Masters Thesis - Neural Operators
Numerical analysis of the theoretical neural operator architecture for learning PDEs, implemented using PyTorch.
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Hi, welcome to my personal website!
Below, you can find a collection of projects I’ve worked on during my academic and professional journey. These include my Master’s in Applied Mathematics at Imperial College London, my Bachelor's in Physics at Ben-Gurion University, and my experience in software engineering and DevOps.
Thanks for visiting!
P.S. You can view the code for this website on my GitHub.
Numerical analysis of the theoretical neural operator architecture for learning PDEs, implemented using PyTorch.
Read more about this is some titleSimulating complex function contours to create 2D fluid flow simulations using Sympy and Manim!
Read more about this is some titleConducting both numerical and mathematical analyses, I explored a model depicting a biological process with unconventional boundary conditions. Employing finite difference methods, I crafted a suitable numerical scheme and implemented it using Numpy.
Read more about this is some titleCollaborating with my advisor, we developed a mathematical model capturing the unique phenomenology of phase transition in a nickel-hydroxide electrode within a battery. I conducted in-depth analyses using Matlab and Python.
Read more about this is some titleImplemented a feed-forward deep learning network strictly in NumPy, following backpropagation straight from the math. I initiated, trained, and analyzed the network's performance, specifically its ability to recognize MNIST digits and polygon edges.
Read more about this is some titleFor the final project in a Nonlinear Dynamics module, I analyzed a chaotic system of equations based on the Willamoski-Rossler equations. Exploring numerous parameters, I selected a few and detailed their influence on the system.
Read more about this is some titleDuring my army service, I focused on real-time, continuous data processing. In this project, I configured and tested the 'Argo Workflows' workflow/pipeline programming tool on our Kubernetes cluster. I found the software valuable and documented its basic usage.
Read more about this is some titleDeveloped a generic networking security layer utilizing NGINX and the OIDC protocol for applications running on OpenShift. The objective was to provide OIDC protection without developers needing to implement it directly into their code.
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