Spearhead development of online platform for genomics reports visualization. Platform features a PDF File viewer, targeted statistics generator, user management dashboard, and API endpoints, all developed using Ruby on Rails. Conduct data analysis using bioinformatics tools and software for genomic and proteomic studies. Utilise statistical software and algorithms to identify patterns and correlations in complex biological data sets. • Initiated and developed Bioinformatic Pipelines using Bash for reading, trimming, aligning, and variant calling in exomes and complete genomes, utilising tools like GATK4, BWA, FastQC, Samtools, and MultiQC. • Programmed Python scripts for efficient pre-processing in ChromGo analysis (Yikon), focusing on reading, trimming, and aligning 50 basepair sequences in FastQC files. • Added new functionalities to the Laboratory Information System, integrating workflows for novel genomic tests and generating reports for Whole Exome Sequencing. • Key tasks included interfacing with the Emedgene Platform from Illumina and implementing multilingual translation capabilities through the Google Translator API, complemented by specialized health databases for accurate health term translations. • Implemented automation deployment strategies for two distinct sites; utilized Capistrano for deploying one website to a Linux web server and crafted a specialized Procfile for seamless deployment of the other to Heroku.

Conducted thorough testing of software to ensure quality and functionality. Engaged in code reviews with peers to ensure adherence to best practices and improve code quality. Worked closely with other developers, UX/UI designers, and project managers to ensure cohesive and coordinated project progress. Explored new technologies, programming languages, and tools to enhance development processes and application performance. Maintained comprehensive documentation for software for future reference and to assist in software maintenance and upgrades. • Led development of an EKG Signal Analyzer Tool, integrating socket communication with company's software and implementing multi-threading techniques. | Key technology used: Python. • Utilised scikit-learn to create neural network specializing in beat morphological classification. • Coordinated creation of online management system for EKG studies including development of API-RESTful Service, PDF File viewer and generator, and implementation of ion-auth for robust user management. Technologies employed included AngularJS, CodeIgniter (PHP), and MySQL.

Worked in the development of a ML algorithm for classifying brain tumors from CT (Computed Tomography) scan images. There I used radiomics, which are some specific characteristics that can be found in this kind of images, and based on those statistics, the ML algorithm can infer if the tumor is benign or not. I made the data pre-processing, ML algorithm development, and first training stage.