ
 Flow, Turbulence and Combustion (Springer), Editor
 12th International Symposium on Turbulence and Shear Flow Phenomena (TSFP12), Secretary General
 JSTʣήư͢ݤβͽ¬˸ήβʳء ΰ襢ɥХ
 ܵز LAJѰ Ѱ
 ܵز ؽѻԽ Fluids Engineering ƥޥͥ㡼
 ܵز бĴѰ ΤWG Ѱ
 ܵز ϳصѼԻǧѰ Ǯήϳʬ 纺
 ܵز ǯ OS֥ץ饺ޥ奨 ʥ
 ܵز ǯ OSֵؽ✕ؤκü ʥ
 ܵز ήι ATS 0524֥ץ饺ޥ奨
 ήϳز ǯ OSAIήϳء ʥ
 ήϳزήϳإϥɥ֥å3ǡ33ϡή纺
 ήϳز ǯ2021¹Ѱ Ѱ
 ήϳز 36ήϳإݥ ¹ѰĹ
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 1989ǯ3Ωع ´
 1994ǯ3 ƥ̻ҹز ´
 1997ǯ6ǥΩ(KTH)ر LicentiateλTeknL
 2000ǯ4ǥΩ(KTH)ر βλTeknD
 2000ǯ9 رطϸ ƥ̻ҹ칶 βλ, ()
 2000ǯ10̾Ⱦʹȵѱ Ѹ Ūͻ縦̸
 2001ǯ4ȵ縦 ͥ륮Ѹ 裱и
 2003ǯ4 رطϸ ʵ칶
 2007ǯ4 Ǥֻ ʵزʡ
 2011ǯ4 ڶ ʵزʡ
 2015ǯ4 ʵزʡ
ô (2021ǯ)
 ¸3ǯQ3, Q4ô
 ԥ塼ߥ졼αѡ3ǯQ3)
 ήϳء3ǯQ3
 ´ȸ4ǯ
 ήδäȿرաѸ
 ϳءϳ裱رա
 ϳءϳ裲رѸ
 긦ʽ1ǯ
 ̸裱ʽ2ǯ
 ĶƥˡGESLա
 絬ϴĶƥˡGESL
 ֥㡼GESLա
 ̸裲Ρ
ֵ̹ʤ
 Ƶθ (3ǯ), 2010ǯ
 Ωع ˬֵ2018ǯ6
 븩Ωع ϵֵʹ2ǯ, 2013ǯ10, 2014ǯ10
 ʣƥΥǥηϡر(GCOE)ա, 2012ǯ6
 SFCʳֺ (SFC1ǯ), 2008ǯ32009ǯ3
 Ķͥ륮ʳ裱 (ر), 2007ǯ4
ǶʸʸꥹȤGoogle Scholar Profile
K. Fukami, R. Maulik, N. Ramachandra, K. Fukagata, and K. Taira,
"Global field reconstruction from sparse sensors with Voronoi tessellationassisted deep learning,"
Nat. Mach. Intell. (to appear).
(Preprint, arXiv:2101.00554 [physics.fludyn]).
M. Morimoto, K. Fukami, K. Zhang, A. G. Nair, and K. Fukagata,
"Convolutional neural networks for fluid flow analysis: toward effective metamodeling and lowdimensionalization,"
Theor. Comput. Fluid Dyn. (to appear).
(Preprint, arXiv:2101.02535 [physics.fludyn]).
 Sample code: Available on GitHub
M. Badri Ghomizad, H. Kor, and K. Fukagata,
"A structured adaptive mesh refinement strategy with a sharp interface directforcing immersed boundary method for moving boundary problems,"
J. Fluid Sci. Technol. 16, JFST0014 (2021).
M. Badri Ghomizad, H. Kor, and K. Fukagata,
"A sharp interface directforcing immersed boundary method using the moving least square approximation,"
J. Fluid Sci. Technol. 16, JFST0013 (2021).
M. Ohashi, K. Fukagata, and N. Tokugawa,
"Adjointbased sensitivity analysis for airfoil flow control aiming at lifttodrag ratio improvement,"
AIAA J. (2021). https://doi.org/10.2514/1.J060415
T. Nakamura, K. Fukami, K. Hasegawa, Y. Nabae, and K. Fukagata,
"Convolutional neural network and long shortterm memory based reduced order surrogate for minimal turbulent channel flow,"
Phys. Fluids 33, 025116 (2021).
K. Fukami, K. Fukagata, and K. Taira,
"Machinelearningbased spatiotemporal super resolution reconstruction of turbulent flows,"
J. Fluid Mech. 909, A9 (2021).
K. Hasegawa, K. Fukami, T. Murata, and K. Fukagata,
"CNNLSTM based reduced order modeling of twodimensional unsteady flows around a circular cylinder at different Reynolds numbers,"
Fluid Dyn. Res. 52, 065501 (2020).
R. Maulik, K. Fukami, N. Ramachandra, K. Fukagata, and K. Taira,
"Probabilistic neural networks for fluid flow surrogate modeling and data recovery,"
Phys. Rev. Fluids 5, 104401 (2020).
 K. Fukami, T. Nakamura, and K. Fukagata,
"Convolutional neural network based hierarchical autoencoder for nonlinear mode decomposition of fluid field data,"
Phys. Fluids 32, 095110 (2020).
S. Hirokawa, M. Ohashi, K. Eto, K. Fukagata, and N. Tokugawa,
"Turbulent friction drag reduction on ClarkY airfoil by passive uniform blowing,"
AIAA J. 58, 41784180 (2020).
R. Uekusa, A. Kawagoe, Y. Nabae, and K. Fukagata,
"Resolvent analysis of turbulent channel flow with manipulated mean velocity profile,"
J. Fluid Sci. Technol. 15, JFST0014 (2020).
K. Hasegawa, K. Fukami, T. Murata, and K. Fukagata,
"Machinelearningbased reducedorder modeling for unsteady flows around bluff bodies of various shapes,"
Theor. Comput. Fluid Dyn. 34, 367383 (2020).
K. Fukami, K. Fukagata, and K. Taira,
"Assessment of supervised machine learning methods for fluid flows,"
Theor. Comput. Fluid Dyn. 34, 497–519 (2020).
S. Hirokawa, K. Eto, K. Fukagata, and N. Tokugawa,
"Experimental investigation on friction drag reduction on an airfoil by passive blowing,"
J. Fluid Sci. Technol. 15, JFST0011 (2020).
M. Ohashi, Y. Morita, S. Hirokawa, K. Fukagata, and N. Tokugawa,
"Parametric study toward optimization of blowing and suction locations for improving lifttodrag ratio on a ClarkY airfoil,"
J. Fluid Sci. Technol. 15, JFST0008 (2020).
Y. Nabae, K. Kawai, and K. Fukagata,
"Prediction of drag reduction effect by streamwise traveling wavelike wall deformation in turbulent channel flow at practically high Reynolds numbers,"
Int. J. Heat Fluid Flow 82, 108550 (2020).
T. Murata, K. Fukami, and K. Fukagata,
"Nonlinear mode decomposition with convolutional neural networks for fluid dynamics,"
J. Fluid Mech. 882, A13 (2020).
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 ϡ2238522 ͻԹ̶3141 ز
 Email: fukagata mech.keio.ac.jp
