- +44 1223 748571
PhD Research Student
- M.S., Aerospace Engineering, University of Maryland (2009-2011)
- B.S., Aerospace Engineering, University of Maryland (2005-2009)
Pranay Seshadri is a PhD student in the Computational Design Group under Geoffrey Parks. His work focuses on developing algorithms for uncertainty quantification and optimization and applying them to complex turbomachinery design problems. His interests range from algorithm development, CFD to compressor and turbine aerodynamics.
Pranay is a visiting PhD student at Stanford University in the Center for Turbulence Research, under Gianluca Iaccarino and Paul Constantine. He has also spent considerable time working in Derby with Rolls-Royce plc, within the CFD Methods Group, under Shahrokh Shahpar. His project is funded by EPSRC (UK) and Rolls-Royce plc.
Seshadri, P., Parks, G.T., Shahpar, S., Leakage Uncertainties for Compressors: The Case of Rotor 37, Revision Submitted. AIAA Journal of Propulsion and Power, 2014.
Seshadri, P., Shahpar, S., Parks, G.T., Robust Design of Compressors for De-sensitizing Operational Tip Clearance Variations, ASME Turbo Expo 2014.
Seshadri, P., Constantine, P., Iaccarino, G., Aggressive Design Under Uncertainty, AIAA SciTech 2014, January 13-17, National Harbor, Maryland, 2014
Lattarulo, V., Seshadri, P., Parks, G.T., Optimization of a Supersonic Airfoil Using the Multi-Objective Alliance Algorithm, GECCO '13: Genetic and Evolutionary Computation Conference, July 6 - 10, Amsterdam, Netherlands, 2013
Seshadri, P., Parks, G.T., Jarrett, J.P., Shahpar, S., Towards Robust Design of Axial Compressors with Uncertainty Quantification, AIAA Sturctural Dynamics and Materials Conference, April 8-11, Boston, MA, 2013
Seshadri, P., Constantine, P.G., Gonnet, P., Parks, G.T., Shahpar, S., Stable Multivariate Rational Interpolation for Parameter-dependent Aerospace Systems, AIAA Sturctural Dynamics and Materials Conference, April 8-11, Boston, MA, 2013
The University of Cambridge,
Department of Engineering,
Phone: +44 1223 748571
Fax: +44 1223 332662