Experience & projects
My work at UPS, HNTB, and Florida State University: the projects, their impact, and how I approached them.
01 / Experience
Sep 2020 – Present
Impact
Approximately $700 million saved annually for UPS Airlines
I led the research, design, and production deployment of an air cargo planning system that combines demand forecasting with mathematical optimization. I used Python and Gurobi to take the model from development into live operation.
Optimization with Uncertainty · Live production · ML Prediction Methods · Gurobi · Non-linear mixed-integer programming
Impact
A framework for large-scale throughput optimization
I direct research and development of a digital twin for large-scale sort facilities, guiding engineers from research through product development. I designed a sequential optimization framework that breaks large planning problems into coordinated stages using Gurobi and a fix-and-optimize algorithm.
Research & development leadership · Simulation · Mathematical optimization
Impact
75% reduction in contractor overhead
I designed, validated, and deployed a contingency planning tool within two weeks during a union strike. The model supported real-time resource allocation as operating conditions changed.
Production deployment · Two-week delivery window
Impact
12–18% reduction in idle time
I designed and deployed a scheduling heuristic that improves resource use while maintaining compliance with complex network rules and operational constraints.
Production scheduling system
Impact
10–15% reduction in asset requirements across targeted routes
I developed a fleet-sizing heuristic that refines an optimization model’s output. I integrated it into live planning systems to determine the assets needed across targeted logistics routes.
Production deployment · Targeted logistics routes
Impact
A prototype for solving complex airline staffing schedules
I collaborated on a Gurobi-based mixed-integer solver, translating interlocking staffing rules into modular constraints for a large planning problem.
Collaborative prototype · Mixed-integer programming · Gurobi
Impact
An independent baseline for evaluating solver performance and ROI
I built a simulation and optimization engine to assess the statistical efficacy and performance gains of production planning solvers, using simulation and Variable Neighborhood Search.
Research & prototype · Simulation · Solver evaluation
Impact
A modernized planning system for peak-demand, real-time operation
I led the migration of a core planning engine from a C++ / CPLEX implementation to Gurobi, refactoring legacy solver logic to improve speed and reliability.
System modernization · C++ · CPLEX → Gurobi
Impact
Scenario-based decision support for future hardware requirements
I built a tool that lets executives run simulations and compare scenarios to determine which hardware assets would be needed for future rollouts.
Decision support · Scenario analysis · Asset planning
02 / Experience
Apr 2020 – Sep 2020
Impact
Spatial and operational evidence to inform infrastructure decisions
I analyzed geographic and operational datasets to support freight infrastructure research and inform strategic infrastructure development projects.
Freight infrastructure research · Spatial data analysis
03 / Experience
Aug 2017 – Apr 2020
Impact
Routing methods that account for real-time mobile production constraints
Through NSF-funded postdoctoral research, I developed algorithms for vehicle routing with Factory-in-a-Box constraints, connecting freight movement with mobile production requirements.
NSF-funded research · Related publication: IEEE Access, 2020
Impact
Published scheduling algorithms for marine container terminals
I developed metaheuristic methods for complex berth scheduling problems. This work formed the basis of my PhD dissertation and peer-reviewed publications.
Maritime Business Review, 2019 · Advanced Engineering Informatics, 2019
Impact
Risk-based models to support rail crossing resource allocation
I developed Florida DOT-funded mathematical models that use empirical risk data to assess highway-rail crossings and inform safety planning across Florida.
Florida DOT-funded research · Related publication: Energies, 2020
Impact
A framework for evacuation planning that accounts for vulnerable populations
I formulated a multi-objective optimization model for regional evacuation planning under risk, balancing planning objectives and the needs of vulnerable population groups.
Florida DOT-funded research · Journal of Management in Engineering, 2020
Impact
An optimization framework that accounts for product degradation
I designed a planning framework for perishable supply chains, using predictive metrics to incorporate product degradation into resource and logistics decisions.
Optimization framework research · Predictive modeling
I enjoy connecting with people working on interesting problems in research, engineering, and analytics. Feel free to get in touch to exchange ideas or catch up.