Adelaide, Australia × PhD, Computer Science

HAYDEN FAULKNER

  • Machine Learning Engineer ×
  • Full-Stack Developer ×
  • Data Scientist ×
  • Application Designer ×
  • Team Leader ×

I build software end to end, from the interface and data model through to the cloud and the devices at the edge. I've worked in machine learning for over a decade, and AI is now both what I put into products and how I build them.

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15+ years writing software
10+ years in machine learning & AI
PhD computer vision & video understanding
5+ products owned from concept to production

01 About

Portrait of Hayden Faulkner
× Dr Hayden Faulkner

I'm a software engineer and machine learning specialist based in Adelaide. For the last several years I've worked inside startups, mainly Insight Via Artificial Intelligence and Woven Optics, as the person who takes a product from an idea to something running in production: the UI, the data design, the backend, the cloud, and the hardware at the edge.

Before that I completed a PhD at The University of Adelaide and the Australian Institute for Machine Learning, researching general and fine-grained video understanding. That's where the computer vision and data science comes from, along with a habit of looking for the answer hidden in the data.

AI is also how I work, not only what I build. I use coding assistants such as Copilot and Claude Code throughout development, and because I've trained and evaluated models myself, I know where they speed things up and where their output needs checking.

I work directly with founders, stakeholders and customers, and I like mentoring small teams while staying hands-on with the product.

tldr.txt
  • 15+ years of software development experience
  • Built and owned applications across web, desktop, cloud and embedded systems
  • Worked in startups alongside founders, stakeholders and customers
  • Led and mentored small engineering teams, guiding process and principles
  • PhD in Machine Learning & Computer Vision, developing and integrating AI
  • AI-literate: builds with AI tools daily and knows how the models work underneath

02 What I do

Six things I'm regularly trusted with, often all on the same project.

01

Software × Product

  • Full-stack applications built from the ground up, including UI/UX, data design, frontend, backend and cloud infrastructure.
  • Systems and APIs connecting web apps, third-party APIs, cloud services and physical devices.
02

Machine Learning × Computer Vision × Data Science

  • Gathering, cleaning and analysing data to answer practical questions.
  • Training, evaluating and refining models for real-world problems, then integrating them into production.
  • Visualisations, reports and data storytelling that make complex results clear.
03

AI Tools × AI Literacy

  • AI coding assistants used throughout development to prototype, build, review and document faster.
  • A research background in how these models work, so I know their limits and verify what they produce.
  • Practical judgement on where AI belongs in a product and where it doesn't.
04

Cloud × Infrastructure

  • Cloud systems designed and implemented on AWS and Firebase/GCP.
  • Data pipelines and infrastructure supporting distributed devices and applications.
05

Embedded Systems

  • Software for Raspberry Pi, NVIDIA Jetson and Linux-based systems.
  • Communication, sync and data-processing pipelines linking edge devices to the cloud.
  • Remote management, file transfer and over-the-air software updates.
06

Leadership × Ownership

  • Sole owner or technical lead on multiple products, from concept through to production.
  • Mentoring small engineering teams while staying hands-on and leading by example.
  • Working with founders and customers to shape requirements and technical direction.

Your project?

If it involves data, devices or a product that needs building properly, let's talk.

03 Selected work

Three products I've built or led, all live today.

Sole developer Woven Optics

Wool Scanner

A handheld instrument that predicts the micron of an individual fleece in real time, paired with a web dashboard that turns each session into decisions for growers and buyers.

  • Built the full stack as sole developer: frontend, backend and cloud.
  • Dashboard for session statistics, histograms, animal rankings and one-click export.
0.9961
R² correlation in published performance testing
30 s
to 2 minutes per result, on the farm
  • React
  • Firebase
  • GCP
scanner.wovenoptics.com ↗
Tech lead Insight Via Artificial Intelligence

Clear Call

A telehealth platform that gives specialists the audio, visual and clinical detail they need to assess risk and decide on escalation remotely.

