Overview
This project was developed as part of Rutgers University’s Interdisciplinary Research Team (IRT) program — a competitive, funded initiative supporting applied research projects. Our team contributed to the Personalized Aide for Student Learning (PAL) effort by building backend infrastructure to automate exam processing workflows.
What I Built
I designed and implemented a Python/Django backend that:
• Integrated Gradescope and Akindi exam data.
• Automated exam data ingestion and reconciliation workflows.
• Reduced manual spreadsheet processing and grading overhead.
• Improved reliability and reproducibility across semesters.
Impact
The system saved over 200+ hours per semester for instructional staff by automating repetitive grading and data integration tasks. It transformed a manual, error-prone workflow into a scalable backend system.
Engineering Growth
This project strengthened my experience in backend architecture, third-party API integration, and building production-ready systems with measurable real-world impact.