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Papers from the 4th International Conference on Data-Driven Plasma Science

Data science, including machine learning (ML) and artificial intelligence (AI), applied to plasma research has gained much interest recently, due to the remarkable advances in this field. Emerging data-driven methods and new learning techniques lead to scientific discoveries, augmented instrumentation, accelerated model development and simulations, as well as new control methods in a large spectrum of plasma research. The scope of the ICDDPS, which was launched in 2018, covers a wide range of science and technologies related to data including, but not limited to, databases, real-time control, ML, and AI applied to plasma research.

Guest Editors: Sadruddin Benkadda and Satoshi Hamaguchi

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W. A Hornsby; A. Gray; J. Buchanan; B. S. Patel; D. Kennedy; F. J. Casson; C. M. Roach; M. B. Lykkegaard; H. Nguyen; N. Papadimas; B. Fourcin; J. Hart
Yao-Li Liu; Yen-Chen Chen; Chun-Sung Jao; Mao-Syun Wong; Chun-Han Huang; Han-Wei Chen; Shogo Isayama; Yasuhiro Kuramitsu
A. Bormanis; C. A. Leon; A. Scheinker
E. Fransson; A. Gillgren; A. Ho; J. Borsander; O. Lindberg; W. Rieck; M. Åqvist; P. Strand
Shokirbek Shermukhamedov; Michael Probst
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