Jun 2023 – Apr 2025 · 1 yr 10 mos · Portland, Oregon Metropolitan Area · On-site

• Developing Full-stack applications for Factory Productivity monitoring. Working with the Angular & React.js UI frameworks, Django APIs, and PostgreSQL & Microsoft SQL databases. Additionally working with Requirements Gathering, Project Planning, and CI/CD pipelines for Containerized Deployments.

May 2022 – Aug 2022 · 3 mos · Menlo Park, California, United States

• Created a Page categorization system that was deployed to segment 60% of the unlabeled Pages for recommendation systems.
• Identified label candidates using NLP Techniques and graph algorithms on Presto SQL Engine using 4TB of Facebook Page data. Implemented Cross-Lingual Language models to perform categorization with feature engineering and hyperparameter optimization.

Jan 2021 – Jul 2021 · 6 mos · Chennai, Tamil Nadu, India

• Engineered a Vendor Terms Mismatch Detection and Clustering tool to identify anomalies in vendor terms and cluster vendors.
• Developed a tool to automatically generate textual contracts for vendors from programmatically stored data in AWS S3.

Jun 2020 – Jan 2021 · 7 mos

• Guided by Professor Debdoot Sheet in the domain of Deep Learning for Radiological Image analysis.
• Researched Adversarial Learning with ConvNets to segment out and quantify infection in lobes and lungs from CT scans of COVID patients with a model learning from multiple partially annotated datasets with an accuracy of 95.5%. Published a dataset where lobe wise annotations were generated by the model for COVID 19 infections and then verified by a physician.

May 2019 – Jul 2019 · 2 mos · Chennai, Tamil Nadu, India

• Designed and developed a Rule Action Framework Tool and created a unified interface that could automate reporting tasks.
• Deployed for internal users to get daily reports and logs from tasks, re-run workflows, and fetch data recursively from databases.