SkillSync — Amir Saad

WORK / Applications

SkillSync

A Java desktop application that connects students with compatible project partners through skill assessments and matching algorithms.

  • Java
  • JavaFX
  • SQLite
  • DSA

Academic desktop application

View source on GitHub ↗

01 / THE PROBLEM

Where it started.

Students need teammates with compatible skills, but casual introductions rarely show what someone can contribute. SkillSync explores a more structured way to discover partners for academic projects.

02 / THE APPROACH

Making the problem concrete.

  1. 01

    Model student profiles and domain scores using Java collections.

  2. 02

    Use short assessments to establish qualified domains.

  3. 03

    Compare shared domains and rank eligible peers.

  4. 04

    Track requests and accepted partnerships in local storage.

03 / THE SOLUTION

A focused workflow.

A local desktop workflow connects assessments to peer discovery. Students qualify in a domain by scoring at least seven out of ten, then review compatible peers and send an invitation.

  • Randomized domain assessments
  • Ranked peer discovery
  • Accept or decline match requests
  • Student dashboard and leaderboard

04 / TECHNICAL DECISIONS

The choices behind it.

Collections before complexity

Hash maps and lists support score lookup and roster processing; shared-domain comparisons and comparator sorting make the matching rules understandable.

Local persistence

SQLite provides local data storage for student profiles, domain assessment scores, and team-matching history, keeping the academic desktop workflow self-contained.

05 / MY CONTRIBUTION

Scope and responsibility.

Designed and implemented the domain skill assessment workflow, peer-matching ranking algorithms, and SQLite local database integration, paired with an interactive JavaFX desktop user interface.

06 / EVIDENCE & LIMITATIONS

What the evidence shows.

  • SkillSync is a JavaFX desktop application that assesses student skills, identifies compatible project partners through matching algorithms, and manages partnership requests. It uses embedded SQLite for local persistence.

No live demo is currently verified.

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