Projects – Machine Learning and Me

SynthEye

Recently, I submitted my thesis project, which was a culmination of my Master’s course in Machine Learning at UCL. This is my second major project combining AI with medical imaging, and I had a great experience collaborating with my supervisor, Dr. Nikolas Pontikos, and everyone at Pontikos Lab. Specifically, my project focused on Generative AdversarialContinue reading “SynthEye”

Bayesian inference, MCMC and comparing COVID vaccines

A couple of months back, I found this fantastic Medium article by Susan Li, which implemented a Bayesian model for estimating the effects of COVID-19 vaccines. As I had studied these topics as part of my course on Graphical models, I thought it would be interesting to re-implement this myself from scratch and break downContinue reading “Bayesian inference, MCMC and comparing COVID vaccines”

Predicting the sub-cellular location of a protein using machine learning

I’m sure most of us will know that proteins play a huge role in the human body. They are responsible for the metabolic reactions in our cells, carry molecules from one part of the body to another, mediate cellular repair, and form a part of our immune system. But to figure out what a protein’sContinue reading “Predicting the sub-cellular location of a protein using machine learning”

Modelling the Relationship Between Structural and Functional Connectomes

As part of my biomedical imaging module, I participated in a group project focused on studying the connectome using graph theory and parametric models. In this post, I’ll briefly overview connectomics, how connectomes are constructed, our team’s experiments, and my big takeaways from the project. What is connectomics? If you’ve read a lot about biologicalContinue reading “Modelling the Relationship Between Structural and Functional Connectomes”

Computational models for Diffusion MRI

During my “Computational Modelling for Biomedical Imaging” course, I had the opportunity to pursue a mini-project on modeling the diffusion patterns in the brain from diffusion MRI studies. This post will give a brief overview of diffusion MRI, the models I implemented, the results, and my biggest takeaways. Introduction to diffusion MRI Magnetic Resonance ImagingContinue reading “Computational models for Diffusion MRI”

Automating Cardiac MR image planning using Deep Learning

Just last year, I had completed my undergraduate journey at UCL with a First Class Honors BSc in Applied Medical Sciences. As part of my degree, I got the opportunity to pursue a 9-month-long research project culminating in a dissertation. My project focused on using deep learning to automate the Cardiac MR image planning protocol.Continue reading “Automating Cardiac MR image planning using Deep Learning”