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Siddarth T

Siddarth T

AI/ML Engineer · Computer Vision & Applied Machine Learning

Palani, Tamil Nadu, India

@siddarth_t

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About

Recent B.Tech graduate in Artificial Intelligence and Machine Learning with hands-on experience building and deploying end-to-end ML systems. Specializes in computer vision, semantic search, and NLP, with a government-recognized funded project and production deployments.

Education

  • B.Tech
    M. Kumarasamy College of Engineering
    Artificial Intelligence and Machine Learning · Aug 2022 – May 2026
  • Higher Secondary
    Bharatiya Vidya Bhavan MHSS
    Computer Science · Jun 2021 – May 2022

Skills

<3 months <3 months Just getting started - under three months. This is also what shows when a level has not been set.
SQL CSS HTML Java Yolo React Flask Python OpenCV Node.js TensorFlow scikit-learn Computer Vision Machine Learning Natural Language Processing API Integration Understanding

Tools / apps / platforms

<3 months <3 months Just getting started - under three months. This is also what shows when a level has not been set.
Git MySQL MongoDB

Languages

Not stated Not stated No level given for this one.
Tamil Speak English Speak Japanese Speak

Projects

  • TruthLens — AI News Analyzer ↗
    TF-IDF, Logistic Regression, Flask, HTML, CSS, JavaScript, Gunicorn

    Trained a text classification model to detect fake news patterns and integrated NewsAPI for live news search and analysis. Built and deployed a full-stack application with confidence-based predictions.

  • ResearchAI — AI-Powered Research Paper Discovery ↗
    scikit-learn, NumPy, Python, Flask, Gunicorn

    Built a semantic search and ranking engine to score and cluster academic papers by topic relevance. Integrated arXiv and OpenAlex APIs for live paper metadata and deployed the backend to production.

  • Smart Bin — AI-Powered Waste Management System
    YOLO, OpenCV

    Built a real-time waste classification system using a YOLO-based detection model and OpenCV for live video inference. Trained and fine-tuned the model on a custom-labeled waste dataset; handled preprocessing, labeling, and augmentation. Selected for MSME Idea Hackathon 4.0 and awarded ₹8 Lakhs in funding.

📚 Publications

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