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PORTFOLIO
PORTFOLIO
Featuring my selected works. Always a work in progress, updated as often as life allows.
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Currently seeking knowledge in the airline industry -- whether you work in operations or know someone who does, I'd genuinely love to connect.
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PROFESSIONAL & PERSONAL
PROFESSIONAL & PERSONAL
Restaurant Payroll
Restaurant Payroll
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Synapse Soltuions / Client / Dyanamic Arrays, XLOOKUP / Dec. 2025
For two years, a restaurant's payroll process quietly underpaid an employee by $20,000 — and no one caught it until it was investigated. The error wasn't an anomaly; it was the inevitable result of a system built on manual reconciliation, good intentions, and no structural safeguards. The overhaul rebuilt it entirely: a weighted tip pool distributing earnings proportionally across FOH, BOH, and Bar by role and hours worked, overtime and regular pay tracked separately, extreme visability, POS-integrated sales data, and a labor cost dashboard surfacing metrics like cost as a percentage of sales and sales per labor hour. The result saved 60+ hours of manager time every month and gave ownership visibility into labor costs. Built because the right system is the one the team will actually use — automated, role-aware, and structurally honest, because when paychecks are wrong, real people are harmed.
Student Spreadsheet
Student Spreadsheet
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Personal / Students / Nested FILTER, Apps Script / Aug. 2024
College is a constant flood of deadlines, decisions, and days that disappear before you've tracked what happened in them -- so I built the infrastructure to run mine. A single-backend Google Sheet serving a live productivity dashboard, paginated assignment views filterable by course and week, a monthly calendar, mood and sleep logging with daily auto-logic, and a course planner handling both semester and quarter systems -- every view a formula, nothing templated, designed and built from scratch
Consignment Template
Consignment Template
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Synapse Soltuions / Client / BYROW, LET, LAMBDA / July 2025
A consignment store owner spent 45 minutes shuffling through paper records to figure out what he owed one vendor -- cross-referencing handwritten logs, printed reports, and receipts from three different months. This system replaced all of it: a single Google Sheet trained on real Square POS data, giving any consignment store complete visibility into every transaction, every consignee, and every item -- from the business and consignee dashboard down to what a single client is owed in any period.
GLOBE Merchandise Tracking
GLOBE Merchandise Tracking
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Systems Manager / Project / XLOOKUP, FILTER / Mar. 2026
An engineering organization was spending money on merchandise it already owned — ordering duplicates, handing things out with no record, and discovering shortages only after the fact. This system replaced the guesswork: a live dashboard tracking every item, quantity, and cost in real time, with structured check-in and check-out workflows, automatic archiving, and active adjustment logic that keeps the ledger honest as inventory moves — built on a clean named range architecture that makes it as precise as it is maintainable.
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ACADEMIC
ACADEMIC
LA 2028 Olympics; Operational Planning Report
LA 2028 Olympics; Operational Planning Report
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Academic / Project / Mixed-Integer Programming, AMPL / Spring 2026
The 2028 Los Angeles Olympics requires allocating dozens of sports across a fixed set of venues -- each with capacity constraints, retrofit costs, and geographic considerations. This project formulates that problem as a mixed integer program: decision variables encoding venue-sport assignments, constraints enforcing capacity and compatibility, and an objective minimizing total cost. Implemented and solved in AMPL , the model produces an optimal allocation with full dual analysis and sensitivity reporting. Documented in a formal technical report written to professional engineering standards.
[162] Project.pdf[165] Project.pdfHousing Price Prediction Using Regression Methods
Housing Price Prediction Using Regression Methods
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Academic / Project / Engineering Statistics, Python & Numpy / Spring 2026
Predicting housing prices is a statistics problem that most people oversimplify. This study builds it correctly — OLS regression with full assumption diagnostics, cross-validation, and careful interpretation of coefficients that resist the usual misreadings. The math isn't the interesting part; the thinking around the math is. Built in Python, written up cleanly, and documented so the results are actually legible to someone who didn't run the model themselves.
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