Photo of Ashwin Renganathan

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

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
 


 

About

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

308 Engineering Collaborative Research and Education (ECoRE) Building

556 White Course Drive

The Pennsylvania State University

University Park, PA 16802

Phone: 814-865-2569