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Senior Research Scientist
Makoto received a Ph.D. in Astrophysics from Kyoto University in 2012. He completed his postdoctoral research in high-energy plasma physics at the Max Planck Institute for Nuclear Physics and the University of Tokyo. He began working on machine learning at NEC Biometrics Research Laboratories in 2018. In 2021, he joined NEC Laboratories Europe to focus on AI-driven scientific research. In November 2018, he received an Outstanding Achievement Award, issued by the High Performance Computing Infrastructure (HPCI) in Japan.
Group Involvement, NEC Laboratories Europe
Intelligent Software Systems
Research Interests
- AI for Science
- Image Recognition
- Physics
Publications
- “Learning Neural PDE Solvers with Parameter-Guided Channel Attention”, ICML2023 · Jul 26, 2023
- “PDEBench: An Extensive Benchmark for Scientific Machine Learning”, NeurIPS2022 Track Datasets and Benchmarks · Sep 16, 2022
- “An Empirical Study of the Effects of Sample-Mixing Methods for Efficient Training of Generative Adversarial Networks”, IEEE 4th International Conference on Multimedia Information Processing and Retrieval · Jan 1, 2021
- “An Efficient Method of Training Small Models for Regression Problems with Knowledge Distillation”, IEEE 3rd International Conference on Multimedia Information Processing and Retrieval (MIPR2020) · Aug 1, 2020
- “Magnetic Field Saturation of the Ion Weibel Instability in Interpenetrating Relativistic Plasmas”, The Astrophysical Journal Letters · Jun 1, 2018
- “Turbulent Reconnection in Relativistic Plasmas and Effects of Compressibility”, The Astrophysical Journal · Dec 1, 2015
- “A new scheme of causal viscous hydrodynamics for relativistic heavy-ion collisions: A Riemann solver for quark-gluon plasma”, Journal of Computational Physics, · Jan 1, 2014
- “Evolution of Relativistic Plasmoid Chains in a Poynting-dominated Plasma”, The Astrophysical Journal · Sep 1, 2013
- “A fast numerical scheme for causal relativistic hydrodynamics with dissipation”, Journal of Computational Physics · Aug 1, 2011
- “A New Numerical Scheme for Resistive Relativistic Magnetohydrodynamics Using Method of Characteristics”, The Astrophysical Journal · Jul 1, 2011