PPPL

Chuanfei Dong
董川飞

Dr. Chuanfei Dong, 董川飞, is an Associate Research Astrophysicist at the Department of Astrophysical Sciences, Princeton University and a long-term Visiting Research Physicist in the Theory Department of the Princeton Plasma Physics Laboratory (PPPL). He received his B. Sci. from the University of Science and Technology of China (2009) in Geophysics and Theoretical Physics. He received his M. Sci. from Georgia Tech (2010) in Earth and Atmospheric Sciences. He received his M. Sci. and Ph. D. from the University of Michigan, Ann Arbor in Space and Planetary Sciences (2012, 2015), M.S.E. in Nuclear Engineering and Radiological Sciences (2014), and Ph. D. in scientific computing (2015).

During his graduate study, he was awarded Vela Fellowship from Los Alamos National Laboratory (2013), the MIPSE Fellowship from Michigan Institute for Plasma Science and Engineering (2014), NASA Earth and Space Science Fellowship from NASA (2013 - 2015), Richard and Eleanor Towner Award for Distinguished Academic Achievement from College of Engineering at the University of Michigan (2015), Award for Outstanding Students Abroad from China Scholarship Council (2015), NASA Living With a Star Jack Eddy Postdoctoral Fellowship from UCAR/NASA (2015), MICDE Fellowship from Michigan Institute for Computational Discovery and Engineering (2015), RHG Exceptional Achievement for Science to the MAVEN Science Team from NASA (2016), and Group Achievement Award to MAVEN Science Team from NASA (2016).

His research interests include: star-planet interactions, (exo-) planetary habitability and astrobiology, solar wind interaction with planets/moons (e.g., Mars, Venus, Mercury and Ganymede), ion/electron heating by Alfvén/whistler waves via non/sub-resonant interaction, high intensity laser-plasma interaction, electrons and coherent radiation (in traveling wave tube, klystron, gyrotron, magnetron), magnetic reconnection and turbulence, information feedback in intelligent transportation systems (ITSs); application of the evolutionary game theory to traffic networks.

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