Hi, I'm Udit Shetty.
Aspiring AI/ML Engineer & Information Science Student.
Aspiring AI/ML Engineer with hands-on expertise in Machine Learning, Deep Learning, and Natural Language Processing (NLP), Computer Vision, Python backend development, and cloud deployment. Proficient in Python and experienced in developing data-driven, AI-powered applications using industry-standard machine learning frameworks. Passionate about developing scalable AI solutions that solve real-world problems.
I enjoy turning creative ideas into scalable, intuitive AI and web applications. As an Information Science and Engineering student, I combine academic problem-solving with hands-on full-stack and AI engineering to build practical, user-centric software. Alongside core Machine Learning, Deep Learning, and NLP, I actively explore Computer Vision pipelines, FastAPI backend architectures, and cloud deployments to stay at the forefront of modern tech innovation. I believe in learning by building real projects and constantly challenging myself with new technologies.
Technologies & Tools I Work With
Education
AJ Institute of Engineering and Technology, Mangalore
St. Aloysius Pre-University College, Mangalore
Plan2Scene AI
GitHub- Developed an AI-powered system that converts 2D floor plans into interactive 3D building models using a YOLOv11-based detection pipeline.
- Designed a reconstruction pipeline for wall graph generation, room extraction, door/window placement, mesh generation, and GLB export for interactive 3D visualization.
Face Recognition Attendance System
GitHub- Built an AI-powered desktop attendance system using MediaPipe for real-time face detection and FaceNet to generate 512-dimensional facial embeddings.
- Implemented cosine similarity-based face recognition with threshold-based unknown face detection and automated attendance logging using SQLite.
AI Government Scheme Navigator
GitHub- Developed an AI-powered government scheme recommendation platform using FastAPI and PostgreSQL to match users with eligible welfare schemes and Designed REST APIs and implemented rule-based eligibility evaluation with AI-generated explanations.
- Deployed the application on AWS EC2, RDS, S3, CloudFront, Nginx, and Gunicorn, ensuring scalable and reliable backend services.
ET GenAI Hackathon
Developed an AI-powered Government Scheme Navigator that recommends welfare schemes using Python, FastAPI, PostgreSQL, and AWS deployment.
Quantium Software Engineering Virtual Experience
Completed practical tasks including data preprocessing, building an interactive Dash analytics dashboard, implementing automated testing using PyTest, and CI-style test automation.
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