Predicting Missed Passenger Connections
Predictive Analytics88.9% accuracy · 75% minority-class recall
Random Forest on ~50,000 flight records with SMOTE for class imbalance and SHAP analysis to identify passengers at risk of missing connections.
Aviation analytics · Operations · Revenue
Aerospace Business Analytics graduate building predictive models, optimization systems, and decision-ready dashboards for airlines and aviation teams.
01 / Selected Work
Each project leads with the operational problem, shows the analytical approach, and ends with a decision a stakeholder can use.
88.9% accuracy · 75% minority-class recall
Random Forest on ~50,000 flight records with SMOTE for class imbalance and SHAP analysis to identify passengers at risk of missing connections.
82 min best turnaround (B737)
Linear programming crew and baggage allocation across 5 aircraft types and 10 scenarios; the B737 was most consistently best at 82 minutes.
Fuel cost pass-through near zero
Econometric models of two decades of U.S. airline fares; GDP emerged as the strongest fare driver.
UPS ~52% higher RTM efficiency per departure
Comparative analysis of cargo networks; operating margin FedEx 5.7% vs UPS 12.1%.
Ancillary revenue & load factor drive profit
OLS regression on BTS and Diio data; ancillary revenue and load factor identified as primary profit levers, with a fuel-hedging recommendation.
Data-driven recommendation: don't launch
Demand and block-time modeling projected 76% unconstrained market share, but CASM economics showed the route would be unprofitable — a data-driven recommendation AGAINST the launch.
02 / Experience
Currently
Building aviation safety data repositories and structured intelligence systems supporting research, analytics, and machine learning initiatives.
Teaching
Helped students understand optimization, simulation, and quantitative decision-making.
Operations
Contributed to logistics planning, inventory management, quality evaluation, and operational execution.
Student Affairs
Supported admissions operations, CRM processes, student engagement, and data management.
Graduate Studies
Embry-Riddle Aeronautical University. Expanded expertise into business intelligence, operations strategy, analytics, and decision-making.
Foundation
Built strong foundations in technical problem-solving, systems thinking, and engineering analysis.
03 / Capabilities
Predictive Modeling & Machine Learning
Applied machine learning to operational aviation data — from forecasting missed passenger connections to uncovering patterns in safety incidents.
Optimization & Operations Research
Modeled and improved complex systems, from aircraft turnaround processes to simulation and quantitative decision-making.
Econometric & Business Analytics
Evaluated demand, financial performance, and route feasibility to turn operational data into strategic, measurable decisions.
Data Visualization & Storytelling
Built clear, decision-ready narratives and dashboards in Power BI that make complex analyses accessible to any audience.
"I like to think ahead — give me the data, and I'll make an informed decision."
Contact
Interested in discussing product strategy, analytics, operations, technology, or future opportunities? Let’s start a conversation.
04 / Beyond the Work
Away from dashboards, I stay active through team sports and make time for strategy games and hands-on creative work.
Play
Table & Board
Creative