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 physics informed machine learning to address challenges in aerothermodynamics. I am the founder of Effective Quadratures.

My current research projects (and interests) are: For all my publications, please check out Google Scholar and Researchgate. For open-source codes, visit my Github profile. For my CV, click here. If you are really interested in my research, check out the videos below. The first one is a high-level research talk, while the other two are initial results of my team's ongoing virtual reality work.


Ashley Scillitoe (Postdoctoral fellow): Physics informed machine learning in computational fluid dynamics.
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.
Slawomir Konrad Tadeja (PhD student, co-advised by Per Ola Kristensson): Digital twinning an aeroengine in virtual reality.

Latest preprints.

Upcoming conference presentations.

Upcoming invited talks.

Former team members.

Joe Zhou (Undergraduate student): High-dimensional quadrature rules.
Shaowu Yuchi (Undergraduate student): Data-driven dimension reduction.


IN2-17 Inglis Building,
Department of Engineering,
University of Cambridge.
p.seshadri @ | pseshadri @