Bani J.
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Bani J. is a Software Engineer — Full Stack Developer with hands-on experience designing and deploying production-grade applications in the e-commerce, automotive, AI developer tools, and computer vision research domains. At the College of Engineering Kottarakkara, Bani engineered a scalable e-commerce platform for a family automotive business, leveraging FastAPI, Next.js, and PostgreSQL to deliver intelligent product filtering and automated inventory management that dramatically reduced operational overhead. Bani’s AI-powered projects include building an offline debugging coach for Python and creating an object detection system for real-time roadside litter identification utilizing PyTorch and YOLOv8, with research published in IJERT. As Chief Technical Lead at IEDC, Bani has led technical workshops and mentored teams in full-stack development and deployment best practices.
Experience
Chief Technical Lead
Innovation and Entrepreneurship Development Cell (IEDC) College of Engineering Kottarakkara · 2023 — PresentConducted technical workshops covering web development, cloud computing, and machine learning for over 200 students. Supervised the technical team during college hackathons and innovation challenges. Provided mentorship to more than 15 student teams on full-stack development and deployment practices.Software Engineer — Full Stack Developer
nullDeveloped an automotive parts e-commerce platform managing 1,000+ SKUs with vehicle compatibility filtering. Created a PostgreSQL database schema optimized for product-vehicle relationships, resulting in sub-200ms query response times. Built intelligent search features that enable customers to filter parts by vehicle make/model/year, reducing incorrect orders. Integrated Stripe for payment processing and automated inventory management, significantly decreasing manual order processing time. Architected a REST API using FastAPI and designed a responsive frontend with Next.js, deployed through Docker containers.Debugging Coach - AI Code Assistant
nullEngineered an offline debugging platform to analyze Python runtime errors through AST parsing and custom pattern recognition. Developed a hint generation system that offers structured guidance for common error types to aid beginner programmers. Established a secure sandbox execution environment with timeout handling and resource limitations for code analysis. Created interactive visualizations using React and D3.js for call stacks and execution flows.Civic Cam - AI Litter Detection System
nullTrained a YOLOv8 object detection model on a custom dataset to detect roadside litter with 87% accuracy. Executed an end-to-end machine learning pipeline, which included data augmentation and model fine-tuning. Integrated PaddleOCR for license plate recognition and Haarcascade for face detection to identify offenders. Authored a research paper in IJERT detailing the methodology and findings.
Skills & Expertise
Education
- Bachelor of Technology - Computer Science and EngineeringCollege of Engineering Kottarakkara · 2022 — 2026
- Plus Two - Computer ScienceSt Thomas College HSS · 2021 — 2022
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