Pranay Seshadri

About me.

I live in London and work at the University of Cambridge and The Alan Turing Institute. I studied computational engineering at Cambridge and aerospace engineering previously at Maryland. During my doctorate I worked at Rolls-Royce plc in Derby and spent time at Stanford. My research focuses on uncertainty quantification, optimisation and machine learning applied to address challenges in aeronautics. I am the founder of Effective Quadratures and the organizer for the Cambridge Linear Algebra Seminar Series (CLASS).

My current research projects are:

• Bayesian models for improved aerothermal flow-physics in engines
• Subspace-based dimension reduction: algorithms and 3D blade design
• Machine learning with polynomials: from quadratures to neural networks
• Leveraging virtual reality for digital twins in aeronautics

For all my publications, please check out Google Scholar and Researchgate. For open-source codes, visit my Github profile. If you are really interested in my research, check out this high-level research talk. For my CV, click here.

Team.

Chun Yui Wong (PhD student): Embedded ridge approximations for improved computational aerodynamic inference.
James Gross (PhD student): Techniques in polynomial subspace projections for design optimisation.
Joe Zhou (Undergraduate student): High-dimensional quadrature rules.

Latest preprints.

• Embedded ridge approximations
• Gaussian ridge functions
• Higher order sensitivities via polynomial least squares
• Frequentist strategies for aero-engine spatial field approximation: I & II
• Multipoint fan design with dimension reduction
• AeroVR: An immersive visualization system for aerospace design and digital twinning in virtual reality

Upcoming conference presentations.

• AIAA SciTech 2020: Optimisation with intrinsic dimension reduction: A ridge informed trust-region method.
• IEEE Aerospace 2020: Digital twin assessments in virtual reality: An exploration study with aeroengines.

Upcoming invited talks.

• Effective and efficient Gaussian processes
• NAFEMS European Conference: Simulation-Based Optimisation

Contact.

IN2-17 Inglis Building,
Department of Engineering,
University of Cambridge.
p.seshadri @ eng.cam.ac.uk