Harshith Sheggam

Harshith SheggamProjectsPosts

About


Hey there, my self 👨‍💻 Harshith Sheggam a full stack developer who codes with the precision of a master chef 👨‍🍳 and cooks with the creativity of a seasoned coder. While I craft impeccable code sandwiches by day, I'm simmering up delightful dishes in my coding kitchen by night. Think of me as the HTML-haute-cuisine aficionado and Python pastry chef rolled into one! Just like in cooking, debugging code requires the perfect blend of flavors – a dash of patience, a pinch of creativity, and a sprinkle of problem-solving skills. When I'm not debugging, you'll find me decoding recipes as meticulously as I decode bugs in my code. So, let's embark on this delightful journey of mixing and merging tech and taste! Bon appétit 🍽️ and happy coding! ✨

💼 Experience


💻 Specializes in full-stack development, proficient in both frontend and backend technologies, with over 4+ years of hands-on experience in Startup and MNC.

🏆 At FairShares, Developed FairShares tax-saving web app from scratch. Worked on scaling user @ 1000RPS, Led a team of 5, enhanced security measures, optimized system architecture and integrate 3rd party API's such as plaid, stripe.

💲🏛️ At American Express, I upgraded their internal django app from single-tenant to multi-tenant in just 2 months. I also helped scale various in-house projects using Django.Worked on there Ldap servers. Helps them moving away from tradtional elasticsearch to Postgresql full text search.

🌐💻🛠️ At Mutual Mobile, I've spearheaded fintech web app creation and upkeep with Django, Python's framework. AWS, managed through Elastic Beanstalk, handled server tasks, scaling, and deployment. We fortified security with AWS WAF. On the frontend, I've delved into MVT, using vanilla JS and jQuery. Collaborating via agile tools like Git, Jira, and Slack, I've engaged with teams. My growth? Constant: learning via code reviews, courses, and mentorship!

👨‍💼 At Aptagrim, I collaborated closely with the dev team to create efficient backend solutions, ensuring top-notch app performance. 🛠️ I actively tackled debugging and troubleshooting, maintaining reliability. Integrating third-party APIs was key in boosting app features.I aimed for innovative server-side improvements. 📚 Also, I documented our backend thoroughly for easy team reference using MKdocs. 📝

Projects


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Identifing Industrial TMT Rods

TMT(Thermo Mechanical treatment) rods are the walloping production of the steel industries and they require tailor-made measurements for each construction site. for that there are huge machines that will make the task of cutting TMT rods easier for industries. while cutting the rods they measure for efficient cutting for that they use a photoelectric sensor, Manual labor, and complex computing machine that ended up in huge maintenance of the machines and time-consuming process, in the last decade research on Digital image processing and computer vision has seen much progress. I developed a methodology that is adaptable for the industries in measuring TMT rods much more efficiently , robust towards cram-full of rods, and minimizing the error rate. The captured digital image first undergoes the preprocessing phase where the first step is image enhancement and then edge detection, which extracts the TMT rods edges then followed by the diameter calculations (pixels per metric). An experiment was conducted on a variety of challenging conditions to demonstrate the capability of our approach to a good measure of success This concept gives me optimism for the future of AI (Computer Vision) in construction equipment and materials. The challenges became even greater when it came to the production level, as construction sites were littered with sawdust, which caused a lot of noise in the image and made our job even more difficult in the preprocessing stage. Another issue was the lack of a bright light, which we needed to capture the image. A right contrast of light is required while capturing the image that will help us in identifying the edges of the rod this was later rectified through a contrast library mdoule

📚 Publications


Industrial Rod Size Diameter and Size Detection Using OpenCV Computer Vision

Thermo-mechanical treatment (TMT) rods are the walloping production of the steel industries, and there are giant machines that will make the task of cutting TMT rods easier for industries. While cutting the rods, photoelectric sensor, manual labor, and complex computing machine are used that need huge maintenance of the machine, and it is a time-consuming process. In the last decade, research on digital image processing and computer vision has seen much progress. In this paper, we propose an adaptable methodology for the industries in measuring the TMT rods much more efficiently, maximizing the efficiency, robust toward cram-full of rods and minimizing the error rate. The captured digital image first undergoes the preprocessing phase, where the first step is image enhancement and then edge detection, which extracts the TMT rods edges then followed by the diameter calculations (pixels per metric). An experiment has been conducted with various challenging conditions to demonstrate the capability of our approach to a good measure of success.

🎓 Education


🎓 Master's in Computer Science @ College of Staten Island.
🎓 Bachelor's in Computer Science @ Sreyas Institute of Engineering and Technology.

🌐 Contact Me


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