High performance computing data science and evolving agent-based simulation.

· CUSTOMER PRESENCE FORECASTER: System to forecast and simulate passenger traffic, customer service and arrival patterns for all stations to evaluate future airport designs. · OPTIMAL GATE CONSOLIDATOR: Clustering of flight assignments to gates (machine learning) to achieve continuous uniform podium activity using customer service queuing-model simulations. · STRATEGIC FUEL COSTING: Developed a fuel vendor bid analysis and Southwest price positioning adviser that forecast weekly average spot market fuel prices (eigen vector network analysis) and Southwest daily fuel consumption over a twelve month period (CUDA environment) . · STOWING/SEATING OPTIMIZATION: Developed an agent based simulation that found the fastest passenger boarding regime for assigned seating in the airline industry. · OPTIMAL GATE FLIGHT ASSIGNMENT: Combined machine learning and agent based simulation to determine the must efficient gate use of Southwest arriving flights at Seattle-Tacoma and Phoenix Sky Harbor airports. · AIRCRAFT PRESENCE FORECASTING: Developed a conditional probabilistic forecaster (CUDA environment)of aircraft route movement used to set airport staffing through flight schedule adjustment. · FUELING OPTIMIZATION: Used evolutionary computation (convergent, genetic programming) to optimize tankering of fuel.