Josh Rabbani

Josh Rabbani

Computer Science & AI/ML Student

Duke University junior building full-stack applications and creating real-world impact.

Technical Arsenal

Python
React & Next.js
Java
HTML/CSS
PostgreSQL
Algorithm Design
Swift
SQL
Kotlin
AI/ML
C
Flask
Ruby
JavaScript
R
XQuery
Ruby on Rails
Docker
Assembly (MIPS)

Relevant Coursework

Computer Science

CS 201

Data Structures & Algorithms

Advanced data structures, algorithm analysis, and problem-solving techniques for software development.

Duke University
Completed
Computer Science

CS 230

Discrete Math

Mathematical foundations for computer science including logic, sets, relations, functions, and proof techniques.

Duke University
Completed
Computer Science

CS 250

Computer Architecture

Digital logic, processor design, memory systems, and assembly language programming.

Duke University
Completed
Computer Science

CS 330

Design and Analysis of Algorithms

Advanced algorithmic techniques including sorting, searching, dynamic programming, graph algorithms, and computational complexity analysis.

Duke University
Completed
Computer Science

CS 316

Database Systems

Database design, SQL, transaction processing, and modern database management systems.

Duke University
Completed
Computer Science

CS 370

AI/ML Applications

Machine learning algorithms, artificial intelligence concepts, and practical applications.

Duke University
Completed
Statistics

STA 199

Introduction to Data Science

Statistical analysis, data visualization, and computational methods for extracting insights from data.

Duke University
Completed
Statistics

STA 240L

Probability for Statistics

Mathematical foundations of probability theory with applications to statistical inference and data analysis.

Duke University
Completed
Mathematics

MATH 216

Linear Algebra

Vector spaces, linear transformations, eigenvalues, and applications to computer science and statistics.

Duke University
Completed
Language

SPAN 302

Spanish Grammar & Composition

Advanced grammatical structures, composition techniques, and linguistic analysis of the Spanish language.

Duke University
Completed

Featured Projects

Full-stack platform connecting local businesses with student brand ambassadors, streamlining marketing campaigns and microinfluencing by students. Built with modern web technologies and robust database architecture.

React & Next.jsJavaScriptHTML/CSSPostgreSQLSwiftSQLDatabase DesignReal-time Messaging

Frontend Architecture

  • Next.js Application
  • Atomic Design Components
  • • Tailwind CSS Styling
  • • Responsive UI Design

Backend Systems

  • Supabase Integration
  • • PostgreSQL Database
  • Row-level Security
  • • Real-time Analytics

Key Features

  • User Authentication & Profiles
  • • Application Tracking System
  • Campaign Management Dashboard
  • • Performance Metrics & Analytics

📱 Mobile App Screenshots

Rippl Platform Screenshot 1
🍕

Order Processing Application for Restaurants

Full-stack Android application streamlining meal order processing by Duke students and printing receipts for Durham restaurants in a $120K annual revenue business. Built with hardware integration for StarXpand printers, supporting restaurant operations.

KotlinJavaAndroidHardware Integration

📱 Frontend & Mobile

  • Kotlin Android Application
  • • Dynamic Fragment Management
  • Minimalistic, Accessible UI
  • • Real-time Order Processing

🖨️ Hardware Integration

  • Star Micronics StarXpand SDK
  • • LAN-based Receipt Printing
  • Multi-protocol: Bluetooth & USB
  • • Asynchronous Print Operations

💼 Business Impact

  • • Powers $120K+ Annual Revenue Business
  • Streamlined Restaurant Operations
  • • Real-time Order Management System

📱 Tablet Screenshot

Restaurant Order Processing App Screenshot

Developed and deployed a web tool within 10 weeks to help 1.2 million veterans navigate insurance options to find the lowest-cost diabetes medications, sponsored by Microsoft and the U.S. Department of Veterans Affairs through Duke Office of Information Technology (OIT) Code+ program.

React & Next.jsRuby on RailsPythonPostgreSQLDockerHTML/CSSData ProcessingAPI Development

🎯 Frontend Development

  • Next.js Single-page App
  • Atomic Design Components
  • • Wireframed questionnaire for scalability
  • • Accessibility-focused UI design

📊 Backend & Data

  • Ruby on Rails API
  • • PostgreSQL Database
  • 40GB → 500MB Data Cleaning
  • • Robust API interactions

🎖️ Project Impact

  • • Serves 1.2 Million Veterans
  • Microsoft & VA Sponsored
  • 10-Week Development Timeline
  • • Full Production Deployment

Final Presentation

Team Photo

Vet-RX Team Photo
2025 Hack Duke Hackathon

Full-stack safe navigation platform developed during the 2024 Hack Duke hackathon specifically for Durham, NC using React, Python, and OpenStreetMap, analyzing 7.7M historical traffic accidents across 49 states (2016-2023) to compute Durham-specific safety scores. Features custom pathfinding algorithms for safety-optimized routing in a 24-hour development sprint.

React & Next.jsJavaScriptPythonRSwiftData WranglingStatistical AnalysisGeospatial Analysis

🧠 Backend & Algorithms

  • Python Data Processing
  • NetworkX & OSMnx Integration
  • Custom Pathfinding Algorithm
  • • Kaggle accident dataset analysis

📈 Technical Achievements

  • 7.7M Accident Data Points Analyzed
  • Risk-weighted Route Optimization
  • Folium Map Visualization
  • • Location Presets & User Experience

Application Screenshots

SafeRoute App Screenshot 1SafeRoute App Screenshot 2SafeRoute App Screenshot 3

Hackathon Presentation

SafeRoute Hackathon Presentation

Additional Projects & Presentations

Durham Diner Operations Analysis for Efficiency

Simulated restaurant operations to evaluate efficiency trade-offs using a Poisson arrival model and exponential service time distribution. Analyzed customer flow, wait times, and revenue across 300 simulation runs to determine optimal staffing and table configuration for maximizing profit and satisfaction.

Poisson ProcessesExponential DistributionsProfit ModelingStochastic Simulation
Statistical Analysis Project

Key Takeaways

  • • Modeled customer arrivals as a Poisson process and service times using an exponential distribution
  • • Ran 100 simulations across 3 distinct scenarios: varying chefs, tables, and both
  • • Identified optimal configuration: 2 chefs and 5 tables, balancing near-zero wait time and maximum profit
  • • Quantified downtime, wait time distributions, and service throughput to inform strategic resource allocation

Food Accessibility in the US

Investigated how population density correlates with food insecurity across US states using USDA and census-derived data. Focused on proportions of county populations residing 10+ miles from a supermarket, with emphasis on North Carolina. Used R for data wrangling, mapping, and statistical modeling to reveal geographic and socioeconomic disparities in food access.

Geospatial AnalysisLinear RegressionPopulation DensityR Visualizations
Data Analysis Project

Key Takeaways

  • • Used state-level population and access data from USDA and the US Census via the CORGIS dataset
  • • Created choropleth maps and scatter plots in R to visualize total vs. proportional low-access populations across states
  • • Performed linear regression showing a significant negative correlation between population density and food inaccessibility (p < 0.001)
  • • Highlighted disparities in rural vs. urban states, where sparsely populated states (e.g., North Dakota) show >15% low access

Room Scout

LiDAR-powered room scanning platform for student housing decisions. Won audience favorite in the Duke I&E Quad Cup competition and secured dinner with faculty.

LiDAR3D ScanningEntrepreneurship
Duke I&E Competition Winner

Let's Build Something Together

I like building and making impactful projects. Let's connect and discuss opportunities.

NY