
Jason Rabinovitch
استادیار · Computational Fluid Dynamics
Stevens Institute of Technologyمعرفی
Dr. Jason Rabinovitch is an Assistant Professor in the Department of Mechanical Engineering at Stevens Institute of Technology. He directs the Rabinovitch Research Group, which integrates computational fluid dynamics with space exploration challenges. His research focuses on spacecraft plume-surface interactions, supersonic parachute inflation modeling, high-speed multiphase flows, and geophysical phenomena on celestial bodies like Enceladus and Mars.
Research interests span computational methods for space systems, including: hypersonic fluid dynamics, multiphase flow physics, hybrid rocket propulsion, planetary entry-descent-landing technologies, and cryovolcanic processes. Current projects investigate shock-droplet interactions, Mars parachute permeability, and Enceladus plume dynamics through NASA and ONR-funded initiatives.
Recent publications demonstrate strong focus on experimental and computational validation of aerospace systems, with 15 peer-reviewed articles since 2020 covering parachute FSI modeling, Mars landing erosion analysis, rocket combustion studies, and extraterrestrial rotorcraft effects. The research consistently bridges fundamental fluid mechanics with spacecraft engineering applications.
Honors include multiple NASA Group Achievement Awards, the Ernest E. Sechler Memorial Award in Aeronautics, and selection for the Humboldt Research Fellowship. Patent #11,578,682 covers a SmallSat hybrid propulsion system.
Supervises 3 PhD candidates (Danial Ghasimi, Nikk Lao, Andrew Sayad) and multiple undergraduate researchers through the Provost's Research Fund. Leadership includes Principal Investigator roles on ONR and NASA grants supporting hyperspeed multiphase flow research and Enceladus plume modeling collaborations with JPL/SWRI.
The Rabinovitch Research Group maintains active collaborations with Cornell University's Computational ThermoFluds Lab, Stanford University, JPL, and Johns Hopkins APL on projects involving high-fidelity simulations and experimental validation.
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