Driving the Future: AutoGuru’s AI Capstone Collaboration with QUT

AutoGuru’s Senior Data Analyst, Paul Ross, shares how AutoGuru’s collaboration with four final-year Computer Science students from the Faculty of Science at the Queensland University of Technology (QUT) provided real value for our tech roadmap and their career development.

I recently had the pleasure of mentoring a talented team of four final-year Computer Science students from QUT as they completed their Capstone project in collaboration with AutoGuru. Now that they've wrapped up, I wanted to share a few reflections on what was a genuinely rewarding experience for everyone involved.

The Challenge

We didn’t give them a theoretical exercise. We tasked the team with a high-value, real-world business problem: to develop a machine learning (ML) model capable of predicting the price of fleet automotive maintenance transactions.

This was no side project. This collaboration is part of our ongoing investment in AI and data-driven systems that power the smarter, faster, and fairer car care experience AutoGuru is building for customers and partners. 

What made the project particularly exciting was the team’s composition. While all were Computer Science majors, their diverse backgrounds spanned Aerospace and Medical Engineering, bringing a blend of analytical thinking and creative problem-solving that enriched every stage of the project.

The Process

As an industry mentor, my role was to guide, not to manage. I provided business context, helped connect their technical insights to commercial realities, and acted as a sounding board as they iterated on their model design.

We held weekly check-ins, and from the very first meeting, the team impressed me with their professionalism and initiative. They managed their project like seasoned consultants: setting clear goals, maintaining transparent communication, and coming prepared to discuss challenges and next steps.

Each member developed a strong sense of ownership over their area, whether it was data cleaning, model training, or evaluation, yet they remained highly collaborative. They sought feedback proactively, navigated technical hurdles with composure, and demonstrated a thoughtful understanding of how their work fit into the broader AutoGuru technology ecosystem.

The Value

By the end of the semester, the team successfully delivered a predictive ML model, along with a thorough investigation into the complexities of pricing within automotive fleet maintenance. Their findings helped validate our internal ML assumptions and informed our next iteration of pricing logic in addition to enhancing our broader AI roadmap. 

For AutoGuru, the project delivered real business value:

• Fresh perspectives on a challenging technical problem

• Focused research grounded in academic rigour

• A prototype that will serve as a stepping stone for further ML enhancements

For the students, this experience offered something even more important, a genuine taste of the industry. They learned how to align academic theory with practical business needs, navigate ambiguity, and present technical work to non-technical stakeholders. It’s the kind of experience that helps turn great students into outstanding professionals.

"This project gave us valuable insights into the real-world applications of machine learning and demonstrated how it can drive meaningful improvements and positive impact within businesses," said Dylan Hessing.

On a personal note, I also found this collaboration deeply enriching. Mentoring the team not only allowed me to support emerging talent but also to stay close to the evolving frontiers of machine learning through their fresh academic insights.

A huge congratulations to Alvin Luu, Dylan Hessing, Jack Langdon, and Theo Dela Cruz on their hard work and achievements. They were an absolute pleasure to work with, and based on their professionalism, teamwork, and curiosity, I have no doubt they’ll each make a strong mark in the tech industry.

At AutoGuru, we’re proud to support initiatives like this that bridge the gap between education and industry. Collaborations like our partnership with QUT are a key part of how we continue to foster innovation, nurture future tech talent, and push the boundaries of what’s possible in automotive technology.

Here’s to the next generation of problem-solvers driving the future forward, one model at a time.

We’re always looking for ways to collaborate with bright minds. If you’re a student or researcher passionate about AI, get in touch at contactus@autoguru.com.au!