- Currently working on building a Machine Learning system to better predict wages for workers in a niche domain. I am responsible for the entire Machine Learning Development Life Cycle of the project.- Designed and built a distributed computing backend utilising Python FastAPI, PostgreSQL DB and Slurm for an end-to-end solution for the underlying AAV pipeline.- Developed and deployed a crucial AAV truncation analysis. Analysis tools and visualisations built using Python and shell scripts were created, and active participation in the initial research phase was undertaken, leading to significant advancements in the project. This reduced the analysis speed for bioinformaticians by 95%.

- Developed and deployed an R shiny app that visualizes the output of a GWAS pipeline- Developed an RNA Seq genomics pipeline using WDL. Also developed a CRUD app that used ReactJS for front-end and Fast-API for REST API implementation. The web app also consisted of a run monitoring system that informs the user if the run is completed or not over mail. The new pipeline cut the run time by over 90% due to the use of a SLURM back-end for workload management - Developed the database model and back-end data processing scripts for a web application that visualizes poisonous exons in RNA transcripts

- Developed RNA sequencing data processing pipeline on DNA Nexus platform. The data processing workflow was built using Python and WDL.- Developed a deep learning model based on Mask R-CNN application that could track the growth of microbes in a petridish

Developed an application using Tesseract OCR to perform text recognition on sensitive financial data. The text extractor was based on a custom Domain Specific Language(DSL) and templates. It achieved 90%+ recognition on 600 images with varying templates.