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<title>Michael Pivato</title>
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<body>
<main class="container">
<aside>
<nav class="closed-on-mobile">
<ul>
<li><a class="contrast" href="#career">Career</a></li>
<li>
<a class="secondary" href="#telstrahealth">Telstra Health</a>
</li>
<li><a class="secondary" href="#powerhealth">PowerHealth</a></li>
<li><a class="secondary" href="#dstgroup">DST Group</a></li>
<li><a class="secondary" href="#kilburn">Kilburn Software</a></li>
<li><a class="contrast" href="#education">Education</a></li>
<li><a class="secondary" href="#awards">Awards</a></li>
<li><a class="contrast" href="#skills">Skills</a></li>
<li><a class="secondary" href="#technical">Technical</a></li>
<li><a class="secondary" href="#other">Other</a></li>
<li><a class="contrast" href="#hobbies">Hobby Projects</a></li>
<li>
<a class="secondary" href="#bufpiv">Buf Piv</a>
</li>
<li><a class="secondary" href="#picar">PiCar</a></li>
<li>
<a class="secondary" href="#depthprediction">Depth Prediction</a>
</li>
</ul>
</nav>
</aside>
<div role="document">
<header>
<hgroup>
<h1>Michael Pivato</h1>
<p>Career summary and interests</p>
<a href="contact">Contact</a>
</hgroup>
</header>
<p>
As a driven and highly motivated full-stack software engineer, I am
always ready to improve and learn. With a vast knowledge of multiple
programming languages, paradigms and related technologies, I have
successfully implemented many applications that have been used and
loved by clients.
</p>
<section id="career">
<h2>Career</h2>
<hgroup id="telstrahealth">
<h3>Senior Software Engineer at Telstra Health</h3>
<p>2024 - Current</p>
</hgroup>
<h4>Key Responsibilities</h4>
<ul>
<li>
Design, maintain and implement modern solutions in various
products, primarily the enterprise costing product (PPM).
</li>
<li>
Create and maintain various front- and back-end components to
support consistent theming, quality, and developer experience
across PPM and the billing product (PBRC).
</li>
<li>Respond to internal and client feedback to improve PPM.</li>
<li>Develop automated tests to improve code quality.</li>
<li>Review and assist new developers in the team.</li>
</ul>
<h4>Key Achievements</h4>
<ul>
<li>
Significant contributions to PPM, including designing and
implementing shared libraries for use in other teams.
</li>
<li>
Create and setup front-end and associated web server back-end
components on PPM AND PBRC, as well as internal products.
</li>
<li>
Created the PowerAnalytics product within the PPM reporting
framework, which improved the speed and functionality of an
implementation in PowerBI by another team that experienced cost
blowouts.
</li>
</ul>
<details id="powerhealth">
<summary role="button" class="contrast">
PowerHealth Solutions
</summary>
<hgroup>
<h3>Software Developer at PowerHealth Solutions</h3>
<p>2019 - 2024</p>
</hgroup>
<h4>Key Responsibilities</h4>
<ul>
<li>
Redesign and maintain the PowerHealth Solutions costing product
(PPM).
</li>
<li>
Create and maintain various front- and back-end components to
support consistent theming, quality, and developer experience
across PPM and the billing product (PBRC).
</li>
<li>Respond to internal and client feedback to improve PPM.</li>
<li>Develop automated tests to improve code quality.</li>
</ul>
<h4>Key Achievements</h4>
<ul>
<li>
Significant contributions to the redesigned costing product,
that is now in production use and enjoyed by clients.
</li>
<li>
Create and setup front-end and associated web server back-end
components on the costing and billing products, as well as
internal products.
</li>
</ul>
</details>
<details id="dstgroup">
<summary role="button" class="contrast">DST Group</summary>
<hgroup>
<h4>Cadet at DST Group</h4>
<p>2018 - 2019</p>
</hgroup>
<h5>Key Responsibilities</h5>
<ul>
<li>
Research distributed systems and middleware for use in tactical
situations.
</li>
<li>Develop a project to show this research.</li>
<li>
Write about new technologies, their benefits to defence, and how
they can be used.
</li>
<li>Held a Negative Vetting 1 (NV1) Security Clearance.</li>
</ul>
<h5>Key Achievements</h5>
<ul>
<li>Implementation of Raft algorithm for the camera network.</li>
<li>
Implementation of Hand Detection using CNN, and finger
recognition with alternative algorithm.
</li>
</ul>
</details>
<details id="kilburn">
<summary role="button" class="contrast">Kilburn Software</summary>
<hgroup>
<h4>Software Developer at Kilburn Software</h4>
<p>2016 - 2018</p>
</hgroup>
<h5>Key Responsibilities</h5>
<ul>
<li>Develop Mac and iOS applications using Xamarin and C#.</li>
<li>
Network and MS-SQL Server Troubleshooting and Implementation.
</li>
<li>
Adhere to quality standards regarding privacy of information for
schools.
</li>
<li>
Liaise with stakeholders of the application being developed.
</li>
</ul>
<h5>Key Achievements</h5>
<ul>
<li>Rollout of macOS and iOS applications to several schools.</li>
<li>
Set up a testing station in the office to simulate a Catholic
Primary School.
