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所属機関・部署：
職名： Assistant Professor
論文 (57件)：
MISC (2件)：
講演・口頭発表等 (16件)：
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Kyoto University Chemical En
Kyoto University Chemical En について
職名： Assistant Professor
論文 (57件)：
- Simon K. Schnyder, John J. Molina, Ryoichi Yamamoto, Matthew S. Turner. Understanding Nash epidemics. Proceedings of the National Academy of Sciences. 2025. 122. 9
- Krongtum Sankaewtong, John J. Molina, Ryoichi Yamamoto. Autonomous navigation of smart microswimmers in non-uniform flow fields. Physics of Fluids. 2024. 36. 4
- Adnan Hamid, Muhammad Shakaib, John J. Molina, M. Danyal Qasim, Bilal Fareed, Muhammad Uzair, Ryoichi Yamamoto. Direct numerical simulations of suspension of disk-shaped particles. Physics of Fluids. 2024. 36. 4
- John J. Jairo Molina, Kenta Ogawa, Takashi Taniguchi. Stokesian Processes : Inferring Stokes Flows using Physics-Informed Gaussian Processes. Machine Learning: Science and Technology. 2023
- Simon K Schnyder, John J Molina, Ryoichi Yamamoto, Matthew S Turner. Rational social distancing policy during epidemics with limited healthcare capacity. PLoS computational biology. 2023. 19. 10. e1011533
- Jean-Francois Dufreche, Bertrand Siboulet, Magali Duvail, Pierre Turq, John Molina, Biman Bagchi. Viscosity of aqueous electrolyte solutions: The dynamic point of view for hydrophobicity and hydrophilicity. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY. 2014. 248
- Yamamoto, Ryoichi, Molina, John J, Tatsumi, Rei. Simulating colloids and self-propelled particles with fully resolved hydrodynamics using the smoothed profile method (SPM). Hybrid Particle-Continuum Methods in Computational Materials Physics,46, pp. 11-24. 2013
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Learning the constitutive relation of polymeric flows with Memory
(American Physical Society (APS) March Meeting 2021) -
Novel Soft Matter Physics through Computational and Information Science
(The Physical Society of Japan 2021 Annual Meeting 2021) -
Learning the Constitutive Relation of Polymer Flows with Memory: from Micro-Scale Dynamics to Macro-Scale Flow
(SIAM Conference on Computational Science and Engineering (CSE21) 2021) -
ポリマー加工フローの機械学習
(京大テックフォーラム ソフトマター理工学の流れ問題 ~シミュレーションの視点から~ 2021) -
Learning the Constitutive Relation of Non-Newtonian Fluids from Microscopic Dynamics
(18th International Congress on Rheology 2020)
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