Star Bars

Context

StarBars was created to solve a common group-planning problem: choosing a good place to meet when everyone starts from different locations. The goal was to make this decision faster and fairer by computing a practical midpoint and surfacing options nearby.

What I built

I helped build an open-source mobile application where users can:

• Add group locations
• Compute a shared central area
• Discover nearby bars in that radius
• Review place details before deciding where to meet

The product focused on turning a frequent social friction point into a quick, map-assisted flow.

Technical approach

The solution combined an Android mobile app (Java) with a Python backend API stack. We integrated geospatial and place-search services to calculate midpoint-based suggestions and return candidate venues. The project was organized as open source with dedicated repositories for backend, frontend, and landing page, using Git-based collaboration throughout the build process.

Outcome

StarBars delivered a working end-to-end prototype during HackUPC 2022, validating the core product idea and proving we could ship a usable geolocation-heavy experience under tight timelines. It also strengthened our ability to coordinate across distributed teamwork and unfamiliar APIs while keeping the user experience simple.