</li>
</ul>
</details>
</section>
<section id="education">
<h2>Education</h2>
<hgroup>
<h3>Bachelor of Information Technology</h3>
<p>2016 - 2018</p>
</hgroup>
<p>University of South Australia</p>
<p>GPA: 6.89</p>
<h4 id="awards">Awards</h4>
<ul>
<li>
University of South Australia 25th Anniversary Excellence
Scholarship
</li>
<li>2nd year Scholarship in Information Technology</li>
<li>3rd year Scholarship in Information Technology</li>
<li>Chancellors Letters of Commendation</li>
</ul>
</section>
<section id="skills">
<h2>Skills</h2>
<hgroup>
<h3 id="technical">Technical</h3>
<p>Ordered by proficiency</p>
</hgroup>
<ul>
<li>Java - Gradle, JUnit, Jooq, Swing</li>
<li>
Angular and Web - including Typescript/Javascript, CSS, HTML
</li>
<li>SQL - primarily MSSQL/T-SQL</li>
<li>Rust</li>
<li>Development Tools - Git, Jira, shell script</li>
<li>Modern Operating Systems - Debian Linux, Windows, macOS</li>
<li>
Writing and Consuming OCI Containers - Docker and Podman/Buildah
</li>
<li>
Managed Cloud Services (PaaS) - Azure SQL, Microsoft Entra,
Cloudflare (this site is hosted on Cloudflare!)
</li>
<li>
Python - Tensorflow and pandas for machine learning and data
analysis
</li>
<li>Flutter/Dart</li>
<li>Xamarin + C#/.Net</li>
</ul>
<h3 id="other">Other</h3>
<ul>
<li>UI/UX - responsive, easy to use, and acessible design</li>
<li>
Excellent written and verbal communication - handling of client
and internal feedback, new features and problems
</li>
<li>Testing - automated unit and integration tests</li>
</ul>
</section>
<section id="hobbies">
<h2>Hobby Projects</h2>
<p>
Over the years I've hacked away at various personal projects. My
preference is always to build, run and host applications locally,
however I have come around to cloud services for public-facing
resources, such as CloudFlare, which is used to host this page!
</p>
<p>
I have used AI/ML in the past, as seen in my own Depth Prediction
implementation, and LLMs, where I fine-tuned BERT to perform Named
Entity Recognition, however recent models have gotten too large to
train at home. I also use local LLMs in LM Studio, to provide basic
information and coding assistance when learning a new framework.
Recently my interesets have shifted to designing applications that
can maximise throughput for large datasets and minimise response
time for queries/charts. I'm currently reading
<a
href="https://www.oreilly.com/library/view/designing-data-intensive-applications/9781491903063/"
>Designing Data-Intensive Applications</a
>
to facilitate improvements in the Ingey project once core
implemetation is complete.
</p>
<p>
Finally I've enjoyed writing new applications in Rust; the
efficiency, ease of use and correctness have been fantastic. One
example is in the
<a href="https://gitea.michaelpivato.dev/vato007/ingey">Ingey</a>
project, where I reduced the time to perform reciprocal accounting
on a costing product from ~1.5 hours to ~7 seconds on a
laptop/desktop, or ~36 seconds on a smartphone. This was due to
avoiding non-bulk inserts into a relational database, and using a
custom algorithm in overhead allocation that significantly reduced
memory consumption and the number of required calculations. The
optimisations applied by Rust in release mode also had a significant
impact on performance, and is what facilitated easy deployment to an
iOS application.
</p>
<hgroup id="bufpiv">
<h3>Buf Piv</h3>
<p>
<a href="https://gitea.michaelpivato.dev/vato007/bufpiv"
>Source</a
>
</p>
</hgroup>
<p>
This is a Tauri + Angular application that makes it easy to edit
json files conforming to a protobuf definition. It works as a
standalone desktop application for the most complete experience,
with browser support to show Tauri's versatility as well.
</p>
<p>
A browser demo is available at
<a href="https://buf.michaelpivato.dev">BufPiv</a>
</p>
<hgroup id="picar">
<h3>PiCar</h3>
<p>
<a href="https://gitea.michaelpivato.dev/vato007/picar">Source</a>
</p>
</hgroup>
<p>
This project originally involved communication between a Raspberry
Pi and a Traxxas Slash using the Pi's GPIO to control the steering
and throttle of the RC Car. This was mounted on some 3D printed
brackets. The steering and throttle are set by an iPhone/Android
application connected over WiFi.
</p>
<p>Over time this worked as a base to explore other ideas, namely:</p>
<ul>
<li>
SLAM: Using BreezySLAM and a 2D RP Lidar A1, the Pi can map out an
area and send this information to the controlling phone.
</li>
<li>
Depth Prediction: Using the Pi's camera and an Intel Neural
Compute Stick (NCS), the Pi could process camera data and use a
custom implementation of the
<a href="https://gitea.michaelpivato.dev/vato007/fast-depth-tf"
>FastDepth</a
>
Neural Network to add 3D sensing capabilities.
</li>
</ul>
<p>
Recently there have been efforts to port the backend to Rust, with
the 2D Lidar sensing and control completed. The Python BreezySLAM
implementation is currently unfinished, mainly due to work on other
projects
</p>
<hgroup id="depthprediction">
<h3>Depth Prediction</h3>
<p>
<a href="https://gitea.michaelpivato.dev/vato007/fast-depth-tf"
>Source</a
>
</p>
</hgroup>
<p>
From the PiCar project, I explored many different implementations of
monocular depth prediction and 3D SLAM solutions, including
implementing my own algorithms and trainers for depth prediction
that perform well on constrained devices.
</p>
<p>
This gave me a solid foundation on Tensorflow/Keras and computer
vision. It also helped expand my knowledge on machine learning from
university/online study, as I previously had not explored models
this large, or specifically computer vision related models.
</p>
</section>
<footer class="container">
<small>Michael Pivato • 2025</small>
</footer>
</div>
</main>
</body>
</html>