• 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

Journal Articles

Annie S Booth, Ashwin Renganathan and Robert B Gramacy, 2025, "Contour Location for Reliability in Airfoil Simulation Experiments using Deep Gaussian Processes", Annals of Applied Statistics, 19, (1)

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

Dushhyanth Rajaram, Tejas G Puranik, Ashwin Renganathan, WoongJe Sung, Olivia Pinon Fischer, Dimitri N Mavris and Arun Ramamurthy, 2022, "Empirical assessment of deep Gaussian process surrogate models for engineering problems", Journal of Aircraft, 58, (1), pp. 182--196

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

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

Ashwin Renganathan and Kade Carlson, 2025, "qPOTS: Efficient batch multiobjective Bayesian optimization via Pareto optimal Thompson sampling", International Conference on Artificial Intelligence and Statistics, 258, pp. 4051-4059

• 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).

• AI for Societal Impact award, Penn State AI Hub, April 2025

Service to Penn State:

Service to External Organizations:

• Organizing Conferences and Service on Conference Committees, Chairperson, Conference Technical Discipline Chair, AIAA SciTech 2025, 2025

• Organizing Conferences and Service on Conference Committees, Chairperson, Multidisciplinary Design Optimization Student Paper Competition Chair, AIAA, 2023