261 lines
9.8 KiB
HTML
261 lines
9.8 KiB
HTML
<head>
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<meta charset="utf-8" />
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<meta name="viewport" content="width=device-width, initial-scale=1" />
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<title>Michael Pivato</title>
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<link rel="stylesheet" href="node_modules/@picocss/pico/css/pico.min.css" />
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<link rel="stylesheet" href="site.css" />
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</head>
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<body>
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<main class="container">
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<aside>
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<nav class="closed-on-mobile">
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<ul>
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<li><a class="contrast" href="#career">Career</a></li>
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<li><a class="secondary" href="#powerhealth">PowerHealth</a></li>
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<li><a class="secondary" href="#dstgroup">DST Group</a></li>
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<li><a class="secondary" href="#kilburn">Kilburn Software</a></li>
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<li><a class="contrast" href="#education">Education</a></li>
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<li><a class="contrast" href="#skills">Skills</a></li>
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<li><a class="contrast" href="#hobbies">Hobby Projects</a></li>
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<li><a class="secondary" href="#picar">PiCar</a></li>
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<li>
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<a class="secondary" href="#depthprediction">Depth Prediction</a>
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</li>
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</ul>
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</nav>
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</aside>
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<div role="document">
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<header>
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<hgroup>
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<h1>Michael Pivato</h1>
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<h2>Career summary and interests</h2>
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</hgroup>
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</header>
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<p>
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A driven and highly motivated full-stack developer, I am always ready to
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improve and learn. With a vast knowledge of multiple programming
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languages, paradigms and related technicologies, I have successfully
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implemented many applications that have been used and loved by clients.
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</p>
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<section id="career">
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<h2>Career</h2>
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<hgroup id="powerhealth">
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<h3>PowerHealth Solutions</h3>
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<h4>2019 - Current</h4>
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</hgroup>
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<h4>Key Responsibilities</h4>
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<ul>
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<li>
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Redesign and maintain the PowerHealth Solutions costing product
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(PPM).
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</li>
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<li>
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Create and maintain various front- and back-end components to
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support consistent theming, quality, and developer experience across
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PPM and now the billing product.
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</li>
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<li>
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Respond to internal and client feedback to improve the costing
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product.
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</li>
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<li>Develop automated tests to improve code quality.</li>
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</ul>
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<h4>Key Achievements</h4>
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<ul>
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<li>
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Significant contributions to the redesigned costing product, that is
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now in production use and enjoyed by clients.
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</li>
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<li>
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Create and setup front-end and associated web server back-end
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components on the costing and billing products, as well as internal
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products.
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</li>
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</ul>
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<details id="dstgroup">
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<summary role="button" class="contrast">DST Group</summary>
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<hgroup>
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<h4>Cadet at DST Group</h4>
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<h5>2018 - 2019</h5>
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</hgroup>
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<h5>Key Responsibilities</h5>
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<ul>
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<li>
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Research distributed systems and middleware for use in tactical
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situations.
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</li>
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<li>Develop a project to show this research.</li>
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<li>
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Write about new technologies, their benefits to defence, and how
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they can be used.
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</li>
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<li>Held a Negative Vetting 1 (NV1) Security Clearance.</li>
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</ul>
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<h5>Key Achievements</h5>
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<ul>
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<li>Implementation of Raft algorithm for the camera network.</li>
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<li>
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Implementation of Hand Detection using CNN, and finger recognition
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with alternative algorithm.
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</li>
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</ul>
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</details>
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<details id="kilburn">
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<summary role="button" class="contrast">Kilburn Software</summary>
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<hgroup>
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<h4>Software Developer at Kilburn Software</h4>
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<h5>2016 - 2018</h5>
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</hgroup>
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<h5>Key Responsibilities</h5>
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<ul>
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<li>Develop Mac and iOS applications using Xamarin and C#.</li>
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<li>
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Network and MS-SQL Server Troubleshooting and Implementation.
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</li>
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<li>
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Adhere to quality standards regarding privacy of information for
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schools.
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</li>
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<li>
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Liaise with stakeholders of the application being developed.
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</li>
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</ul>
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<h5>Key Achievements</h5>
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<ul>
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<li>Rollout of macOS and iOS applications to several schools.</li>
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<li>
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Set up a testing station in the office to simulate a Catholic
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Primary School.
