• Collaborated with various departments to develop a multi-environment dashboard using Superset, SQL, and pgAdmin to track performance, memory usage, and error rates, reducing debugging time by 30%

• Developed an automated testing framework with Playwright and Cucumber to cover unit, integration, and end-to-end tests, lowering manual testing by 45% and increasing code quality

• Overhauled front-end architecture with Angular, Redux, and RxJS, cutting production bugs by 25% and boosting system responsiveness

• Managed and led a team of five co-op students to develop the company website using React, while managing timelines and tasks ultimately reducing bounce rate by 35%, and increasing user engagement by 25%

• Implemented advanced SEO tactics, keyword optimization, meta-tag refinement, and mobile-first indexing which doubled organic search traffic and elevated the site to the first page of Google results for key terms

• Implemented cross-browser testing protocols for Chrome, Firefox, and Safari, reducing UI inconsistencies by 40% and elevating user satisfaction scores

• Developed a end-to-end AI-pneumonia detector from chest X-ray images using transfer learning with MobileNetV2

• Achieved 95% accuracy on clinical data through rigorous model optimization and robust image preprocessing

• Deployed the application on Azure, leveraging GitHub integration with an automated CI/CD pipeline

• Developed a dynamic mobile application for real-time nutritional analysis by scanning item barcodes

• Designed features to analyze food items, including nutrition scores, additive identification, and ingredient analysis

• Created LockedIn, a app that fosters habit-building and accountability through a community based approach

• Built authentication system with Firebase, handling user login, role-based access control, and secure image uploads

• Led end-to-end development cycle, from UI/UX design to backend infrastructure and Firestore data modeling

• Built a WLP4 (C++ subset) compiler covering scanning, parsing, semantic analysis, and code generation

• Developed a custom loader/linker to handle execution, ensuring translation of high-level code into machine code

• Designed compiler from tokenization to machine code, using regex, DFAs, symbol tables, and semantic checks

• Developed a end-to-end AI-pneumonia detector from chest X-ray images using transfer learning with MobileNetV2

• Achieved 95% accuracy on clinical data through rigorous model optimization and robust image preprocessing

• Deployed the application on Azure, leveraging GitHub integration with an automated CI/CD pipeline