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375 lines
15 KiB
HTML
<!DOCTYPE html>
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<html lang="en">
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<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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name="theme-color"
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media="(prefers-color-scheme: light)"
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content="#2a3140"
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<meta
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name="description"
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content="Michael Pivato's Resume: Career summary and interests"
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/>
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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>
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<a class="secondary" href="#telstrahealth">Telstra Health</a>
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</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="secondary" href="#awards">Awards</a></li>
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<li><a class="contrast" href="#skills">Skills</a></li>
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<li><a class="secondary" href="#technical">Technical</a></li>
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<li><a class="secondary" href="#other">Other</a></li>
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<li><a class="contrast" href="#hobbies">Hobby Projects</a></li>
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<li>
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<a class="secondary" href="#bufpiv">Buf Piv</a>
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</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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<p>Career summary and interests</p>
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<a href="contact">Contact</a>
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</hgroup>
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</header>
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<p>
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As a driven and highly motivated full-stack software engineer, I am
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always ready to improve and learn. With a vast knowledge of multiple
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programming languages, paradigms and related technologies, I have
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successfully implemented many applications that have been used and
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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="telstrahealth">
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<h3>Senior Software Engineer at Telstra Health</h3>
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<p>2024 - Current</p>
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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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Design, maintain and implement modern solutions in various
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products, primarily the enterprise costing product (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
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across PPM and the billing product (PBRC).
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</li>
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<li>Respond to internal and client feedback to improve PPM.</li>
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<li>Develop automated tests to improve code quality.</li>
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<li>Review and assist new developers in the team.</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 PPM, including designing and
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implementing shared libraries for use in other teams.
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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 PPM AND PBRC, as well as internal products.
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</li>
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<li>
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Created the PowerAnalytics product within the PPM reporting
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framework, which improved the speed and functionality of an
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implementation in PowerBI by another team that experienced cost
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blowouts.
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</li>
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</ul>
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<details id="powerhealth">
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<summary role="button" class="contrast">
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PowerHealth Solutions
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</summary>
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<hgroup>
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<h3>Software Developer at PowerHealth Solutions</h3>
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<p>2019 - 2024</p>
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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
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across PPM and the billing product (PBRC).
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</li>
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<li>Respond to internal and client feedback to improve PPM.</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,
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that is 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
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internal products.
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</li>
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</ul>
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</details>
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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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<p>2018 - 2019</p>
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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
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recognition 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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<p>2016 - 2018</p>
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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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<p>2016 - 2018</p>
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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 id="awards">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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<hgroup>
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<h3 id="technical">Technical</h3>
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<p>Ordered by proficiency</p>
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</hgroup>
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<ul>
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<li>Java - Gradle, JUnit, Jooq, Swing</li>
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<li>
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Angular and Web - including Typescript/Javascript, CSS, HTML
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</li>
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<li>SQL - primarily MSSQL/T-SQL</li>
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<li>Rust</li>
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<li>Development Tools - Git, Jira, shell script</li>
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<li>Modern Operating Systems - Debian Linux, Windows, macOS</li>
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<li>
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Writing and Consuming OCI Containers - Docker and Podman/Buildah
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</li>
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<li>
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Managed Cloud Services (PaaS) - Azure SQL, Microsoft Entra,
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Cloudflare (this site is hosted on Cloudflare!)
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</li>
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<li>
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Python - Tensorflow and pandas for machine learning and data
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analysis
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</li>
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<li>Flutter/Dart</li>
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<li>Xamarin + C#/.Net</li>
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</ul>
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<h3 id="other">Other</h3>
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<ul>
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<li>UI/UX - responsive, easy to use, and acessible design</li>
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<li>
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Excellent written and verbal communication - handling of client
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and internal feedback, new features and problems
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</li>
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<li>Testing - automated unit and integration tests</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
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learning models, and have messed around with Stable Diffusion
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(mainly with
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<a href="https://github.com/invoke-ai">Invoke AI</a>) and Large
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Language Models such as the
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<a href="https://llama.meta.com">Llama</a> family. I have also
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trained/finetuned LLMs in the past (BERT), however this has been
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outside of my capability recently due to the growth in parameters.
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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://gitea.michaelpivato.dev/vato007/ingey">Ingey</a>
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project, where I reduced the time taken for processing some demo
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data 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
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to 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="bufpiv">
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<h3>Buf Piv</h3>
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<p>
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<a href="https://gitea.michaelpivato.dev/vato007/bufpiv"
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>Source</a
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>
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</p>
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</hgroup>
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<p>
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This is a tauri application that makes it easy to edit json files
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conforming to a protobuf definition. It works as a standalone
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desktop application for the most complete experience, with browser
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support to show tauri's versatility as well.
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</p>
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<p>
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A browser demo is available at
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<a href="https://buf.michaelpivato.dev">BufPiv</a>
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</p>
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<hgroup id="picar">
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<h3>PiCar</h3>
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<p>
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<a href="https://gitea.michaelpivato.dev/vato007/picar">Source</a>
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</p>
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</hgroup>
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<p>
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This project originally involved communication between a Raspberry
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Pi and a Traxxas Slash using the Pi's GPIO to control the steering
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and 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
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Compute Stick (NCS), the Pi could process camera data and use a
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custom implementation of the
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<a href="https://gitea.michaelpivato.dev/vato007/fast-depth-tf"
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>FastDepth</a
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>
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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
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the 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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<p>
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<a href="https://gitea.michaelpivato.dev/vato007/fast-depth-tf"
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>Source</a
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>
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</p>
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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
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that 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
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this 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>Michael Pivato • 2025</small>
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</footer>
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</div>
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</main>
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</body>
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</html>
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