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HACKATHON RECAP 01
The AIML
Hackathon 2026
A build sprint for practical ideas: teams turned everyday student and community challenges into working AI products.
115+participants
20teams
QUT’s biggeststandalone student club hackathon to date
The AIML Hackathon gave teams a few intense days to identify a problem, build a prototype, and pitch a solution with real world potential. The result was a wide range of ideas spanning study support, career planning, accessibility, mobility, and personal productivity.
Projects paired thoughtful user problems with technical experimentation: browser tools that make university information easier to navigate, AI assisted career planning, private local first study companions, and systems designed to make reporting and decision making faster.
What stood out was not only the ambition of the projects, but the way teams turned rough concepts into tangible demonstrations under pressure.
FROM THE BUILD FLOOR
Ideas that became working prototypes.
Selected examples from the projects submitted during the hackathon.
Course2Career
A tool matching academic progress with job requirements to surface skill gaps, next semester choices, and useful learning resources.
Clarity
An AI second brain for capturing notes, finding connections between ideas, and chatting with a personal knowledge base.
FuelFlow
A refuelling planner combining fuel price data, route detours, and short term forecasting to help drivers decide when and where to fill up.
Neurovox
An eye tracking communication prototype with a gaze keyboard and language assisted reply suggestions for hands free interaction.
Roadify
An AI supported vehicle incident reporting flow that guides photo capture and helps produce a data rich first report.
HACKATHON RECAP 02
Brains & Bots
Hackathon.
A three day hackathon centred on one challenge: disaster response.
60+participants
13teams
3days of building
Brains & Bots asked teams to focus on one real world challenge: disaster response. Over three days, teams built and refined prototypes before presenting how their ideas could help in high pressure situations.
Delivered with the QUT Robotics Club, the hackathon brought AI and machine learning together with robotics hardware. The brief encouraged practical systems that could speed up post disaster operations and help responders make faster, better informed decisions.
From early concepts to working demonstrations, teams had to balance technical thinking with the realities of the people and situations their solutions were designed to support.
FEATURED TEAM SOLUTIONS
Ideas built for the response.
Six practical approaches to finding people, sharing information, and supporting responders in difficult conditions.
AshRovers
A ground rover concept using camera sensing and AI detection to spot people and wildlife after a fire, while monitoring nearby conditions and obstacles.
ARGUS
A disaster recovery sensor system that brings environmental readings and camera snapshots into a live operator dashboard.
Banshees
A microphone array concept designed to isolate human sounds, estimate their direction, and guide a robot toward people trapped under rubble.
DR.BOT
A robot assisted reporting workflow that combines person detection with voice or gesture responses to send structured information to responders.
LifeTrace
A Wi Fi sensing prototype that uses ESP32 channel state information to estimate a person’s likely position and show it on a live heatmap.
SaveWise
A voice guided emergency intake system that captures survivor information, asks follow up questions, and helps organise it for response teams.
THE PHOTO STORY
Built in
the room.
A look back at the teams, prototypes, pitches, and people behind both hackathons.
AIML Hackathon 2026
01 — 07
Brains & Bots Hackathon
01 — 04
