Rahul Manavalan

I am a doctoral student in mathematical statistics at Lund University. Formerly, I was student-researcher at the Technical University of Munich and constantly collaborate with people there.

I am an active proponent of John Tukey’s – “getting to play in everyone’s backyard” idea. Promptly, I am interested in all things manifold learning and its applications to Many Body Physics, Non-linear Model Order Reduction and other surrogates for large scale dynamical systems. I am particularly intrigued by the duality of optimization landscapes and evolution potentials of large scale (especially quantum) dynamical systems.

My research focuses on developing novel numerical and statistical methods for dynamical systems with applications spanning computational fluid dynamics, quantum many body physics, waveform inversion and quantum chemistry. A major component of this is examining the source and propagation of uncertainty in these models.

I am the lead developer of FastSolvers.jl; a package for accelerated PDE evaluations.

When I am not working, I like to make silly simulations of waves.