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</li>
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</ul>
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</details>
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</section>
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<section id="education">
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<h2>Education</h2>
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<hgroup>
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<h3>Bachelor of Information Technology</h3>
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<h4>2016 - 2018</h4>
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</hgroup>
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<p>University of South Australia</p>
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<p>GPA: 6.89</p>
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<h4>Awards</h4>
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<ul>
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<li>
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University of South Australia 25th Anniversary Excellence
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Scholarship
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</li>
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<li>2nd year Scholarship in Information Technology</li>
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<li>3rd year Scholarship in Information Technology</li>
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<li>Chancellors Letters of Commendation</li>
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</ul>
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</section>
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<section id="skills">
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<h2>Skills</h2>
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<ul>
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<li>Java</li>
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<li>Angular and Web - including Typescript/Javascript, CSS, HTML</li>
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<li>SQL - primarily MSSQL/T-SQL</li>
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<li>Rust</li>
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<li>Flutter/Dart</li>
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<li>Xamarin + C#/.Net</li>
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<li>Python</li>
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</ul>
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</section>
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<section id="hobbies">
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<h2>Hobby Projects</h2>
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<p>
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Over the years I've hacked away at various personal projects. My
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preference is always to build, run and host applications locally,
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which includes this page!
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</p>
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<p>
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Recently my interesets have shifted slightly to large machine learning
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models, and have messed around with Stable Diffusion (mainly with
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<a href="https://github.com/invoke-ai">Invoke AI</a>) and Llama
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language models in
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<a href="https://github.com/rustformers/llm">rustformers</a>. The
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latter has been a bit dissappointing (at least for its programming
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ability), and I think my job will stick around a while longer!
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</p>
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<p>
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Finally I've thoroughly enjoyed writing in Rust, mainly the
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efficiency, ease of use and correctness that come from using this
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programming language. One example was in the
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<a href="https://vato.ddns.net/gitlab/vato007/coster-rs"
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>FastCoster</a
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>
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project, where I reduced the time taken for processing some demo data
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on the costing product from ~1.5 hours to ~7 seconds on a
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laptop/desktop, or ~36 seconds on a smartphone. This was mainly due to
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not using SQL Server, and using a custom algorithm in overhead
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allocation that significantly reduced memory consumption and the
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number of required calculations.
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</p>
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<hgroup id="picar">
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<h3>PiCar</h3>
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<a href="https://vato.ddns.net/gitlab/vato007/picar">Source</a>
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</hgroup>
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<p>
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This project originally involved communication between a Raspberry Pi
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and a Traxxas Slash using the Pi's GPIO to control the steering and
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throttle of the RC Car. This was mounted on some 3D printed
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brackets.The steering and throttle are set using an iPhone/Android
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application connected over WiFi.
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</p>
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<p>Over time this worked as a base to explore other ideas, namely:</p>
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<ul>
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<li>
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SLAM: Using BreezySLAM and a 2D RP Lidar A1, the Pi can map out an
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area and send this information to the controlling phone.
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</li>
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<li>
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Depth Prediction: Using the Pi's camera and an Intel Neural Compute
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Stick (NCS), the Pi could process camera data and use a custom
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implementation of the
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<a href="https://vato.ddns.net/gitlab/vato007/fast-depth-tf"
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>FastDepth</a
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Neural Network to add 3D sensing capabilities.
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</li>
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</ul>
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<p>
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Recently there have been efforts to port the backend to Rust, with the
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2D Lidar sensing and control completed. The Python BreezySLAM
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implementation is currently unfinished, mainly due to distractions
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from other projects
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</p>
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<hgroup id="depthprediction">
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<h3>Depth Prediction</h3>
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<a href="https://vato.ddns.net/gitlab/vato007/fast-depth-tf"
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>Source</a
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>
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</hgroup>
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<p>
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From the PiCar project, I explored many different implementations of
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monocular depth Prediction and 3D SLAM solutions, including
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implementing my own algorithms and trainers for depth prediction that
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perform well on constrained devices.
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</p>
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<p>
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This gave me a solid foundation on Tensorflow/Keras and computer
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vision. It also helped expand my knowledge on machine learning from
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university/online study, as I previously had not explored models this
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large, or specifically computer vision related models.
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</p>
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</section>
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<footer class="container">
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<small
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>Michael Pivato • 2023 •
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<a
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class="secondary"
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href="https://vato.ddns.net/gitlab/vato007/website/-/blob/main/LICENSE.md"
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>MIT License</a
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></small
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>
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</footer>
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</div>
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</main>
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</body>
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