ResearchLens: AI Biomedical Research Assistant

Problem

Biomedical literature review is slow because useful context is spread across papers, abstracts, terminology, and experimental details. ResearchLens was built around a simple goal: make it easier to move from a research question to a useful reading path.

Approach

The app emphasizes focused search and synthesis instead of a general-purpose chatbot experience. The interface is designed to keep the research task visible: papers, summaries, and follow-up questions stay close to the user's working context.

• Structured the app around biomedical paper discovery and review workflows.
• Kept the UI dense enough for research work without burying the primary task.
• Used AI support for synthesis while preserving the need to inspect source material.

Technical Notes

ResearchLens is a TypeScript web application deployed on Vercel. The front end is organized around repeatable research actions: ask a question, review relevant material, refine the search, and capture the useful parts of the result. That structure matters because research tools need to reduce friction without hiding uncertainty.

Outcome

The result is a working research assistant that demonstrates how AI can support biomedical review tasks without turning the interface into a generic chat surface. It also gives prospective collaborators a concrete example of my work at the intersection of research software, AI-assisted tooling, and full-stack product development.