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Portrait of Prashanth Nadukandi

ResearcherID
C-3012-2013
ORCID
0000-0002-4031-8457
Scopus Author ID
24485217300
Google Scholar
XiKya3AAAAAJ
CIMNE
2028

Contact:
2.146, Alan Turing Building
School of Mathematics
The University of Manchester
Oxford Rd, Manchester, M13 9PL, UK
ph: +44 161 306 3640
prashanth[DOT]nadukandi[AT]manchester[DOT]ac[DOT]uk

NEWS: I presented my research at the STEM for BRITAIN poster competition on 12-Mar-2018 in the House of Commons (UK Parliament).

I am a Marie Skłodowska-Curie Fellow at the School of Mathematics, University of Manchester, UK. My stay at UoM is funded by a MSCA Individual Fellowship to implement the FastFlowSim project and Professor Nicholas J. Higham is my host.

Before moving to Manchester, I was an Assistant Research Professor at CIMNE Barcelona, Spain. I graduated with a B.Tech. degree in civil engineering from IIT Guwahati, India and a Ph.D. degree in computational mechanics from UPC (BarcelonaTech), Spain. I am a native of Kerala state in southern India.

My latest research output is on the backward error theory and computation of the wave-kernel matrix functions. I presented an early version of this work at the 27th Biennial Numerical Analysis Conference held in Glasgow.

The solution to systems of second-order ordinary differential equations can be written succinctly using the wave-kernel matrix functions. These matrix functions provide a starting point from which to develop trigonometric time integrators for stiff second-order systems, to compute waves on graphs, and to analyze and control asymmetric systems prone to non-decaying vibrations.

My current project (FastFlowSim) is focused on particle-based exponential integrators for the simulation of low viscosity incompressible flows and its efficient implementation in software. My approach is distinct from peers/colleagues in the sense that I employ analytical solutions to compute the trajectories of the particles driven by velocity and acceleration fields approximated by piecewise linear interpolants. The analytical solutions are expressed in terms of matrix functions—the numerically stable and efficient computation of which is a specific goal.

In the past I have proposed, among other works, novel Petrov–Galerkin FEM for the numerical simulation of the convection–diffusion–reaction equation and the Helmholtz equation.

The following poem, which I learnt at school, has motivated the approach taken in my activities till date:

Climb every mountain, ford every stream,
Follow every rainbow, till you find your dream.
A dream that will take all the love that you can give,
All the days of your life as long as you live.

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