Transforming Ideas Into Reality

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Abhi Bhardwaj

Building intelligent solutions with code—from AI-powered applications to full-stack systems.

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About Me

I'm a Software Engineer and Machine Learning enthusiast pursuing my Master's in Computer Science at George Washington University. With a strong foundation in Algorithms, System Design, and AI/ML, I'm passionate about building intelligent software solutions that solve real-world problems.

My technical journey spans full-stack development, machine learning systems, and MLOps. I've built production-grade fraud detection models with 96%+ precision, developed scalable e-commerce platforms handling 1000+ concurrent users, and created AI-powered financial analytics tools. From training neural networks to architecting cloud-based microservices, I focus on writing clean, efficient code that scales and delivers measurable impact.

Featured Projects

🔮 Flagship Project

Lumina AI

Visual Commerce Engine

Solving the $500B visual search problem in e-commerce. AI-powered engine that understands fashion through computer vision — zero-shot object detection, style & vibe analysis, and semantic search with two-stage retrieval and cross-encoder reranking. Production-grade with CI/CD, Redis caching, and hybrid search filters.

OWLv2 CLIP Qdrant FastAPI Next.js 15 Redis Docker
7+ AI Models
Live HF Spaces
2-Stage Retrieval
Full Docker Stack
✦ Zero-shot fashion detection (OWLv2)
✦ Style & vibe analysis (CLIP)
✦ Cross-encoder reranking pipeline
✦ Hybrid search: vector + structured filters
✦ Live on Hugging Face Spaces
Featured

FraudGuard - MLOps Fraud Detection

Python XGBoost MLOps MLflow FastAPI

Enterprise-grade fraud detection system achieving 96.2% precision using XGBoost and LightGBM. Complete MLOps pipeline with MLflow tracking, CI/CD deployment, real-time drift detection, and FastAPI microservice with <50ms latency. Delivers $2.4M annual savings through 40% reduction in false positives.

Featured

TicketBlitz - High-Concurrency Booking System

Node.js Kafka Redis WebSockets React

Live Production System deployed on Vercel & Render. Features a Real-Time Engineering Visualizer exposing Redis distributed locks, atomic PostgreSQL transactions, and Kafka event streaming. Engineered to handle 10k+ concurrent requests with zero race conditions.

Featured

SentiStock Analytics

Python NLP Streamlit TextBlob

AI-powered stock analysis platform integrating real-time market data with NLP sentiment analysis. Processes 100+ financial news articles per minute, achieving 75-80% correlation to price movements. Interactive Streamlit dashboard with <2s data fetch times across 10,000+ stock tickers.

Featured

UrbanKart - E-Commerce Platform

React TypeScript FastAPI MySQL Vite

Scalable full-stack e-commerce platform supporting 1000+ concurrent users with <100ms API response time. Features JWT authentication, role-based access control, MySQL triggers for inventory automation, and type-safe React frontend with Vite optimization achieving <2s load time.

MoodTunes

Python AI/ML Recommendation System

Emotion-aware music recommendation system that analyzes user emotions and preferences to curate personalized playlists. Uses machine learning to understand mood patterns and suggest songs that match your vibe.

Featured

PadhAI Dost v2.0

Next.js 14 RAG Pipeline GenAI EdTech

AI-Powered Study Support System. Transforms static PDFs into interactive conversations and auto-generated flashcards using retrieval-augmented generation. Features intelligent context-aware chat, hybrid search, and real-time learning metrics.

Featured

WeatherNow - AI Weather Intelligence

Python PyTorch FastAPI Streamlit LSTM

AI-Powered Weather Platform combining real-time data with LSTM neural networks for next-day temperature prediction. Features GPS geolocation, 30-day historical analytics with Plotly visualizations, and interactive Folium maps. Glassmorphism-themed Streamlit dashboard with Docker containerization and 100+ city support across India/US/EU.

Work Experience

BI Big Data & Analyst

Vodafone Intelligent Solutions

Aug 2022 - Jul 2023

  • Engineered 15+ data pipelines and ETL workflows using AB Initio, GCP (BigQuery, Cloud Storage), and Teradata SQL, processing 500K+ daily transactions
  • Collaborated with cross-functional teams of 8+ members ensuring quality requirements delivery to 50+ distributors with 95%+ on-time delivery rate
  • Reduced critical incident resolution time by 30% through systematic debugging and comprehensive reporting using Unix shell scripting and Python
  • Improved data accuracy by 25% by automating quality checks with Python scripts, decreasing manual verification effort by 40%

Tech Consultant

High Radius

Jun 2021 - Jul 2021

  • Completed business analysis and technical documentation for 3+ client projects, translating requirements into data models and analytical frameworks
  • Performed data analysis on 100K+ records using Python (Pandas, NumPy) and SQL to identify process inefficiencies, delivering 5+ actionable insights
  • Developed 10+ detailed client documentation including data dictionaries and technical specifications, reducing onboarding time by 25%

Technical Skills

Languages

Python C++ TypeScript SQL R Shell Scripting

Machine Learning & AI

TensorFlow PyTorch Scikit-Learn NLP RAG LLMs Computer Vision Deep Learning OpenCV

Web Development

React.js Node.js FastAPI Streamlit RESTful APIs

Cloud & Big Data

Google Cloud Platform BigQuery Cloud Storage AB Initio Teradata

DevOps & MLOps

Docker Kubernetes CI/CD MLflow Git

Databases & Tools

MySQL MongoDB ChromaDB Vector Databases Pandas NumPy LangChain

Education

🎓

Master's in Computer Science

George Washington University

Aug 2024 - May 2026

Coursework: Design & Analysis of Algorithms, Machine Learning, Cloud Computing, Computer System Architecture

🎓

B.Tech. in Computer Science Engineering

SRM University

Jul 2018 - May 2022

Coursework: Data Structures & Algorithms, Probability & Queueing Theory, Data Mining & Analytics, Artificial Intelligence

Articles

Technical insights on software engineering, machine learning, and building scalable systems.

🚀 Building Production ML Systems: MLOps Best Practices

Deep dive into MLflow, model monitoring, and deployment strategies for production ML systems.

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âš¡ Real-Time Data Processing with Kafka and Spark

Building scalable streaming pipelines with Apache Kafka and Spark Structured Streaming.

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🤖 Deploying LLM Applications: RAG Architecture Guide

Complete guide to building and deploying Retrieval-Augmented Generation systems in production.

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Get In Touch

I'm always interested in hearing about new projects and opportunities. Feel free to reach out if you'd like to connect!