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Ashwin Renganathan

Assistant Professor


  • Aerospace Engineering
  • Center for Acoustics and Vibration
  • Institute for Computational and Data Sciences



  • B.S., Chemical Engineering (with course work in Aerospace Eng.), Anna University, 2008
  • M.S., Aerospace Engineering, Georgia Institute of Technology, 2010
  • Ph.D., Aerospace Engineering, Georgia Institute of Technology, 2018


Journal Articles

  • Jai Ahuja, Ashwin Renganathan and Dimitri N. Mavris, 2022, "Sensitivity Analysis of the Over-Wing Nacelle Design Space", Journal of Aircraft
  • G. V. Iungo, R. Maulik, Ashwin Renganathan and S. Letizia, 2022, "Machine-learning identification of the variability of mean velocity and turbulence intensity for wakes generated by onshore wind turbines: Cluster analysis of wind LiDAR measurements", Journal of Renewable and Sustainable Energy, 14, (023307)
  • Ashwin Renganathan, Romit Maulik, Stefano Letizia and Giacomo Valerio Iungo, 2022, "Data-driven wind turbine wake modeling via probabilistic machine learning", Neural Computing and Applications, 34, pp. 6171, 6186
  • Ashwin Renganathan, Vishwas Rao and Ionel M. Navon, 2022, "CAMERA: A Method for Cost-aware Adaptive Multifidelity Efficient Reliability Analysis", Journal of Computational Physics
  • Ashwin Renganathan, 2021, "From probabilistic machine learning to “look ahead” decision-making in the design of complex engineered systems", Aerospace America
  • Ashwin Renganathan, Romit Maulik and Jai Ahuja, 2021, "Enhanced data efficiency using deep neural networks and Gaussian processes for aerodynamic design optimization", Aerospace Science and Technology
  • Dushhyanth Rajaram, Tejas G. Puranik and Ashwin Renganathan, 2020, "Empirical Assessment of Deep Gaussian Process Surrogate Models for Engineering Problems", AIAA Journal of Aircraft
  • Ashwin Renganathan, Kohei Harada and Dimitri N. Mavris, 2020, "Aerodynamic Data Fusion Toward the Digital Twin Paradigm", AIAA Journal, 58, (9), pp. 3902-3918
  • Ashwin Renganathan, Romit Maulik and Vishwas Rao, 2020, "Machine learning for nonintrusive model order reduction of the parametric inviscid transonic flow past an airfoil", Physics of Fluids, 32, (4)
  • Ashwin Renganathan, 2020, "Koopman-Based Approach to Nonintrusive Reduced Order Modeling: Application to Aerodynamic Shape Optimization and Uncertainty Propagation", AIAA Journal, 58, (5), pp. 2221-2235
  • Ashwin Renganathan, Yingjie Liu and Dimitri N. Mavris, 2018, "A Koopman-Based Approach to Nonintrusive Projection-Based Reduced-Order Modeling with Black-Box High-Fidelity Models", AIAA Journal
  • Ashwin Renganathan and Mishra P. Debi, 2014, "Numerical study of flame/vortex interactions in 2-D Trapped Vortex Combustor", Thermal Science, 18, (4), pp. 1373-1387
  • Ashwin Renganathan and Mishra P. Debi, 2010, "Numerical analysis of fuel—air mixing in a two-dimensional trapped vortex combustor", Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 224, (1)

Conference Proceedings

  • Ashwin Renganathan, Vishwas Rao and Ionel Navon, 2022, "Multifidelity Gaussian processes for failure boundary and probability estimation", Uncertainty Quantification and Analysis of Complex Aerospace Systems
  • Varuni Katti Sastry, Romit Maulik, Vishwas Rao and Ashwin Renganathan, 2021, "Data-Driven Deep Learning Emulators for Geophysical Forecasting", Springer, Cham, pp. 433-446
  • Romit Maulik, Vishwas Rao, Ashwin Renganathan, Stefano Letizia and Giacomo Iungo, 2021, "Cluster analysis of wind turbine wakes measured through a scanning Doppler wind LiDAR", AIAA SciTech 2021 Forum
  • G. V. Iungo, S. Letizia, R. Maulik and Ashwin Renganathan, 2021, "Double-Gaussian model for predictions of the streamwise mean velocity and turbulence intensity in wind-turbine wakes", Bulletin of the American Physical Society
  • Dushhyanth Rajaram, Tejas G. Puranik, Ashwin Renganathan, Woong Je Sung, Olivia J. Pinon-Fischer, Dimitri N. Mavris and Arun Ramamurthy, 2020, "Deep Gaussian Process Enabled Surrogate Models for Aerodynamic Flows", AIAA SciTech 2020 Forum, pp. 1640
  • Ashwin Renganathan, Kohei Harada and Dimitri N. Mavris, 2019, "Multifidelity Data Fusion via Bayesian Inference", AIAA Aviation 2019 Forum, pp. 3556
  • Jai Ahuja, Ashwin Renganathan, Steven Berguin and Dimitri N. Mavris, 2018, "Multidisciplinary Analysis of Aerodynamics-Propulsion Coupling for the OWN Concept"
  • Ashwin Renganathan, Steven H. Berguin, Mengzhen Chen, Jai Ahuja, Jimmy C. Tai, Dimitri N. Mavris and David Hills, 2018, "Sensitivity Analysis of Aero-Propulsive Coupling for Over-Wing-Nacelle Concepts", 2018 AIAA Aerospace Sciences Meeting, AIAA SciTech Forum
  • Ashwin Renganathan and Dimitri N. Mavris, 2017, "A Methodology for Projection-Based Model Reduction with Black-Box High-Fidelity Models"
  • Ashwin Renganathan and Dimitri N. Mavris, 2015, "Conceptual Design of a Two Stage Runway based Space Launch System"
  • Ashwin Renganathan, Russell K. Denney, Antoine Duquerrois and Dimitri N. Mavris, 2014, "Validation and Assesment of Lower Order Aerodynamics Based Design of Ram Air Turbines"


  • Ashwin Renganathan, Jeffrey Larson and Stefan Wild, 2020, "Recursive Two-Step Lookahead Expected Payoff for Time-Dependent Bayesian Optimization"
  • Steven H. Berguin and Ashwin Renganathan, 2018, "CFD Study of an Over-Wing Nacelle Configuration"

Research Projects

Honors and Awards


Service to Penn State:

Service to External Organizations: