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5<link as="script" rel="preload" href="/webpack-runtime-109df70d1f133654fc95.js"/><link as="script" rel="preload" href="/framework-d8da6d7aa71dc8811b0a.js"/><link as="script" rel="preload" href="/app-2f7e4427a9f84b31b812.js"/><link as="script" rel="preload" href="/1bfc9850-bfe0d60a3f7bf3201b91.js"/><link as="script" rel="preload" href="/commons-dc169c0bdfaa1a417811.js"/><link as="script" rel="preload" href="/component---src-templates-index-js-773cf24a610e6c6c08e0.js"/><link as="fetch" rel="preload" href="/page-data/index/page-data.json" crossorigin="anonymous"/><link as="fetch" rel="preload" href="/page-data/sq/d/2903201533.json" crossorigin="anonymous"/><link as="fetch" rel="preload" href="/page-data/app-data.json" crossorigin="anonymous"/></head><body><div id="___gatsby"><div style="outline:none" tabindex="-1" id="gatsby-focus-wrapper"><div class="antialiased bg-back leading-normal font-text text-front"><header class="flex justify-between p-4 lg:px-8"><span class="inline-flex w-14 h-14 lg:mt-4 font-header font-bold text-xl justify-center items-center text-center text-front border-2 border-solid border-front rounded-full">SK</span></header><div class="md:max-w-screen-md lg:max-w-screen-2xl mx-auto px-4 flex flex-wrap pt-4 my-8"><aside class="w-full lg:w-1/3 lg:border-r border-line lg:px-6 xl:px-12"><div class="flex flex-col h-full "><div><h2 class="font-header font-light text-front text-2xl leading-none mb-4">Machine Learning Engineer</h2><h1 class="font-header font-black text-front text-4xl leading-none break-words mb-6">Sergios Karagiannakos</h1><div class="relative inline-block leading-none"><div data-gatsby-image-wrapper="" style="width:144px;height:144px" class="gatsby-image-wrapper rounded-full relative z-10"><div aria-hidden="true" data-placeholder-image="" style="opacity:1;transition:opacity 500ms linear;background-color:#181818;width:144px;height:144px;position:relative"></div><picture><source type="image/webp" data-srcset="/static/f557c04fd57d3cd2f2030740f47625fc/7512d/profile.webp 144w,/static/f557c04fd57d3cd2f2030740f47625fc/654e6/profile.webp 288w" sizes="144px"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="144px" decoding="async" loading="lazy" data-src="/static/f557c04fd57d3cd2f2030740f47625fc/17fa0/profile.jpg" data-srcset="/static/f557c04fd57d3cd2f2030740f47625fc/17fa0/profile.jpg 144w,/static/f557c04fd57d3cd2f2030740f47625fc/d75f5/profile.jpg 288w" alt="Sergios Karagiannakos"/></picture><noscript><picture><source type="image/webp" srcSet="/static/f557c04fd57d3cd2f2030740f47625fc/7512d/profile.webp 144w,/static/f557c04fd57d3cd2f2030740f47625fc/654e6/profile.webp 288w" sizes="144px"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="144px" decoding="async" loading="lazy" src="/static/f557c04fd57d3cd2f2030740f47625fc/17fa0/profile.jpg" srcSet="/static/f557c04fd57d3cd2f2030740f47625fc/17fa0/profile.jpg 144w,/static/f557c04fd57d3cd2f2030740f47625fc/d75f5/profile.jpg 288w" alt="Sergios Karagiannakos"/></picture></noscript>
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5</div><div class="absolute inset-0 rounded-full bg-lead z-0 transform translate-x-12"></div></div><br/><div class="inline-flex items-center bg-front mt-6 w-auto"><span class="text-lead border-r-2 border-back px-3"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 384 512" class="h-4 w-4" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M172.268 501.67C26.97 291.031 0 269.413 0 192 0 85.961 85.961 0 192 0s192 85.961 192 192c0 77.413-26.97 99.031-172.268 309.67-9.535 13.774-29.93 13.773-39.464 0zM192 272c44.183 0 80-35.817 80-80s-35.817-80-80-80-80 35.817-80 80 35.817 80 80 80z"></path></svg></span><span class="text-back font-header font-bold py-1 px-3 text-lg">Athens, Greece</span></div></div><div class="pt-8 pb-12 lg:py-12"><h5 class="font-header font-semibold text-front text-sm uppercase mb-3">Connect</h5><div class="pl-3"><a aria-label="linkedin" class="inline-flex w-12 h-12 justify-center items-center rounded-full -ml-3 bg-front text-back-light hover:shadow-lg transition-shadow duration-150" href="https://www.linkedin.com/in/sergios-karagiannakos" rel="noopener noreferrer" target="_blank"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 448 512" class="w-6 h-6" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M100.28 448H7.4V148.9h92.88zM53.79 108.1C24.09 108.1 0 83.5 0 53.8a53.79 53.79 0 0 1 107.58 0c0 29.7-24.1 54.3-53.79 54.3zM447.9 448h-92.68V302.4c0-34.7-.7-79.2-48.29-79.2-48.29 0-55.69 37.7-55.69 76.7V448h-92.78V148.9h89.08v40.8h1.3c12.4-23.5 42.69-48.3 87.88-48.3 94 0 111.28 61.9 111.28 142.3V448z"></path></svg></a><a aria-label="twitter" class="inline-flex w-12 h-12 justify-center items-center rounded-full -ml-3 bg-back-light text-front hover:shadow-lg transition-shadow duration-150" href="https://twitter.com/KarSergios" rel="noopener noreferrer" target="_blank"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 512 512" class="w-6 h-6" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M459.37 151.716c.325 4.548.325 9.097.325 13.645 0 138.72-105.583 298.558-298.558 298.558-59.452 0-114.68-17.219-161.137-47.106 8.447.974 16.568 1.299 25.34 1.299 49.055 0 94.213-16.568 130.274-44.832-46.132-.975-84.792-31.188-98.112-72.772 6.498.974 12.995 1.624 19.818 1.624 9.421 0 18.843-1.3 27.614-3.573-48.081-9.747-84.143-51.98-84.143-102.985v-1.299c13.969 7.797 30.214 12.67 47.431 13.319-28.264-18.843-46.781-51.005-46.781-87.391 0-19.492 5.197-37.36 14.294-52.954 51.655 63.675 129.3 105.258 216.365 109.807-1.624-7.797-2.599-15.918-2.599-24.04 0-57.828 46.782-104.934 104.934-104.934 30.213 0 57.502 12.67 76.67 33.137 23.715-4.548 46.456-13.32 66.599-25.34-7.798 24.366-24.366 44.833-46.132 57.827 21.117-2.273 41.584-8.122 60.426-16.243-14.292 20.791-32.161 39.308-52.628 54.253z"></path></svg></a><a aria-label="github" class="inline-flex w-12 h-12 justify-center items-center rounded-full -ml-3 bg-front text-back-light hover:shadow-lg transition-shadow duration-150" href="https://github.com/SergiosKar" rel="noopener noreferrer" target="_blank"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" class="w-6 h-6" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></a><a aria-label="goodreads" class="inline-flex w-12 h-12 justify-center items-center rounded-full -ml-3 bg-back-light text-front hover:shadow-lg transition-shadow duration-150" href="https://www.goodreads.com/author/show/22021693.Sergios_K
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7I started my journey with a Masters in Electrical and Computer Engineering and I quickly became super interested in Machine Learning. I have worked as a Data Scientist, as a freelancer ML Engineer with small start-ups, and as a Software Engineer in big tech.
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9AI Summer is the project that I&#x27;m most proud of. Over the past year, we reached a huge audience of AI researchers and aspiring ML Engineers, who are coming to our blog for learning and discussing about AI.
10
11My last role in Hubspot as a part of the Machine Learning Infrastructure team sparked my interest in MLOps, which has been my main focus in the past months. The result? My first book titled &quot;Deep Learning in Production&quot;.
12</div><h5 class="font-header font-semibold text-front text-lg uppercase mt-12 mb-3 text-center">Work history</h5><div class="history flex flex-col relative pt-6 pb-6"><div class="history-entry relative w-1/2 py-4"><span class="dot-bg w-14 h-14 absolute bg-line inline-flex rounded-full items-center justify-center"><span class="dot w-5 h-5 bg-back-light rounded-full"></span></span><h4 class="subpixel-antialiased"><a href="https://theaisummer.com" target="_blank" rel="noopener noreferrer" class="text-lg font-bold hover:opacity-75 transition-opacity duration-150">AI Summer</a></h4><h5 class="text-lg font-normal mb-1">Founder and Deep Learning Writer</h5><span class="text-lg font-medium opacity-50">June 2018 - present</span></div><div class="history-entry relative w-1/2 py-4"><span class="dot-bg w-14 h-14 absolute bg-line inline-flex rounded-full items-center justify-center"><span class="dot w-5 h-5 bg-back-light rounded-full"></span></span><h4 class="subpixel-antialiased"><a href="https://www.hubspot.com/" target="_blank" rel="noopener noreferrer" class="text-lg font-bold hover:opacity-75 transition-opacity duration-150">HubSpot</a></h4><h5 class="text-lg font-normal mb-1">Software Engineer in the Machine Learning Infrastructure team</h5><span class="text-lg font-medium opacity-50">November 2019 - November 2020</span></div><div class="history-entry relative w-1/2 py-4"><span class="dot-bg w-14 h-14 absolute bg-line inline-flex rounded-full items-center justify-center"><span class="dot w-5 h-5 bg-back-light rounded-full"></span></span><h4 class="subpixel-antialiased"><a href="https://www.eworx.gr/" target="_blank" rel="noopener noreferrer" class="text-lg font-bold hover:opacity-75 transition-opacity duration-150">Eworx SA</a></h4><h5 class="text-lg font-normal mb-1">Data Scientist</h5><span class="text-lg font-medium opacity-50">January 2017 - December 2017</span></div><div class="history-entry relative w-1/2 py-4"><span class="dot-bg w-14 h-14 absolute bg-line inline-flex rounded-full items-center justify-center"><span class="dot w-5 h-5 bg-back-light rounded-full"></span></span><h4 class=" text-lg font-bold subpixel-antialiased">Freelance Sofware Engineer</h4><h5 class="text-lg font-normal mb-1">Independent contractor with startups</h5><span class="text-lg font-medium opacity-50">April 2016 - June 2018</span></div><div class="history-entry relative w-1/2 py-4"><span class="dot-bg w-14 h-14 absolute bg-line inline-flex rounded-full items-center justify-center"><span class="dot w-5 h-5 bg-back-light rounded-full"></span></span><h4 class=" text-lg font-bold subpixel-antialiased">University of Patras</h4><h5 class="text-lg font-normal mb-1">MEng Electrical and Computer Engineer</h5><span class="text-lg font-medium opacity-50">September 2012- September 2017</span></div></div><h5 class="font-header font-semibold text-front text-lg uppercase mb-3">Projects and teams</h5><div class="border-t-4 border-line relative flex flex-wrap bg-back-light p-4 lg:p-8 bg-no-repeat text-sm mb-6"><div class="flex flex-wrap content-center w-full pb-4 lg:w-2/5 lg:pr-8 lg:pb-0"><div data-gatsby-image-wrapper="" class="gatsby-image-wrapper gatsby-image-wrapper-constrained"><div style="max-width:640px;display:block"><img alt="" role="presentation" aria-hidden="true" src="data:image/svg+xml;charset=utf-8,%3Csvg height=&#x27;788&#x27; width=&#x27;640&#x27; xmlns=&#x27;http://www.w3.org/2000/svg&#x27; version=&#x27;1.1&#x27;%3E%3C/svg%3E" style="max-width:100%;display:block;position:static"/></div><div aria-hidden="true" data-placeholder-image="" style="opacity:1;transition:opacity 500ms linear;background-color:#082858;position:absolute;top:0;left:0;bottom:0;right:0"></div><picture><source type="image/webp" data-srcset="/static/502e7c498dd9d981ac44c1dcd10f9276/af7d3/deep-learning-production-book.webp 160w,/static/502e7c498dd9d981ac44c1dcd10f9276/b9706/deep-learning-production-book.webp 320w,/static/502e7c498dd9d981ac44c1dcd10f9276/64ff6/deep-learning-production-book.webp 640w" sizes="(min-width: 640px) 640px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 640px) 640px, 100vw" decoding="async" loading="lazy" data-src="/static/502e7c498dd9d981ac44c1dcd10f9276/f4151/deep-learning-production-book.png" data-srcset="/static/502e7c498dd9d981ac44c1dcd10f9276/f0879/deep-learning-production-book.png 160w,/static/502e7c498dd9d981ac44c1dcd10f9276/51fcb/deep-learning-production-book.png 320w,/static/502e7c498dd9d981ac44c1dcd10f9276/f4151/deep-learning-production-book.png 640w" alt="Deep Learning in Production Book"/></picture><noscript><picture><source type="image/webp" srcSet="/static/502e7c498dd9d981ac44c1dcd10f9276/af7d3/deep-learning-production-book.webp 160w,/static/502e7c498dd9d981ac44c1dcd10f9276/b9706/deep-learning-production-book.webp 320w,/static/502e7c498dd9d981ac44c1dcd10f9276/64ff6/deep-learning-production-book.webp 640w" sizes="(min-width: 640px) 640px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 640px) 640px, 100vw" decoding="async" loading="lazy" src="/static/502e7c498dd9d981ac44c1dcd10f9276/f4151/deep-learning-production-book.png" srcSet="/static/502e7c498dd9d981ac44c1dcd10f9276/f0879/deep-learning-production-book.png 160w,/static/502e7c498dd9d981ac44c1dcd10f9276/51fcb/deep-learning-production-book.png 320w,/static/502e7c498dd9d981ac44c1dcd10f9276/f4151/deep-learning-production-book.png 640w" alt="Deep Learning in Production Book"/></picture></noscript>
12<script type="module">const t="undefined"!=typeof HTMLImageElement&&"loading"in HTMLImageElement.prototype;if(t){const t=document.querySelectorAll("img[data-main-image]");for(let e of t){e.dataset.src&&(e.setAttribute("src",e.dataset.src),e.removeAttribute("data-src")),e.dataset.srcset&&(e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset"));const t=e.parentNode.querySelectorAll("source[data-srcset]");for(let e of t)e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset");e.complete&&(e.style.opacity=1)}}</script>
12</div></div><div class="lg:flex-1"><h4 class="font-bold text-lg">Deep Learning in Production Book</h4><a class="text-lg text-front underline break-all hover:opacity-75 transition-opacity duration-150" href="https://amzn.to/3oa50Vj" rel="noreferrer noopener" target="_blank">https://amzn.to/3oa50Vj</a><p class="text-lg w-full py-4 whitespace-pre-line">Deep Leanrning in Production explores how to develop, deploy and scale Deep Learning pipelines with Tensorflow. The reader will learn:
13
14  •  how to design a deep learning system from scratch
15  •  how to structure and develop production-ready machine learning code
16  •  how to develop efficient and scalable data pipelines
17  •  how to make it available to the public by setting up a service on the cloud
18  •  how to scale and maintain the service as the user base grows
19</p><ul class="pr-2"><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back"><span class="inline-block w-2 h-2 rounded-full mr-2 bg-green-500"></span>Status: <!-- -->live</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">MLOps</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Deep Learning</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Tensorflow</li></ul></div></div><div class="border-t-4 border-line relative flex flex-wrap bg-back-light p-4 lg:p-8 bg-no-repeat text-sm mb-6"><div class="flex flex-wrap content-center w-full pb-4 lg:w-2/5 lg:pr-8 lg:pb-0"><div data-gatsby-image-wrapper="" class="gatsby-image-wrapper gatsby-image-wrapper-constrained"><div style="max-width:640px;display:block"><img alt="" role="presentation" aria-hidden="true" src="data:image/svg+xml;charset=utf-8,%3Csvg height=&#x27;320&#x27; width=&#x27;640&#x27; xmlns=&#x27;http://www.w3.org/2000/svg&#x27; version=&#x27;1.1&#x27;%3E%3C/svg%3E" style="max-width:100%;display:block;position:static"/></div><div aria-hidden="true" data-placeholder-image="" style="opacity:1;transition:opacity 500ms linear;background-color:#e8e8f8;position:absolute;top:0;left:0;bottom:0;right:0"></div><picture><source type="image/webp" data-srcset="/static/9844a74228807e4ceba55275be42bade/7aa95/intro-to-dl-course-cover.webp 150w,/static/9844a74228807e4ceba55275be42bade/01d6b/intro-to-dl-course-cover.webp 300w,/static/9844a74228807e4ceba55275be42bade/236f9/intro-to-dl-course-cover.webp 600w" sizes="(min-width: 600px) 600px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 600px) 600px, 100vw" decoding="async" loading="lazy" data-src="/static/9844a74228807e4ceba55275be42bade/90080/intro-to-dl-course-cover.png" data-srcset="/static/9844a74228807e4ceba55275be42bade/fe93a/intro-to-dl-course-cover.png 150w,/static/9844a74228807e4ceba55275be42bade/69574/intro-to-dl-course-cover.png 300w,/static/9844a74228807e4ceba55275be42bade/90080/intro-to-dl-course-cover.png 600w" alt="Introduction to Deep Learning and Neural Networks Course"/></picture><noscript><picture><source type="image/webp" srcSet="/static/9844a74228807e4ceba55275be42bade/7aa95/intro-to-dl-course-cover.webp 150w,/static/9844a74228807e4ceba55275be42bade/01d6b/intro-to-dl-course-cover.webp 300w,/static/9844a74228807e4ceba55275be42bade/236f9/intro-to-dl-course-cover.webp 600w" sizes="(min-width: 600px) 600px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 600px) 600px, 100vw" decoding="async" loading="lazy" src="/static/9844a74228807e4ceba55275be42bade/90080/intro-to-dl-course-cover.png" srcSet="/static/9844a74228807e4ceba55275be42bade/fe93a/intro-to-dl-course-cover.png 150w,/static/9844a74228807e4ceba55275be42bade/69574/intro-to-dl-course-cover.png 300w,/static/9844a74228807e4ceba55275be42bade/90080/intro-to-dl-course-cover.png 600w" alt="Introduction to Deep Learning and Neural Networks Course"/></picture></noscript>
19<script type="module">const t="undefined"!=typeof HTMLImageElement&&"loading"in HTMLImageElement.prototype;if(t){const t=document.querySelectorAll("img[data-main-image]");for(let e of t){e.dataset.src&&(e.setAttribute("src",e.dataset.src),e.removeAttribute("data-src")),e.dataset.srcset&&(e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset"));const t=e.parentNode.querySelectorAll("source[data-srcset]");for(let e of t)e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset");e.complete&&(e.style.opacity=1)}}</script>
19</div></div><div class="lg:flex-1"><h4 class="font-bold text-lg">Introduction to Deep Learning and Neural Networks Course</h4><a class="text-lg text-front underline break-all hover:opacity-75 transition-opacity duration-150" href="https://www.educative.io/courses/intro-deep-learning/" rel="noreferrer noopener" target="_blank">https://www.educative.io/courses/intro-deep-learning/</a><p class="text-lg w-full py-4 whitespace-pre-line">The course provides to the student the basic concepts they need in order to start working with and training various machine learning models. 
20
21Takeaway Skills:
22  • Understanding of the most popular Deep Learning models
23  • A solid grasp on the mathematics and the intuition behind the algorithms
24  • A good experience with Deep Learning Programming and Pytorch
25</p><ul class="pr-2"><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back"><span class="inline-block w-2 h-2 rounded-full mr-2 bg-green-500"></span>Status: <!-- -->live</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Deep Learning</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Pytorch</li></ul></div></div><div class="border-t-4 border-line relative flex flex-wrap bg-back-light p-4 lg:p-8 bg-no-repeat text-sm mb-6"><div class="flex flex-wrap content-center w-full pb-4 lg:w-2/5 lg:pr-8 lg:pb-0"><div data-gatsby-image-wrapper="" class="gatsby-image-wrapper gatsby-image-wrapper-constrained"><div style="max-width:640px;display:block"><img alt="" role="presentation" aria-hidden="true" src="data:image/svg+xml;charset=utf-8,%3Csvg height=&#x27;94.89655172413792&#x27; width=&#x27;640&#x27; xmlns=&#x27;http://www.w3.org/2000/svg&#x27; version=&#x27;1.1&#x27;%3E%3C/svg%3E" style="max-width:100%;display:block;position:static"/></div><div aria-hidden="true" data-placeholder-image="" style="opacity:1;transition:opacity 500ms linear;background-color:#f8a848;position:absolute;top:0;left:0;bottom:0;right:0"></div><picture><source type="image/webp" data-srcset="/static/01eca04941cd887e192b03f09a749811/29c13/aisummer-image.webp 145w,/static/01eca04941cd887e192b03f09a749811/ff1d2/aisummer-image.webp 290w,/static/01eca04941cd887e192b03f09a749811/09150/aisummer-image.webp 580w" sizes="(min-width: 580px) 580px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 580px) 580px, 100vw" decoding="async" loading="lazy" data-src="/static/01eca04941cd887e192b03f09a749811/73358/aisummer-image.png" data-srcset="/static/01eca04941cd887e192b03f09a749811/65e38/aisummer-image.png 145w,/static/01eca04941cd887e192b03f09a749811/828a8/aisummer-image.png 290w,/static/01eca04941cd887e192b03f09a749811/73358/aisummer-image.png 580w" alt="AI Summer"/></picture><noscript><picture><source type="image/webp" srcSet="/static/01eca04941cd887e192b03f09a749811/29c13/aisummer-image.webp 145w,/static/01eca04941cd887e192b03f09a749811/ff1d2/aisummer-image.webp 290w,/static/01eca04941cd887e192b03f09a749811/09150/aisummer-image.webp 580w" sizes="(min-width: 580px) 580px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 580px) 580px, 100vw" decoding="async" loading="lazy" src="/static/01eca04941cd887e192b03f09a749811/73358/aisummer-image.png" srcSet="/static/01eca04941cd887e192b03f09a749811/65e38/aisummer-image.png 145w,/static/01eca04941cd887e192b03f09a749811/828a8/aisummer-image.png 290w,/static/01eca04941cd887e192b03f09a749811/73358/aisummer-image.png 580w" alt="AI Summer"/></picture></noscript>
25<script type="module">const t="undefined"!=typeof HTMLImageElement&&"loading"in HTMLImageElement.prototype;if(t){const t=document.querySelectorAll("img[data-main-image]");for(let e of t){e.dataset.src&&(e.setAttribute("src",e.dataset.src),e.removeAttribute("data-src")),e.dataset.srcset&&(e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset"));const t=e.parentNode.querySelectorAll("source[data-srcset]");for(let e of t)e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset");e.complete&&(e.style.opacity=1)}}</script>
25</div></div><div class="lg:flex-1"><h4 class="font-bold text-lg">AI Summer</h4><a class="text-lg text-front underline break-all hover:opacity-75 transition-opacity duration-150" href="https://theaisummer.com/" rel="noreferrer noopener" target="_blank">https://theaisummer.com/</a><p class="text-lg w-full py-4 whitespace-pre-line">I founded AI Summer as a way to document my journey in Machine Learning. Now AI Summer is one of the biggest educational Deep Learning blogs globally with over 40.000 monthly visitors, a newsletter of 3000 emails and almost 100 highly detailed articles. 
26
27We cover a wide range of topics  from Computer Vision and Natural Language Processing to Machine Learning Infrastructure, Medical Imaging and Reinforcement Learning.
28</p><ul class="pr-2"><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back"><span class="inline-block w-2 h-2 rounded-full mr-2 bg-green-500"></span>Status: <!-- -->live</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Deep Learning</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Machine Learning</li></ul></div></div><div class="border-t-4 border-line relative flex flex-wrap bg-back-light p-4 lg:p-8 bg-no-repeat text-sm mb-6"><div class="flex flex-wrap content-center w-full pb-4 lg:w-2/5 lg:pr-8 lg:pb-0"><div data-gatsby-image-wrapper="" class="gatsby-image-wrapper gatsby-image-wrapper-constrained"><div style="max-width:640px;display:block"><img alt="" role="presentation" aria-hidden="true" src="data:image/svg+xml;charset=utf-8,%3Csvg height=&#x27;248.54368932038832&#x27; width=&#x27;640&#x27; xmlns=&#x27;http://www.w3.org/2000/svg&#x27; version=&#x27;1.1&#x27;%3E%3C/svg%3E" style="max-width:100%;display:block;position:static"/></div><div aria-hidden="true" data-placeholder-image="" style="opacity:1;transition:opacity 500ms linear;background-color:#f8f8f8;position:absolute;top:0;left:0;bottom:0;right:0"></div><picture><source type="image/webp" data-srcset="/static/a1ef70de0abfce1cc12184ea2cb74865/15fac/hubspot-logo.webp 129w,/static/a1ef70de0abfce1cc12184ea2cb74865/bf62b/hubspot-logo.webp 258w,/static/a1ef70de0abfce1cc12184ea2cb74865/ec51e/hubspot-logo.webp 515w" sizes="(min-width: 515px) 515px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 515px) 515px, 100vw" decoding="async" loading="lazy" data-src="/static/a1ef70de0abfce1cc12184ea2cb74865/ccdf9/hubspot-logo.jpg" data-srcset="/static/a1ef70de0abfce1cc12184ea2cb74865/30d27/hubspot-logo.jpg 129w,/static/a1ef70de0abfce1cc12184ea2cb74865/0b19e/hubspot-logo.jpg 258w,/static/a1ef70de0abfce1cc12184ea2cb74865/ccdf9/hubspot-logo.jpg 515w" alt="HubSpot - Machine Learning Infrastructure team"/></picture><noscript><picture><source type="image/webp" srcSet="/static/a1ef70de0abfce1cc12184ea2cb74865/15fac/hubspot-logo.webp 129w,/static/a1ef70de0abfce1cc12184ea2cb74865/bf62b/hubspot-logo.webp 258w,/static/a1ef70de0abfce1cc12184ea2cb74865/ec51e/hubspot-logo.webp 515w" sizes="(min-width: 515px) 515px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 515px) 515px, 100vw" decoding="async" loading="lazy" src="/static/a1ef70de0abfce1cc12184ea2cb74865/ccdf9/hubspot-logo.jpg" srcSet="/static/a1ef70de0abfce1cc12184ea2cb74865/30d27/hubspot-logo.jpg 129w,/static/a1ef70de0abfce1cc12184ea2cb74865/0b19e/hubspot-logo.jpg 258w,/static/a1ef70de0abfce1cc12184ea2cb74865/ccdf9/hubspot-logo.jpg 515w" alt="HubSpot - Machine Learning Infrastructure team"/></picture></noscript>
28<script type="module">const t="undefined"!=typeof HTMLImageElement&&"loading"in HTMLImageElement.prototype;if(t){const t=document.querySelectorAll("img[data-main-image]");for(let e of t){e.dataset.src&&(e.setAttribute("src",e.dataset.src),e.removeAttribute("data-src")),e.dataset.srcset&&(e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset"));const t=e.parentNode.querySelectorAll("source[data-srcset]");for(let e of t)e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset");e.complete&&(e.style.opacity=1)}}</script>
28</div></div><div class="lg:flex-1"><h4 class="font-bold text-lg">HubSpot - Machine Learning Infrastructure team</h4><p class="text-lg w-full py-4 whitespace-pre-line">• The Machine Learning Infrastructure team is responsible for building and maintaining all Machine Learning services and pipelines inside HubSpot. Handled more than 1 billion requests per day and almost 70 machine learning models on production.
29
30• Technologies used: Java, Python, MySQL, HBase, Hadoop, Kafka, AWS, Docker, Kubernetes
31</p><ul class="pr-2"><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Machine Learning</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">MLOps</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Java</li></ul></div></div><div class="border-t-4 border-line relative flex flex-wrap bg-back-light p-4 lg:p-8 bg-no-repeat text-sm mb-6"><div class="lg:flex-1"><h4 class="font-bold text-lg">Master thesis - Development of computer vision framework with deep learning techniques</h4><a class="text-lg text-front underline break-all hover:opacity-75 transition-opacity duration-150" href="https://nemertes.lis.upatras.gr/jspui/handle/10889/10955?mode=full" rel="noreferrer noopener" target="_blank">https://nemertes.lis.upatras.gr/jspui/handle/10889/10955?mode=full</a><p class="text-lg w-full py-4 whitespace-pre-line">As part of my thesis during my MEng degree in Electrical and Computer Engineering , we developed a Computer Vision library that allows the user to recognize objects in images using deep learning. To accomplish that, the user/developer can define his own neural network architecture and train his own images on it.
32
33The system supports fully connected and convolutional neural networks , which we implement in C++ from scratch. To speed up the training, we decided use parallelization and execute the training in GPU, which we programmed with the OpenCL library. Also OpenCV was used to parse and read the images and do all the necessary preprocessing of the dataset.
34</p><ul class="pr-2"><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Deep Learning</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">GPU programming</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Computer vision</li></ul></div></div><div class="border-t-4 border-line relative flex flex-wrap bg-back-light p-4 lg:p-8 bg-no-repeat text-sm mb-6"><div class="flex flex-wrap content-center w-full pb-4 lg:w-2/5 lg:pr-8 lg:pb-0"><div data-gatsby-image-wrapper="" class="gatsby-image-wrapper gatsby-image-wrapper-constrained"><div style="max-width:640px;display:block"><img alt="" role="presentation" aria-hidden="true" src="data:image/svg+xml;charset=utf-8,%3Csvg height=&#x27;640&#x27; width=&#x27;640&#x27; xmlns=&#x27;http://www.w3.org/2000/svg&#x27; version=&#x27;1.1&#x27;%3E%3C/svg%3E" style="max-width:100%;display:block;position:static"/></div><div aria-hidden="true" data-placeholder-image="" style="opacity:1;transition:opacity 500ms linear;background-color:#c80818;position:absolute;top:0;left:0;bottom:0;right:0"></div><picture><source type="image/webp" data-srcset="/static/474dbc206f90c078f50fd5793e065ded/b25ad/eworx-logo.webp 128w,/static/474dbc206f90c078f50fd5793e065ded/7c855/eworx-logo.webp 256w,/static/474dbc206f90c078f50fd5793e065ded/b91d2/eworx-logo.webp 512w" sizes="(min-width: 512px) 512px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 512px) 512px, 100vw" decoding="async" loading="lazy" data-src="/static/474dbc206f90c078f50fd5793e065ded/d3e98/eworx-logo.jpg" data-srcset="/static/474dbc206f90c078f50fd5793e065ded/8fc82/eworx-logo.jpg 128w,/static/474dbc206f90c078f50fd5793e065ded/6e29a/eworx-logo.jpg 256w,/static/474dbc206f90c078f50fd5793e065ded/d3e98/eworx-logo.jpg 512w" alt="Eworx SA"/></picture><noscript><picture><source type="image/webp" srcSet="/static/474dbc206f90c078f50fd5793e065ded/b25ad/eworx-logo.webp 128w,/static/474dbc206f90c078f50fd5793e065ded/7c855/eworx-logo.webp 256w,/static/474dbc206f90c078f50fd5793e065ded/b91d2/eworx-logo.webp 512w" sizes="(min-width: 512px) 512px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 512px) 512px, 100vw" decoding="async" loading="lazy" src="/static/474dbc206f90c078f50fd5793e065ded/d3e98/eworx-logo.jpg" srcSet="/static/474dbc206f90c078f50fd5793e065ded/8fc82/eworx-logo.jpg 128w,/static/474dbc206f90c078f50fd5793e065ded/6e29a/eworx-logo.jpg 256w,/static/474dbc206f90c078f50fd5793e065ded/d3e98/eworx-logo.jpg 512w" alt="Eworx SA"/></picture></noscript>
34<script type="module">const t="undefined"!=typeof HTMLImageElement&&"loading"in HTMLImageElement.prototype;if(t){const t=document.querySelectorAll("img[data-main-image]");for(let e of t){e.dataset.src&&(e.setAttribute("src",e.dataset.src),e.removeAttribute("data-src")),e.dataset.srcset&&(e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset"));const t=e.parentNode.querySelectorAll("source[data-srcset]");for(let e of t)e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset");e.complete&&(e.style.opacity=1)}}</script>
34</div></div><div class="lg:flex-1"><h4 class="font-bold text-lg">Eworx SA</h4><p class="text-lg w-full py-4 whitespace-pre-line">• Built the core of a real-time Recommendation Engine with Python using Natural Language processing and Machine Learning techniques for Experly, a travelling web application.
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36• Designed an in-house library for Source Code Analysis for different programming languages.
37
38• Implemented data science pipelines for tasks such as spell correction, language detection on different projects for European organizations such as CEDEFOP and Skills Panorama websites.
39</p><ul class="pr-2"><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">R</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Python</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Javascript</li></ul></div></div><div class="border-t-4 border-line relative flex flex-wrap bg-back-light p-4 lg:p-8 bg-no-repeat text-sm mb-6"><div class="flex flex-wrap content-center w-full pb-4 lg:w-2/5 lg:pr-8 lg:pb-0"><div data-gatsby-image-wrapper="" class="gatsby-image-wrapper gatsby-image-wrapper-constrained"><div style="max-width:640px;display:block"><img alt="" role="presentation" aria-hidden="true" src="data:image/svg+xml;charset=utf-8,%3Csvg height=&#x27;602&#x27; width=&#x27;640&#x27; xmlns=&#x27;http://www.w3.org/2000/svg&#x27; version=&#x27;1.1&#x27;%3E%3C/svg%3E" style="max-width:100%;display:block;position:static"/></div><div aria-hidden="true" data-placeholder-image="" style="opacity:1;transition:opacity 500ms linear;background-color:#f8f8f8;position:absolute;top:0;left:0;bottom:0;right:0"></div><picture><source type="image/webp" data-srcset="/static/a1b384c7eb0621fc0dc867539ddfd515/ddf18/etf-db.webp 160w,/static/a1b384c7eb0621fc0dc867539ddfd515/348bc/etf-db.webp 320w,/static/a1b384c7eb0621fc0dc867539ddfd515/5c62e/etf-db.webp 640w,/static/a1b384c7eb0621fc0dc867539ddfd515/6bef2/etf-db.webp 1280w" sizes="(min-width: 640px) 640px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 640px) 640px, 100vw" decoding="async" loading="lazy" data-src="/static/a1b384c7eb0621fc0dc867539ddfd515/020e1/etf-db.jpg" data-srcset="/static/a1b384c7eb0621fc0dc867539ddfd515/4ea5c/etf-db.jpg 160w,/static/a1b384c7eb0621fc0dc867539ddfd515/7eed1/etf-db.jpg 320w,/static/a1b384c7eb0621fc0dc867539ddfd515/020e1/etf-db.jpg 640w,/static/a1b384c7eb0621fc0dc867539ddfd515/c84ac/etf-db.jpg 1280w" alt="European Training Foundation Database"/></picture><noscript><picture><source type="image/webp" srcSet="/static/a1b384c7eb0621fc0dc867539ddfd515/ddf18/etf-db.webp 160w,/static/a1b384c7eb0621fc0dc867539ddfd515/348bc/etf-db.webp 320w,/static/a1b384c7eb0621fc0dc867539ddfd515/5c62e/etf-db.webp 640w,/static/a1b384c7eb0621fc0dc867539ddfd515/6bef2/etf-db.webp 1280w" sizes="(min-width: 640px) 640px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 640px) 640px, 100vw" decoding="async" loading="lazy" src="/static/a1b384c7eb0621fc0dc867539ddfd515/020e1/etf-db.jpg" srcSet="/static/a1b384c7eb0621fc0dc867539ddfd515/4ea5c/etf-db.jpg 160w,/static/a1b384c7eb0621fc0dc867539ddfd515/7eed1/etf-db.jpg 320w,/static/a1b384c7eb0621fc0dc867539ddfd515/020e1/etf-db.jpg 640w,/static/a1b384c7eb0621fc0dc867539ddfd515/c84ac/etf-db.jpg 1280w" alt="European Training Foundation Database"/></picture></noscript>
39<script type="module">const t="undefined"!=typeof HTMLImageElement&&"loading"in HTMLImageElement.prototype;if(t){const t=document.querySelectorAll("img[data-main-image]");for(let e of t){e.dataset.src&&(e.setAttribute("src",e.dataset.src),e.removeAttribute("data-src")),e.dataset.srcset&&(e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset"));const t=e.parentNode.querySelectorAll("source[data-srcset]");for(let e of t)e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset");e.complete&&(e.style.opacity=1)}}</script>
39</div></div><div class="lg:flex-1"><h4 class="font-bold text-lg">European Training Foundation Database</h4><p class="text-lg w-full py-4 whitespace-pre-line">During my time on Eworx SA, I developed a full-stack web application for the European Training Foundation (ETF). The purpose of the app is to store, organize and manipulate their data, perform validations and verifications on them and build reports for internal or external use.
40
41The user is able to add, edit or delete data from the browser using an excel-like table, create reports based on selected filters and build interactive visualizations such as Pie Charts, Bar Charts and Maps.
42</p><ul class="pr-2"><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">R</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Javascript</li></ul></div></div><div class="border-t-4 border-line relative flex flex-wrap bg-back-light p-4 lg:p-8 bg-no-repeat text-sm mb-6"><div class="flex flex-wrap content-center w-full pb-4 lg:w-2/5 lg:pr-8 lg:pb-0"><div data-gatsby-image-wrapper="" class="gatsby-image-wrapper gatsby-image-wrapper-constrained"><div style="max-width:640px;display:block"><img alt="" role="presentation" aria-hidden="true" src="data:image/svg+xml;charset=utf-8,%3Csvg height=&#x27;429.05027932960894&#x27; width=&#x27;640&#x27; xmlns=&#x27;http://www.w3.org/2000/svg&#x27; version=&#x27;1.1&#x27;%3E%3C/svg%3E" style="max-width:100%;display:block;position:static"/></div><div aria-hidden="true" data-placeholder-image="" style="opacity:1;transition:opacity 500ms linear;background-color:#0868f8;position:absolute;top:0;left:0;bottom:0;right:0"></div><picture><source type="image/webp" data-srcset="/static/01061366ffd20f47364709a4a8990472/e13d2/chill.webp 90w,/static/01061366ffd20f47364709a4a8990472/09e76/chill.webp 179w,/static/01061366ffd20f47364709a4a8990472/ade9f/chill.webp 358w" sizes="(min-width: 358px) 358px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 358px) 358px, 100vw" decoding="async" loading="lazy" data-src="/static/01061366ffd20f47364709a4a8990472/60253/chill.jpg" data-srcset="/static/01061366ffd20f47364709a4a8990472/f6f8e/chill.jpg 90w,/static/01061366ffd20f47364709a4a8990472/a314f/chill.jpg 179w,/static/01061366ffd20f47364709a4a8990472/60253/chill.jpg 358w" alt="Chill- Meet and Movie Date"/></picture><noscript><picture><source type="image/webp" srcSet="/static/01061366ffd20f47364709a4a8990472/e13d2/chill.webp 90w,/static/01061366ffd20f47364709a4a8990472/09e76/chill.webp 179w,/static/01061366ffd20f47364709a4a8990472/ade9f/chill.webp 358w" sizes="(min-width: 358px) 358px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 358px) 358px, 100vw" decoding="async" loading="lazy" src="/static/01061366ffd20f47364709a4a8990472/60253/chill.jpg" srcSet="/static/01061366ffd20f47364709a4a8990472/f6f8e/chill.jpg 90w,/static/01061366ffd20f47364709a4a8990472/a314f/chill.jpg 179w,/static/01061366ffd20f47364709a4a8990472/60253/chill.jpg 358w" alt="Chill- Meet and Movie Date"/></picture></noscript>
42<script type="module">const t="undefined"!=typeof HTMLImageElement&&"loading"in HTMLImageElement.prototype;if(t){const t=document.querySelectorAll("img[data-main-image]");for(let e of t){e.dataset.src&&(e.setAttribute("src",e.dataset.src),e.removeAttribute("data-src")),e.dataset.srcset&&(e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset"));const t=e.parentNode.querySelectorAll("source[data-srcset]");for(let e of t)e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset");e.complete&&(e.style.opacity=1)}}</script>
42</div></div><div class="lg:flex-1"><h4 class="font-bold text-lg">Chill- Meet and Movie Date</h4><p class="text-lg w-full py-4 whitespace-pre-line">Developed and published an Android app with a NoSQL database and a server hosted in Google cloud. The app connects users via common interests in movies and tv shows and it organically grew to more than 500 users within the first two weeks.</p><ul class="pr-2"><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Android</li><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Java</li></ul></div></div><div class="border-t-4 border-line relative flex flex-wrap bg-back-light p-4 lg:p-8 bg-no-repeat text-sm mb-6"><div class="flex flex-wrap content-center w-full pb-4 lg:w-2/5 lg:pr-8 lg:pb-0"><div data-gatsby-image-wrapper="" class="gatsby-image-wrapper gatsby-image-wrapper-constrained"><div style="max-width:640px;display:block"><img alt="" role="presentation" aria-hidden="true" src="data:image/svg+xml;charset=utf-8,%3Csvg height=&#x27;449.06666666666666&#x27; width=&#x27;640&#x27; xmlns=&#x27;http://www.w3.org/2000/svg&#x27; version=&#x27;1.1&#x27;%3E%3C/svg%3E" style="max-width:100%;display:block;position:static"/></div><div aria-hidden="true" data-placeholder-image="" style="opacity:1;transition:opacity 500ms linear;background-color:#e8e8e8;position:absolute;top:0;left:0;bottom:0;right:0"></div><picture><source type="image/webp" data-srcset="/static/88f312b2511fed16feee6e943b43cf15/aec0b/robot_car.webp 150w,/static/88f312b2511fed16feee6e943b43cf15/56e75/robot_car.webp 300w,/static/88f312b2511fed16feee6e943b43cf15/6a95d/robot_car.webp 600w" sizes="(min-width: 600px) 600px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 600px) 600px, 100vw" decoding="async" loading="lazy" data-src="/static/88f312b2511fed16feee6e943b43cf15/68f8d/robot_car.jpg" data-srcset="/static/88f312b2511fed16feee6e943b43cf15/1443d/robot_car.jpg 150w,/static/88f312b2511fed16feee6e943b43cf15/27050/robot_c
42ar.jpg 300w,/static/88f312b2511fed16feee6e943b43cf15/68f8d/robot_car.jpg 600w" alt="Differential Wheeled Robot"/></picture><noscript><picture><source type="image/webp" srcSet="/static/88f312b2511fed16feee6e943b43cf15/aec0b/robot_car.webp 150w,/static/88f312b2511fed16feee6e943b43cf15/56e75/robot_car.webp 300w,/static/88f312b2511fed16feee6e943b43cf15/6a95d/robot_car.webp 600w" sizes="(min-width: 600px) 600px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 600px) 600px, 100vw" decoding="async" loading="lazy" src="/static/88f312b2511fed16feee6e943b43cf15/68f8d/robot_car.jpg" srcSet="/static/88f312b2511fed16feee6e943b43cf15/1443d/robot_car.jpg 150w,/static/88f312b2511fed16feee6e943b43cf15/27050/robot_car.jpg 300w,/static/88f312b2511fed16feee6e943b43cf15/68f8d/robot_car.jpg 600w" alt="Differential Wheeled Robot"/></picture></noscript>
42<script type="module">const t="undefined"!=typeof HTMLImageElement&&"loading"in HTMLImageElement.prototype;if(t){const t=document.querySelectorAll("img[data-main-image]");for(let e of t){e.dataset.src&&(e.setAttribute("src",e.dataset.src),e.removeAttribute("data-src")),e.dataset.srcset&&(e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset"));const t=e.parentNode.querySelectorAll("source[data-srcset]");for(let e of t)e.setAttribute("srcset",e.dataset.srcset),e.removeAttribute("data-srcset");e.complete&&(e.style.opacity=1)}}</script>
42</div></div><div class="lg:flex-1"><h4 class="font-bold text-lg">Differential Wheeled Robot</h4><a class="text-lg text-front underline break-all hover:opacity-75 transition-opacity duration-150" href="https://github.com/SergiosKar/-Robotic-vehicle" rel="noreferrer noopener" target="_blank">https://github.com/SergiosKar/-Robotic-vehicle</a><p class="text-lg w-full py-4 whitespace-pre-line">Programmed an embedded board for a 2 wheeled robot. he robot is able to move to straight line, follow a certain path,such as a trinagle or a circle , detect and avoid obstacles with supersonic sensor.</p><ul class="pr-2"><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Embedded programming</li></ul><span class="absolute right-0 bottom-0 mb-5 mr-5 text-back"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" class="w-6 h-6" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></span></div></div><div class="border-t-4 border-line relative flex flex-wrap bg-back-light p-4 lg:p-8 bg-no-repeat text-sm mb-6"><div class="flex flex-wrap content-center w-full pb-4 lg:w-2/5 lg:pr-8 lg:pb-0"><div data-gatsby-image-wrapper="" class="gatsby-image-wrapper gatsby-image-wrapper-constrained"><div style="max-width:640px;display:block"><img alt="" role="presentation" aria-hidden="true" src="data:image/svg+xml;charset=utf-8,%3Csvg height=&#x27;360&#x27; width=&#x27;640&#x27; xmlns=&#x27;http://www.w3.org/2000/svg&#x27; version=&#x27;1.1&#x27;%3E%3C/svg%3E" style="max-width:100%;display:block;position:static"/></div><div aria-hidden="true" data-placeholder-image="" style="opacity:1;transition:opacity 500ms linear;background-color:#484848;position:absolute;top:0;left:0;bottom:0;right:0"></div><picture><source type="image/webp" data-srcset="/static/7edce12de9cb6843d484668e69f8f128/94784/robot_motion_planning.webp 160w,/static/7edce12de9cb6843d484668e69f8f128/c064d/robot_motion_planning.webp 320w,/static/7edce12de9cb6843d484668e69f8f128/2af6d/robot_motion_planning.webp 640w,/static/7edce12de9cb6843d484668e69f8f128/23e38/robot_motion_planning.webp 1280w" sizes="(min-width: 640px) 640px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 640px) 640px, 100vw" decoding="async" loading="lazy" data-src="/static/7edce12de9cb6843d484668e69f8f128/27816/robot_motion_planning.png" data-srcset="/static/7edce12de9cb6843d484668e69f8f128/9ec47/robot_motion_planning.png 160w,/static/7edce12de9cb6843d484668e69f8f128/26aac/robot_motion_planning.png 320w,/static/7edce12de9cb6843d484668e69f8f128/27816/robot_motion_planning.png 640w,/static/7edce12de9cb6843d484668e69f8f128/ca004/robot_motion_planning.png 1280w" alt="Robot motion plainning"/></picture><noscript><picture>
42<source type="image/webp" srcSet="/static/7edce12de9cb6843d484668e69f8f128/94784/robot_motion_planning.webp 160w,/static/7edce12de9cb6843d484668e69f8f128/c064d/robot_motion_planning.webp 320w,/static/7edce12de9cb6843d484668e69f8f128/2af6d/robot_motion_planning.webp 640w,/static/7edce12de9cb6843d484668e69f8f128/23e38/robot_motion_planning.webp 1280w" sizes="(min-width: 640px) 640px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 640px) 640px, 100vw" decoding="async" loading="lazy" src="/static/7edce12de9cb6843d484668e69f8f128/27816/robot_motion_planning.png" srcSet="/static/7edce12de9cb6843d484668e69f8f128/9ec47/robot_motion_planning.png 160w,/static/7edce12de9cb6843d484668e69f8f128/26aac/robot_motion_planning.png 320w,/static/7edce12de9cb6843d484668e69f8f128/27816/robot_motion_planning.png 640w,/static/7edce12de9cb6843d484668e69f8f128/ca004/robot_motion_planning.png 1280w" alt="Robot motion plainning"/></picture></noscript>
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42</div></div><div class="lg:flex-1"><h4 class="font-bold text-lg">Robot motion plainning</h4><p class="text-lg w-full py-4 whitespace-pre-line">Designed a system for robot navigation on 2D space with C++ and computational geometry techniques, such as voronoi diagrams and visibility graphs.</p><ul class="pr-2"><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Robotics</li></ul><span class="absolute right-0 bottom-0 mb-5 mr-5 text-back"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" class="w-6 h-6" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></span></div></div><div class="border-t-4 border-line relative flex flex-wrap bg-back-light p-4 lg:p-8 bg-no-repeat text-sm mb-6"><div class="flex flex-wrap content-center w-full pb-4 lg:w-2/5 lg:pr-8 lg:pb-0"><div data-gatsby-image-wrapper="" class="gatsby-image-wrapper gatsby-image-wrapper-constrained"><div style="max-width:640px;display:block"><img alt="" role="presentation" aria-hidden="true" src="data:image/svg+xml;charset=utf-8,%3Csvg height=&#x27;538.7906976744187&#x27; width=&#x27;640&#x27; xmlns=&#x27;http://www.w3.org/2000/svg&#x27; version=&#x27;1.1&#x27;%3E%3C/svg%3E" style="max-width:100%;display:block;position:static"/></div><div aria-hidden="true" data-placeholder-image="" style="opacity:1;transition:opacity 500ms linear;background-color:#e8e8e8;position:absolute;top:0;left:0;bottom:0;right:0"></div><picture><source type="image/webp" data-srcset="/static/bdeee59f1f86115c40bf93df7fa05416/48f53/robotic_arm.webp 108w,/static/bdeee59f1f86115c40bf93df7fa05416/6f1a0/robotic_arm.webp 215w,/static/bdeee59f1f86115c40bf93df7fa05416/8414b/robotic_arm.webp 430w" sizes="(min-width: 430px) 430px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 430px) 430px, 100vw" decoding="async" loading="lazy" data-src="/static/bdeee59f1f86115c40bf93df7fa05416/0ff1a/robotic_arm.png" data-srcset="/static/bdeee59f1f86115c40bf93df7fa05416/72ec8/robotic_arm.png 108w,/static/bdeee59f1f86115c40bf93df7fa05416/b08f4/robotic_arm.png 215w,/static/bdeee59f1f86115c40bf93df7fa05416/0ff1a/robotic_arm.png 430w" alt="Simulation of Robotic Arm"/></picture><noscript><picture><source type="image/webp" srcSet="/static/bdeee59f1f86115c40bf93df7fa05416/48f53/robotic_arm.webp 108w,/static/bdeee59f1f86115c40bf93df7fa05416/6f1a0/robotic_arm.webp 215w,/static/bdeee59f1f86115c40bf93df7fa05416/8414b/robotic_arm.webp 430w" sizes="(min-width: 430px) 430px, 100vw"/><img data-gatsby-image-ssr="" data-main-image="" style="opacity:0" sizes="(min-width: 430px) 430px, 100vw" decoding="async" loading="lazy" src="/static/bdeee59f1f86115c40bf93df7fa05416/0ff1a/robotic_arm.png" srcSet="/static/bdeee59f1f86115c40bf93df7fa05416/72ec8/robotic_arm.png 108w,/static/bdeee59f1f86115c40bf93df7fa05416/b
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42</div></div><div class="lg:flex-1"><h4 class="font-bold text-lg">Simulation of Robotic Arm</h4><a class="text-lg text-front underline break-all hover:opacity-75 transition-opacity duration-150" href="https://github.com/SergiosKar/Robotic-Arm" rel="noreferrer noopener" target="_blank">https://github.com/SergiosKar/Robotic-Arm</a><p class="text-lg w-full py-4 whitespace-pre-line">Study of Kinematics, Dynamics, Position, Control and Simulation of robotic arm with MATLAB robotic toolbox</p><ul class="pr-2"><li class="inline-block px-3 py-1 mr-1 mt-1 font-medium text-sm rounded-lg border border-back">Robotics</li></ul><span class="absolute right-0 bottom-0 mb-5 mr-5 text-back"><svg stroke="currentColor" fill="currentColor" stroke-width="0" viewBox="0 0 496 512" class="w-6 h-6" height="1em" width="1em" xmlns="http://www.w3.org/2000/svg"><path d="M165.9 397.4c0 2-2.3 3.6-5.2 3.6-3.3.3-5.6-1.3-5.6-3.6 0-2 2.3-3.6 5.2-3.6 3-.3 5.6 1.3 5.6 3.6zm-31.1-4.5c-.7 2 1.3 4.3 4.3 4.9 2.6 1 5.6 0 6.2-2s-1.3-4.3-4.3-5.2c-2.6-.7-5.5.3-6.2 2.3zm44.2-1.7c-2.9.7-4.9 2.6-4.6 4.9.3 2 2.9 3.3 5.9 2.6 2.9-.7 4.9-2.6 4.6-4.6-.3-1.9-3-3.2-5.9-2.9zM244.8 8C106.1 8 0 113.3 0 252c0 110.9 69.8 205.8 169.5 239.2 12.8 2.3 17.3-5.6 17.3-12.1 0-6.2-.3-40.4-.3-61.4 0 0-70 15-84.7-29.8 0 0-11.4-29.1-27.8-36.6 0 0-22.9-15.7 1.6-15.4 0 0 24.9 2 38.6 25.8 21.9 38.6 58.6 27.5 72.9 20.9 2.3-16 8.8-27.1 16-33.7-55.9-6.2-112.3-14.3-112.3-110.5 0-27.5 7.6-41.3 23.6-58.9-2.6-6.5-11.1-33.3 2.6-67.9 20.9-6.5 69 27 69 27 20-5.6 41.5-8.5 62.8-8.5s42.8 2.9 62.8 8.5c0 0 48.1-33.6 69-27 13.7 34.7 5.2 61.4 2.6 67.9 16 17.7 25.8 31.5 25.8 58.9 0 96.5-58.9 104.2-114.8 110.5 9.2 7.9 17 22.9 17 46.4 0 33.7-.3 75.4-.3 83.6 0 6.5 4.6 14.4 17.3 12.1C428.2 457.8 496 362.9 496 252 496 113.3 383.5 8 244.8 8zM97.2 352.9c-1.3 1-1 3.3.7 5.2 1.6 1.6 3.9 2.3 5.2 1 1.3-1 1-3.3-.7-5.2-1.6-1.6-3.9-2.3-5.2-1zm-10.8-8.1c-.7 1.3.3 2.9 2.3 3.9 1.6 1 3.6.7 4.3-.7.7-1.3-.3-2.9-2.3-3.9-2-.6-3.6-.3-4.3.7zm32.4 35.6c-1.6 1.3-1 4.3 1.3 6.2 2.3 2.3 5.2 2.6 6.5 1 1.3-1.3.7-4.3-1.3-6.2-2.2-2.3-5.2-2.6-6.5-1zm-11.4-14.7c-1.6 1-1.6 3.6 0 5.9 1.6 2.3 4.3 3.3 5.6 2.3 1.6-1.3 1.6-3.9 0-6.2-1.4-2.3-4-3.3-5.6-2z"></path></svg></span></div></div></main></div><footer class="bg-front mt-16 pt-8 pb-16"><div class="md:max-w-screen-sm lg:max-w-screen-xl mx-auto px-4 flex items-center"><div class="w-2/3 text-back-light font-header text-base"><b>© <!-- -->2021<!-- --> <!-- -->Sergios Karagiannakos<!-- -->.</b> <!-- -->All rights reserved.</div><div class="w-1/3 text-right"></div></div></footer></div></div><div id="gatsby-announcer" style="position:absolute;top:0;width:1px;height:1px;padding:0;overflow:hidden;clip:rect(0, 0, 0, 0);white-space:nowrap;border:0" aria-live="assertive" aria-atomic="true"></div></div>
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