Featured Projects

Room Scheduler System

Stack: PHP · MySQL · HTML · CSS

Problem

Shared rooms and resources lead to double-bookings, unclear availability, and inefficient coordination when scheduling is handled informally or manually. Teams need visibility into availability, approval status, and administrative oversight from a single source.

Solution

Built a full-stack scheduling system supporting room booking workflows, resource tracking, and admin-friendly management. The system centralizes bookings into a structured database, reduces scheduling conflicts, and gives administrators full operational control.

Key Features

• Full booking workflow — create, view, update, delete
• Centralized scheduling to eliminate double-bookings
• Equipment and resource tracking support
• Admin controls for organizational management

What This Demonstrates

• CRUD patterns and database-backed operational workflows
• Structured data handling and form-based user flows
• Clean navigation and UI design for practical usability

Screenshots

Inspection Reporting Automation

Tools: Excel · Structured Reporting Workflows

Problem

Manual reporting requires repetitive extraction, formatting, and verification steps — each cycle introducing opportunities for inconsistency and error. Monthly reporting workloads benefit from structured, repeatable approaches that produce consistent outputs regardless of who runs the process.

Solution

Designed a repeatable reporting workflow to reduce manual steps and improve consistency for monthly reporting cycles. The output is structured for easy review, sharing, and archiving.

Key Highlights

• Structured extraction and formatting steps for output consistency
• Reusable workflow supporting monthly reporting at scale
• Designed for quick review and operational decision-making

Impact

• Standardized formatting across all monthly reports
• Reduced manual steps and error-prone data entry
• Improved turnaround and reviewer experience

Work Hours Tracker

Python · Flask · Pandas · Excel · Jinja2

A full-stack Python/Flask web application for logging and tracking work hours across multiple clients. Features automatic earnings calculation based on per-client hourly rates, schedule validation to prevent entries on non-working days, weekly summaries with Pandas groupby aggregation, and Excel-based data persistence.

• Per-client hourly rates and working day schedules enforced server-side
• Pandas DataFrames for data manipulation and weekly aggregation
• Excel read/write with openpyxl for persistent storage
• REST API routes: log, delete, and weekly summary views
• Deployed to cloud with environment-based PORT configuration

Marrison Bee Enterprise — Business Dashboard

Stack: HTML · CSS · JavaScript · LocalStorage API

Problem

A wholesale consumer goods business needed a way to track customer orders, manage supplier purchase orders, monitor stock levels across dozens of products, and generate professional invoices — all without expensive enterprise software or a backend server.

Solution

Built a fully offline-capable, single-file business management dashboard that runs entirely in the browser. The system handles the complete order lifecycle, real-time inventory tracking, supplier purchase orders, and professional invoice generation with WhatsApp sharing — with all data persisted locally via the browser's LocalStorage API.

Key Features

• Customer order pipeline — Draft → Confirmed → Packed → Delivered → Paid
• Supplier purchase orders with automatic stock updates on receipt
• 37-product inventory with real-time stock level tracking (10,000+ units per product)
• Professional invoice generation matching real company invoice format
• WhatsApp integration — one-click formatted order summaries sent to customers
• Sales ledger with CSV export, customer credit tracking, and payment breakdown
• Kanban board view for visual order pipeline management
• Configurable markup pricing with automatic sell price calculation

What This Demonstrates

• Complex state management and data persistence without a backend
• Business process design — translating real-world workflows into software
• Professional UI/UX design for operational business tools
• Client-side data architecture using structured LocalStorage keys
• Dynamic document generation (invoices, WhatsApp messages, CSV exports)

LN2 Tank Availability Dashboard

Stack: Python · FastAPI · Next.js · PostgreSQL · Docker

Problem

In a GMP cell therapy manufacturing environment, LN2 cryogenic tanks store thousands of patient and donor samples across hundreds of racks and locator slots. Identifying which racks have open slots for new samples required manually cross-referencing daily EBS inventory exports — a time-consuming, error-prone process with no central visibility into real-time storage availability.

Solution

Built a full-stack availability dashboard that ingests daily EBS on-hand exports and computes rack-level availability across all active LN2 tanks in real time. The system surfaces open storage slots with exact locator addresses, ranked by availability — reducing the time to identify a valid storage location from minutes to seconds.

Key Features

• Daily EBS export ingestion via drag-and-drop upload (CSV or Excel)
• Rack availability engine applying GMP storage rules — 4 slots per rack, racks 1–30 only, excluded tanks filtered automatically
• Per-tank capacity charts and rack-level availability bars with color coding
• Exact empty locator addresses surfaced for immediate sample placement
• Snapshot history — every upload timestamped, dashboard always shows latest data
• Filter by tank (LN2_03 through LN2_10) and minimum empty slots threshold

Architecture

Python FastAPI backend with SQLAlchemy ORM and PostgreSQL database. Next.js frontend deployed on Netlify. Backend hosted on Render. All services containerized with Docker for local development. Locator parsing engine validates the full EBS format (SUBINVENTORY.TANK.RACK.SLOT) and applies configurable business rules before persisting to the occupancy snapshot table.

What This Demonstrates

• End-to-end full-stack system design for a real operational problem in GMP manufacturing
• Domain-specific business logic implementation (locator parsing, rack rules, tank exclusions)
• REST API design with FastAPI, database modeling with SQLAlchemy, file ingestion with Pandas
• Production deployment across Netlify, Render, and Neon PostgreSQL
• Practical data systems work directly applicable to cell therapy operations

Resource Hub — Q&A Knowledge Base

Stack: HTML · CSS · JavaScript

Purpose

A searchable knowledge base built to answer real questions about cell therapy manufacturing, GMP compliance, data systems, and career paths — written in plain language by someone working at the intersection of these fields. Designed for students, professionals exploring biotech, and anyone curious about how this work actually functions day to day.

Key Features

• Live search across all questions and answers — results filter as you type
• Category tabs: Cell Therapy, Data Systems, GMP & Compliance, Career, My Work
• Expandable Q&A format — clean and readable without overwhelming the page
• Fully human-written answers — no jargon, no generic content
• Contact prompt for questions not yet covered

What This Demonstrates

• Ability to communicate complex technical and regulatory topics clearly
• Front-end development — interactive search, filtering, and accordion components built from scratch
• Domain expertise across cell therapy manufacturing, GMP, and data systems
• Content design and information architecture for a professional audience

Academic Projects

Selected academic projects from Hood College M.S. in Management Information Systems, covering data systems, analysis, and applied computing. Projects are being organized with full documentation — problem statement, tools, methodology, and outcome.

• Project documentation in progress — check back soon
• Available on request for specific review contexts

Each project will follow the same structure: Problem → Solution → Tools → Outcome → Documentation.