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Ashwin Renganathan

Assistant Professor

Affiliation(s):

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

 

Education

  • B.S., Chemical Engineering, Anna University, 2008
  • M.S., Aerospace Engineering, Georgia Institute of Technology, 2010
  • Ph.D., Aerospace Engineering, Georgia Institute of Technology, 2018

Publications

Journal Articles

  • Ashwin Renganathan, Vishwas Rao and Ionel M. Navon, 2023, "CAMERA: A method for cost-aware, adaptive, multifidelity, efficient reliability analysis", Journal of Computational Physics, 472, pp. 111698
  • Jai Ahuja, Ashwin Renganathan and Dimitri N. Mavris, 2022, "Sensitivity Analysis of the Over-Wing Nacelle Design Space", Journal of Aircraft, 59, (6), pp. 1--15
  • G. Valerio Iungo, Romit Maulik, Ashwin Renganathan and Stefano 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, (2)
  • 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, Romit Maulik and Jai Ahuja, 2021, "Enhanced data efficiency using deep neural networks and Gaussian processes for aerodynamic design optimization", Aerospace Science and Technology, 111
  • Dushhyanth Rajaram, Tejas G Puranik, Ashwin Renganathan, WoongJe Sung, Olivia Pinon Fischer, Dimitri N Mavris and Arun Ramamurthy, 2020, "Empirical assessment of deep Gaussian process surrogate models for engineering problems", Journal of Aircraft, 58, (1), pp. 182--196
  • 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, pp. 047110
  • 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, "Koopman-based approach to nonintrusive projection-based reduced-order modeling with black-box high-fidelity models", AIAA Journal, 56, (10), pp. 4087--4111

Conference Proceedings

  • Pramudita S Palar and Ashwin Renganathan, 2024, "Reliability-oriented Sensitivity Analysis using Shapley Additive Explanations and Polynomial Chaos Expansion", AIAA SciTech Forum 2024
  • Annie S Booth, Robert Gramacy and Ashwin Renganathan, 2024, "Actively learning deep Gaussian process models for failure contour and probability estimation", AIAA SciTech Forum 2024
  • Ashwin Renganathan, 2024, "Efficient reliability analysis with multifidelity Gaussian processes and normalizing flows", AIAA SciTech Forum 2024
  • Daning Huang, Ashwin Renganathan and Mark Miller, 2023, "Design of an Aeroelastically Scaled Model in a Compressible Air Wind Tunnel Facility Using Multifidelity Multi-Objective Bayesian Optimization", AIAA SciTech Forum 2023
  • Ashwin Renganathan, Vishwas Rao and Ionel Navon, 2022, "Multifidelity Gaussian processes for failure boundary and probability estimation", AIAA SciTech Forum 2022, AIAA, pp. 0390
  • 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 Forum 2020, pp. 1640
  • Ashwin Renganathan, Kohei Harada and Dimitri N. Mavris, 2019, "Multifidelity Data Fusion via Bayesian Inference", AIAA Aviation Forum 2019, pp. 3556
  • Jai Ahuja, Ashwin Renganathan, Steven Berguin and Dimitri N Mavris, 2018, "Multidisciplinary analysis of aerodynamics-propulsion coupling for the OWN concept", AIAA SciTech Forum 2018, pp. 2927
  • 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", AIAA SciTech Forum 2018

Magazines/Trade Publications

Other

  • Ashwin Renganathan, 2018, "A Methodology for Non-Intrusive projection-based model reduction of expensive black-box PDE-based systems and application in the many-query context"

Research Projects

  • January 2020 - January 2020, "Statistics and Machine Learning to Improve Reduced Order Models," (Sponsor: U.S. Department of Energy (DOE)-Laboratory Directed Research & Development (LDRD) program).
  • March 2019 - October 2019, "Deep Gaussian process for automated decision making," (Sponsor: Siemens Corporate Technology).

Honors and Awards

Service

Service to Penn State:

  • Committee Work, Committee Member, Graduate studies commitee, August 2023

Service to External Organizations:

  • Organizing Conferences and Service on Conference Committees, Chairperson, Non-Deterministic Approaches Conference Technical Discipline Chair, American Institute of Aeronautics and Astronautics, 2025
  • Organizing Conferences and Service on Conference Committees, Co-Organizer, Co-organizer of a conference minisymposium, Society of Industrial and Applied Mathematics, 2024
  • Organizing Conferences and Service on Conference Committees, Chairperson, Conference Technical Discipline Chair, AIAA SciTech 2025, June 2024 - January 2025
  • Organizing Conferences and Service on Conference Committees, Chairperson, Multidisciplinary Design Optimization Student Paper Competition Chair, AIAA, November 2022 - June 2023
  • Organizing Conferences and Service on Conference Committees, Co-Organizer, Co-organizer of a conference minisymposium, Society of Industrial and Applied Mathematics, 2019
  • Organizing Conferences and Service on Conference Committees, Co-Organizer, Co-organizer of a special invited session, AIAA, 2019