Peer Review Finder

Overview

Peer Review Finder is an intelligent application that leverages AI-powered matching algorithms to connect research papers with qualified reviewers. The platform addresses a critical challenge in academic publishing: Journal editors and conference chairs struggle to find appropriate reviewers, while researchers are overwhelmed with review invitations.

Our solution uses machine learning to analyze research interests and expertise, creating better matches between papers and potential reviewers. Editors and chairs can post abstracts needing review, while researchers can discover papers aligned with their expertise.

What I Learned

Managing multiple concurrent projects taught me valuable lessons in prioritization and time management. This experience reinforced that structured planning is essential for success in complex development projects.

Teamwork dynamics were particularly important. Initially, our task dependencies created bottlenecks. We learned to create more granular, independent tickets and use collaborative tools like project boards with detailed story tickets to improve transparency and efficiency.

This project significantly improved my collaborative workflow management skills, and I now use structured scheduling tools to manage complex workloads effectively.

My Contributions

I focused on backend development and paper display functionality. My key contributions included:

• Developed the paper upload system with validation and processing
• Implemented intelligent filtering algorithms for the view paper and my paper pages
• Created user experience improvements to prevent duplicate submissions
• Contributed to UI/UX refinement and bug resolution

One significant challenge was adapting when a team member had to step away mid-project. Through effective work redistribution and communication, we maintained project momentum and delivered on schedule.

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