Topics I've gone deep on, from brain-computer interfaces to health equity and econometrics.
Brain-Computer Interfaces
I conducted a group research project under the Harvard Medical School. To summarize, we assessed different machine and deep learning methods of generating images via EEG signals, building off of StableDiffusion and DreamDiffusion and utilizing methods such as CLIP (Contrastive Language Image Pre-Training).
Epidemiology Research
I worked under a professor at Wayne State University, assessing numerous studies on historic redlining and analyzing adverse health outcomes associated with different HOLC grading levels.
Muscular Dystrophy & Machine Learning
Muscular Dystrophy and other similar genetic disorders have always been extremely interesting to me. As a result, I was wondering which machine learning methodologies are the best for diagnosis of muscular dystrophy, as this is feasible to assess using publicly available genetic datasets.
Econometrics Research
I have always been extremely interested in economics, and econometrics in particularly is a unique combination of economics and quantitative analysis. This project in particular analyzes the labor market and different types of jobs through a quantitative, statistical, econometrics-backed perspective.