  • Led the technical development of the product.
  • Designed the UI and built the frontend.
In trial
at the Royal Adelaide Hospital multidisciplinary foot clinic
3D
wound surface modelling for remote measurement
  • React
  • AWS
clearcall.au ↗
Sole developer Centre for Automotive Safety Research × IVAI

Project Velograph

An open research project measuring how closely vehicles pass cyclists, using devices mounted on participants' own bikes and a public map of the results.

  • Built the full stack as sole developer: frontend, backend and cloud.
  • Participant portal for uploading rides, plus the interactive public data map.
100k+
vehicle passes recorded
55k+
kilometres ridden by 180+ participants
  • React
  • Firebase
  • GCP
project.velograph.app ↗

04 Experience

  1. 2021 – Present

    Software × Product × ML × Cloud × Embedded × Leadership

    • Designed and built full-stack applications from the ground up: UI/UX, data design, frontend, backend and cloud.
    • Solely owned or led the technical development of multiple products from concept through to production.
    • Built systems linking web apps, cloud services and edge devices (Raspberry Pi, NVIDIA Jetson), including sync pipelines, file transfer and remote software updates.
    • Designed and implemented cloud systems on AWS and Firebase/GCP.
    • Developed and integrated machine learning and computer vision into production applications.
    • Mentored small engineering teams and worked directly with founders and customers to shape product direction.
  2. 2019 – 2021

    Machine Learning × Computer Vision × Data Science

    • Gathered, filtered, cleaned and analysed data, interpreting results to find meaningful insights and answer practical questions.
    • Experimented with, trained and evaluated machine learning algorithms, refining approaches for real-world problems.
    • Developed and integrated ML and computer vision algorithms into production applications.
    • Presented findings through visualisations, reports and data storytelling for customers and stakeholders.
  3. 2015 – 2021

    PhD research × Video understanding

    • Researched image and video classification, detection, captioning and tracking with deep neural networks.
    • Published at DICTA and released the TenniSet dataset and models.

05 Research & talks

Papers, theses and talks from my years in computer vision research.

  • Thesis

    General and Fine-Grained Video Understanding

    PhD thesis × The University of Adelaide × 2021

  • Paper

    TenniSet: A Dataset for Dense Fine-Grained Event Recognition, Localisation and Description

    DICTA 2017 × Digital Image Computing: Techniques and Applications

  • Paper

    AFL Player Detection and Tracking

    DICTA 2015 × Digital Image Computing: Techniques and Applications

  • Paper

    A Study of the Region Covariance Descriptor: Impact of Feature Selection and Image Transformations

    DICTA 2015 × Digital Image Computing: Techniques and Applications

  • Paper

    Approximate Approaches to the Traveling Thief Problem

    GECCO 2015 × Genetic and Evolutionary Computation Conference

  • Thesis

    Visual Tracking for Application to AFL Football

    Honours thesis × The University of Adelaide × 2014

  • Talk

    Panel on AI and Machine Learning

    The University of Adelaide

  • Talk

    Deep Learning for Computer Vision

    Data to Decisions CRC

  • Award

    Three Minute Thesis Winner

    Data to Decisions CRC × national student cohort × Canberra

06 Education

  • PhD in Computer Science General & Fine-Grained Video Understanding

    2021 × The University of Adelaide × The Australian Institute for Machine Learning × The Data to Decisions CRC

  • Honours in Computer Science Top of Class

    2014 × The University of Adelaide

  • Bachelor of Computer Graphics GPA 5.63

    2012 × The University of Adelaide

07 Skills

Languages
TypeScriptJavaScriptPythonHTMLCSSCC++SQL
Dev
ReactReact NativeNode.jsAWSFirebaseGCPPyTorchLinux
Specialist
Machine LearningData ScienceComputer VisionImage Processing
AI Tools
GitHub CopilotClaude Code
Design
UI/UXGraphic DesignAdobe Suite
Tools
GitVS Code

08 Contact

Got something
worth building?

Whether it's a product, a data problem or a fleet of devices, I'd like to hear about it.