AI x Systems x Vision • ECE undergrad • RAG & Agentic AI • Safety-focused Computer Vision • 400+ LeetCode

• 🎓 ECE undergrad from Chennai, exploring the intersection of AI, systems, and computer vision.
• 🧠 Building RAG chatbots, agentic LangGraph workflows, and YOLOv8-based safety & detection systems.
• 🛠️ Love stitching together backend systems (FastAPI, microservices) with ML pipelines and real-world sensors (ESP32-CAM, cameras).
• 💡 Enjoy research-style, debug-heavy work: optimizing pipelines, latency, and reliability end-to-end.

• 🧩 Designing agentic RAG workflows with LangGraph + LangChain for more “thinking” chatbots.
• 📚 Diving into multi-index vector DBs, OpenCV tracking, and AI safety for camera systems.
• 🧮 Grinding LeetCode (400+ problems) to sharpen data structures, algorithms, and problem-solving.
• 🎯 Long-term goal: become a next-gen AI + Hardware generalist who can move from RTL to RAG in one day.

An agentic AI travel assistant using LangGraph + LangChain that builds personalized itineraries and tracks expenses for travelers.

• 🧠 Uses tools & agents for planning, budgeting, and recommendation flows.
• 🧵 Built to feel like chatting with a smart “trip engineer,” not a static form.

🔗 Repo: AI_TRIPPLANNER

An AI-powered teaching assistant using Retrieval-Augmented Generation with a FastAPI backend and Streamlit frontend.

• 📚 Ingests documents and answers questions grounded in the user’s content.
• 🧱 Great demo of production-style RAG: ingestion, chunking, embeddings, and query-time retrieval.

🔗 Repo: RAG_TEACHER

A phishing email detector using ML models trained on real-world datasets.

• 🧼 Includes data preprocessing, feature engineering, and classification pipelines.
• 🔐 Focused on practical defensive ML for real security workflows.

🔗 Repo: phishing-detection

A YOLOv8-based fish detection system for identifying fish species from images and video.

• 🎯 Trained and tuned for accurate detection in noisy, real-world conditions.
• 🧪 Includes dataset handling, training scripts, and inference workflows.

🔗 Repo: Fish-Detection-YOLOv8

A production-style REST microservice for customer & order management.

• 🧱 Tech: Python, MongoDB, Docker, CI/CD, and comprehensive testing.
• ⚙️ Shows backend engineering skills: clean architecture, containerization, and deploy-ready design.

🔗 Repo: REST_microservice

A growing collection of LeetCode solutions and patterns in Java.

• 🧠 Focus on clarity, patterns, and interview-style reasoning.
• 📈 Tracks progress toward strong fundamentals in DSA.

🔗 Repo: LeetCode_Hope

• 🤖 AI / ML: RAG, LangChain, LangGraph, YOLOv8, classical ML (classification, detection).
• 🧩 Backend: Python, FastAPI, REST microservices, MongoDB, Docker, CI/CD pipelines.
• 🎛️ Systems / Hardware: ESP32-CAM, computer vision systems, safety-focused camera workflows.
• 📈 Problem Solving: 400+ LeetCode and ongoing competitive programming practice.

• 🌐 Portfolio: vinay0905.github.io/newportfolio
• 💼 LinkedIn: in/naga-vinay-0905nva1915
• 📧 Email: nagavinay0905@gmail.com
• 📍 Chennai, Tamil Nadu, India

“Trying Best” — one more commit, one more experiment, one more iteration.