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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:




The Penn State Department of Aerospace Engineering, established in 1961 and the only aerospace engineering department in Pennsylvania, is consistently recognized as one of the top aerospace engineering departments in the nation, and is also an international leader in aerospace education, research, and engagement. Our undergraduate program is ranked 15th and our graduate programs are ranked 15th nationally by U.S. News & World Report, while one in 25 holders of a B.S. degree in aerospace engineering in the U.S. earned it from Penn State. Our students are consistently among the most highly recruited by industry, government, and graduate schools nationwide.

The department is built upon the fundamentals of academic integrity, innovation in research, and commitment to the advancement of industry. Through an innovative curriculum and world-class instruction that reflects current industry practice and embraces future trends, Penn State Aerospace Engineering graduates emerge as broadly educated, technically sound aerospace engineers who will become future leaders in a critical industry

Department of Aerospace Engineering

229 Hammond Building

The Pennsylvania State University

University Park, PA 16802

Phone: 814-865-2569