Real technology. Curious minds. Learning to think like engineers.
From a DIY quadcopter to AI-assisted landing decisions.
A hands-on prototype, not just a diagram.
Start by understanding the system, then test how its parts work together.
Choose a motion and compare the illustrative motor outputs.
Rear motors produce more thrust. The drone tilts forward.
Pixels become categories. Categories become risk rules.
AI predicts what it sees. People define which conditions may be risky.
A small decision model with a big engineering lesson.
Zone 1 scored 60.3; Zone 2 scored 38.0. What changes when we add an image-edge safety rule?
Engineering continues after the first prototype.
Explore wall thickness, mounting holes and battery clearance. Compare printed prototypes before revising the CAD model.
See the classroom challenge ↗Four connected missions. Eight lessons. One growing record of evidence.
40 minutes of student lab + 40 minutes of industry application.
How does blade design affect a paper rotor’s fall?
Test three blade lengths, three drops each. Compare averages and explain a fair test.
ZIPLINE · Choose an aircraft for a medical delivery.
Can a lighter drone shell still fit and protect its parts?
Edit a starter CAD shell; check wall thickness, mounting holes and battery space. Compare preprinted A/B prototypes.
DJI AGRICULTURE · Balance payload, weight and working time.
What can a camera see — and what does AI miss?
Capture two views, label objects, edit simple risk rules and check model errors.
WINGTRA · Compare ordinary and 360° image coverage.
Which candidate passes our rules? What if none does?
Test three scenarios; change one threshold and defend the result.
WING · Compare cable delivery with full landing.
The same habit carries across all four sessions.
Core · Use prepared tools and explain.
Challenge · Change a variable and compare.
Extension · Analyze deeper and justify.
Across four teams, I learned to connect user behaviour, data and product decisions. Those experiences now give students concrete examples of how technology works in the world.
Selected responsibilities and what each experience brings into the classroom.
Analyse product usage and user behaviour for the 360-camera line, and contribute to AI-enabled natural-language data querying. The work combines data interpretation, product thinking and applied AI in a physical consumer-technology context.
Sensors · User behaviour · Applied AIBuilt metric frameworks and BI systems, designed funnel analysis and A/B evaluations, conducted user segmentation, and contributed to AI assistant measurement and recommendation.
Experiments · Data literacy · Product designSupported data-platform performance governance, including high-frequency query models and reusable SQL execution-plan diagnostic rules.
Systems thinking · Performance trade-offsStudied monetisation, first-purchase activation, repurchase behaviour and high-value user segments to understand how product use connects to commercial outcomes.
Consumer behaviour · Evidence-based questionsThe common thread: ask a clearer question, find the evidence and make the next decision easier to explain.
I bring technology, data and teaching together to make complex ideas visible, testable and connected to real questions.
My background spans quantitative study, technology products and student-facing teaching. I see those experiences as different ways to do the same work: break down complexity, test an idea with evidence and help someone understand what to do next.
Oliver STEAM Lab is where I document teaching ideas, classroom experiments and projects as they evolve.
MPhil in Innovation, Entrepreneurship and Public Policy. Interdisciplinary study across innovation, policy, research and quantitative analysis.
BSc in Financial Statistics, with a foundation in probability, statistics and quantitative modelling.
Good STEAM learning starts with a real problem that gives each subject a reason to be there.
For teaching, collaboration or project ideas, get in touch.
For teaching, collaboration or project ideas.
Start with the project or teaching approach.