Patrick Rodi

Dr. Patrick Rodi holds three degrees in Aerospace Engineering and earned his PhD from The University of Texas at Austin, as a NASA Graduate Student Research Fellow at NASA-Ames. Prior to joining Rice University in the fall of 2018, Dr. Rodi worked in industry for 23 years specializing in high speed aerodynamics, aerothermodynamics, and vehicle design optimization. He has authored over 50 papers on hypersonics, artificial intelligence, numerical grid generation, and optimization. Dr. Rodi an Associate Fellow of the AIAA.

Research Statement

Dr. Rodi’s research focuses on high speed vehicle design and optimization, and artificial intelligence applications.                                                                                                                                                                                  

  • Waverider Vehicles – Waveriders are an intriguing type of supersonic or hypersonic vehicle concept with a strong potential to provide high aerodynamic performance.  By properly shaping the vehicle’s underside, the windward surface generated shock wave can be captured by the leading edges.  As such, the high pressure air on the windward surface is trapped beneath the vehicle which produces high lift-to-drag ratio performance.  Dr. Rodi’s current approach represents the state-of-the-art methodology employed by a large number of research and industrial entities around the world.
  • Vehicle Optimization – Optimization techniques have been and are being employed to improve the overall performance of high speed vehicles, and for details such as leading edges and fixed control surface geometries.  These optimizations seek to reduce drag, reduce aeroheating, and/or delay boundary layer transition, along with quantifying impacts to vehicle design solutions from algorithm details, initial conditions, and convergence criterion of the optimization process.  Dr. Rodi has developed and applied a number of new optimization techniques directly leading to significant vehicle and component design improvements.
  • Neural Networks – Dr. Rodi’s interest in neural networks began in the mid 1990’s.  He has applied this technology to such diverse engineering problems as spacecraft compartment venting analysis, astronaut crew assignments, and numerical grid generation.  Additionally, Dr. Rodi has developed innovative high-accuracy models for problems requiring such a capability, and continues to develop advanced neuron and network models for engineering and financial applications.

Research Areas

High speed vehicle design and optimization, artificial intelligence applications.


B.S. in Aerospace Engineering, University of Florida (1984)

M.S. in Aerospace Engineering, The University of Texas at Austin (1986)

Ph.D. in Aerospace Engineering, The University of Texas at Austin (1992)

Teaching Areas

Gas Dynamics

High Speed Aerodynamics and Aerothermodynamics

Aerospace Propulsion

Orbital Mechanics


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