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I am a masters student and a student-researcher at the Technical University of Munich. My research falls at the intersection of applied mathematics, scientific computing and statistics.

I have an eclectic mix of experiences in systems simulation, product design, computational fluid dynamics, quantum computing, waveform inversion and quantum chemistry.

I am an active proponent of John Tukey’s – “getting to play in everyone’s backyard”. 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 Partial Differential Equations.

Rahul Manavalan's Projects

closuremodels.jl icon closuremodels.jl

A julia package for inferring closure models with different inference schemes.

deepsets.jl icon deepsets.jl

A julia implementation of simple neural network approximators on sets.

gamblets.jl icon gamblets.jl

A julia implementation of the Gamblets transform for solving partial differential equations.

hptn icon hptn

TCL library - TN (bench code)

igsm icon igsm

Integrated Global System Model

lineax icon lineax

Linear solvers in JAX and Equinox. https://docs.kidger.site/lineax

lowrankintegrators.jl icon lowrankintegrators.jl

Package for approximation of solutions to matrix differential equations or time-dependent matrices via dynamically evolving low rank decomposition.

masters-thesis icon masters-thesis

Home of Tex files, reference papers, reference implementations and such for my Masters Thesis.

mlcgmd icon mlcgmd

Simulate time-integrated coarse-grained MD with multi-scale graph neural networks

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