• Work closely with clients to create tailored analytic solutions to improve business processes
• Help clients understand their business better by identifying trends in the data
• Tailor analytics, dashboards, and visualizations to personalize business solutions

• Construct university dashboards for university president and provosts
• Design multi-page views for financial, academic/educational, athletic performance, and comparative trends
• Calculate and derive custom KPIs for university operations
• Assist with Integrated Postsecondary Education Data System (IPEDS) data submission

• Create survey response dashboard for The American International School of Muscat
• Develop Google Analytics custom dashboard for Relay Graduate School of Education
• Perform data audit for Raven360, including analyzing existing data tools
• Propose structural data governance toolset for enhanced data capture

Objective: Create an AI-powered healthcare denial management solution to help reclaim billions in annual spending on denied insurance claims.

Impact: Prototype application featuring XGBoost ML model for appeal success prediction, Google Gemini 2.5 Flash LLM integration, vendor recommendations, and reimbursement estimates.

Outcome: Developed a data-driven chat application that provides actionable recommendations for claim resolution and demonstrates potential for significant healthcare cost savings.

Objective: Improve hospital room turnover efficiency using Remote Video Auditing technology at Northwell Health.

Impact: Presented recommendations that could reduce turnover time by 35% through process optimization across nursing, EVS, bed management, and HR departments.

Outcome: Collaborated on thesis paper demonstrating how RVA technology enhances quality of care and hospital financial health.

Objective: Visualize key patient outcome and resource metrics. Concept: Tableau dashboards integrating clinical/operational data.

Objective: Optimize hospital staffing via admission prediction. Concept: Python ML models using patient flow data.

What: Comprehensive analysis of earnings events and their market impact with interactive dashboards for price performance, trading strategies, and valuation comparisons.

How: Built with quantitative finance analysis covering major companies like Google, Amazon, Microsoft, and market ETFs (SPY, TQQQ).

Why: To provide deep insights into earnings-driven market movements and trading opportunities around quarterly reports.

What: A simulation that models walking routes on a grid (i.e., Manhattan streets) and uses probability (Monte Carlo method) to find the fastest paths, considering potential delays like traffic lights.

How: Employing a Monte Carlo simulation method to compare the efficiency of fixed walking paths versus paths that adapt based on conditions (like traffic lights).

Why: A real-life scenario of figuring out what the fastest, on average, method to walk to work was.

What: Visualizing the cyclic nature of Bitcoin. Analyzing historical patterns to forecast future highs and lows.

How: Built with React and Vite, utilizing logarithmic regression and cycle theory to project market movements.

Why: To provide a clear, data-driven visualization of Bitcoin's 4-year cycles for better pattern understanding. TINFA

What: An interactive web simulation with 3D balls; complete with gravity, colisions, and explosions.

How: Using a Three.js simulation that incorporates gravity, collision detection, and user interaction (both for mouse and touch).

Why: Because it's fun. And to put some Three.js into practice.

What: A visual simulation displaying numerous small particles moving across the screen, their paths influenced by underlying, interactive force fields.

How: Implementing an HTML5 Canvas API simulation featuring interactive force fields that affect particle movement.

Why: To make pretty, dynamic patterns. It was a fun exercise in using the Canvas API to create interactive visuals - and turned out more fun to play with than I anticipated.

What: A basic sample page designed as a dashboard displaying stock market indicators, using static sample data.

How: Creating a front-end dashboard using HTML, CSS, and JavaScript, having it fed by live refreshable data feeds using YFinance (though this example is static).

Why: The real version is a version I use to this day for my personal investing purposes.

This portfolio isn't just a static page; it's a dynamic application showcasing advanced front-end development. It features a custom-built Gemini API powered chatbot for interactive Q&A, a unique physics-based theme toggle using Matter.js, and sophisticated content interactions like dynamic filtering and an animated career timeline, all built from scratch. Every element is carefully constructed with HTML, styled with CSS, and made interactive through extensive JavaScript.