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@sarandhayalan
AI/ML engineer focused on scalable machine learning and data-driven solutions.
I am a recent MTech graduate in Computer Science and Engineering with a strong foundation in AI/ML, data analysis, and visualization. I design and implement scalable ML and deep learning solutions, blending practical engineering with strong mathematical problem-solving.
I built real-time systems using LSTM and YOLO variants, including a sign-language-to-text pipeline and a tomato leaf disease detector, demonstrating hands-on experience in computer vision and model fusion.
I also create interactive data visualizations and dashboards using Power BI and Tableau, and I am familiar with cloud platforms like Microsoft Azure and engineering tools such as Git and VS Code.
I am passionate about applying AI to real-world problems, delivering measurable impact through robust, production-ready models and clear, actionable data insights.
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Work history, roles, and key accomplishments
Vellore Institute of Technology
Sep 2020 - Present (5 years 2 months)
Pursuing integrated MTech in Computer Science and Engineering with coursework and projects in AI/ML, data analysis, and visualization; maintained CGPA 7.91/10 while delivering multiple applied ML projects and conference presentation.
Self Employed
Designed and implemented ML/DL solutions including real-time sign language-to-text and tomato leaf disease detection systems, achieving up to 98.99% detection accuracy and enabling real-time inference for accessibility and agriculture use cases.
Degrees, certifications, and relevant coursework
MTech Integrated, Computer Science and Engineering
2020 - 2025
Grade: 7.91/10.00
Activities and societies: Projects in real-time sign language recognition, tomato leaf disease detection, and Power BI sales analysis; certifications in Google Data Analytics and Azure AI Fundamentals; winner of 2019 All India National Handball Championship.
Integrated MTech in Computer Science and Engineering with coursework and projects focused on AI/ML, deep learning, and data visualization, completed with a CGPA of 7.91/10.00.
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