Applied AI Engineer • Computer Vision • Production AI Systems

Building end-to-end AI applications with focus on Computer Vision, real-time inference,
scalable backends, and production deployment. Passionate about turning ML research into real-world solutions.

I'm an Applied AI Engineer specializing in Computer Vision and production-grade AI systems. My passion lies in transforming machine learning models into scalable, deployable applications that solve real-world problems.

What I do:

• 🔍 Real-time Object Detection & Video Analytics — Building intelligent vision systems using YOLO, OpenCV, and deep learning
• 🚀 AI-powered Backends & Inference Pipelines — Designing scalable APIs with FastAPI, Docker, and cloud infrastructure
• 🌾 Domain-Specific Solutions — Practical AI applications for Agriculture, Healthcare, and Automation
• ⚙️ MLOps & Deployment — Model serving, containerization, CI/CD pipelines, and edge deployment
• 📊 End-to-End AI Projects — From data collection to production deployment

My mindset:

• Code for production, not just notebooks
• Scalability and reliability first
• Continuous learning and iteration
• Open-source contributor

AI & Machine Learning

Backend & Deployment

Frontend & Visualization

Production-ready Object Detection API using YOLOv8 + FastAPI. Returns detailed JSON with bounding boxes, confidence scores, and class predictions. Deployed with auto-scaling.

• Tech: YOLOv8, FastAPI, OpenCV, Python, Docker
• 🔗 Repository

Smart Student Attendance System — Real-time person detection and tracking using YOLOv8 + Flask + Docker. Counts students, tracks presence, and exports reports.

• Tech: YOLOv8, FastAPI/Flask, Docker, OpenCV, PostgreSQL
• 🔗 Repository

AI-powered Skin Disease Classification model with 82% accuracy using MobileNetV2. Deployed with Streamlit for real-time predictions.

• Tech: TensorFlow, MobileNetV2, Streamlit, OpenCV, Transfer Learning
• 🔗 Repository

Multilingual AI Dashboard for Indian Farmers — Crop health monitoring using Computer Vision & NDVI concepts. Provides actionable insights for crop management.

• Tech: Computer Vision, NDVI Analysis, AI Analytics, Python
• 🔗 Repository

Freemium AI SaaS Toolkit for creators — Text generation, resume builder, content tools, and more powered by OpenAI & Hugging Face.

• Tech: Python, OpenAI API, Hugging Face, Streamlit, Firebase
• 🔗 Repository

Modern Next.js website for IGC Forum NGO — Responsive design, SEO-optimized, smooth animations with Framer Motion.

• Tech: Next.js 16, TypeScript, Tailwind CSS, Framer Motion
• 🔗 Repository

• 📈 Advanced MLOps — Experiment tracking, model versioning, automated testing
• ⚡ Real-time Inference Optimization — Quantization, pruning, edge deployment
• 👁️ Vision Transformers & Foundation Models — Exploring latest SOTA vision models
• 🏗️ Scalable AI Architecture — Microservices, event-driven systems, distributed computing

• 🎓 Google Generative AI Certification
• 🤖 Accenture AI/ML Workflow
• 📚 Edureka AI/ML Internship
• 🚀 ISRO Hackathon 2025 — Selected Participant
• 🔐 Tata Cybersecurity Simulation
• 💼 Goldman Sachs Engineering Simulation

I occasionally write about AI, ML engineering, and computer vision on:

• Medium (coming soon)
• Dev.to (coming soon)

I'm always interested in collaborating on innovative AI projects, open-source contributions, or discussing the latest in computer vision and ML engineering.

💻 Passionate about building AI systems that create real-world impact.
🚀 Always learning, always shipping.