AI x Systems x Vision | ECE undergrad building RAG chatbots, agentic LangGraph workflows, and safety-focused computer vision systems | 400+ LeetCode
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Demo_Fullstack_Project
April 18, 2026 – Present
Demo_Fullstack_Project — GitHub repository
View ProjectRegression_ML_EndtoEnd
December 6, 2025 – Present
End-to-end ML pipeline for housing price prediction with XGBoost, deployed on Google Cloud Run with Supabase integration. Features REST API, Streamlit dashboard, MLflow experiment tracking, and comprehensive testing.
View ProjectREST_microservice
December 2, 2025 – December 9, 2025
Production-ready REST microservice for customer and order management with MongoDB, Docker, CI/CD, and comprehensive testing
View ProjectRAG_TEACHER
September 19, 2025 – October 11, 2025
AI-powered teaching assistant using RAG (Retrieval-Augmented Generation) with FastAPI backend and Streamlit frontend
View ProjectAI_TRIPPLANNER
July 7, 2025 – July 24, 2025
🧳 An agentic AI travel assistant built using LangGraph and LangChain. It helps users plan personalized itineraries while tracking expenses — built for smart explorers!
View ProjectFish-Detection-YOLOv8
March 4, 2025 – Present
Welcome to the Fish-Detection-YOLOv8 repository! This project focuses on detecting fish species using the YOLOv8 object detection algorithm. It aims to provide accurate and efficient fish detection models for applications such as marine biology research and automated fishing systems.
View Projectphishing-detection
February 15, 2025 – February 15, 2025
📧 Detects phishing emails using machine learning models trained on real-world datasets. Includes data preprocessing, feature engineering, and classification techniques.
View ProjectLeetCode_Hope
January 6, 2025 – October 12, 2025
Welcome to LeetCode_Hope! This repository is dedicated to providing solutions to various LeetCode problems. Whether you're preparing for coding interviews, enhancing your problem-solving skills, or exploring different algorithms, this repository serves as a valuable resource.
View ProjectCultural Fit Analysis
The candidate's project portfolio indicates a strong interest and self-driven learning in AI/ML, which aligns well with an 'AI Systems' role. The diversity of personal projects (computer vision, NLP, MLOps, full-stack AI applications) suggests a proactive and curious individual. However, the lack of team-based projects or professional experience makes it difficult to assess collaboration and broader cultural fit.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.