About Me
I am an undergraduate researcher in Industrial and Systems Engineering at the University of Oklahoma studying optimization under imperfect information, especially in public and infrastructure systems. My work asks how decision-makers should act when models are simplified, data are incomplete, and resources are constrained.
I am building that agenda through two connected streams of work: regret-aware optimization for public planning and resilience analysis for large transportation networks. Across both, I am interested in how mathematical models can remain useful when the information available to the decision-maker is incomplete, imperfect, or changing over time.
Recent outputs include an accepted conference proceedings paper at the IISE Annual Conference & Expo, poster presentations on park-access modeling and parameterization regret, and current research in the NetSys Research Lab on airline network disruption and recovery.
That perspective shapes the kinds of questions I want to pursue in a PhD in Industrial Engineering or Operations Research: optimization frameworks that better reflect the informational limits and modeling tradeoffs faced by real decision-makers, especially in public-good settings.
I also highlight a small number of selected projects when they show the same broader research habits: problem formulation, careful modeling choices, and interpretation of tradeoffs. Some of that work comes from research settings and some from coursework, but I aim to present all of it transparently and selectively.
Start Here
Research:research agenda, flagship projects, methods, and current directions.Research Outputs:conference proceedings, posters, and research-in-progress entries.CV:education, coursework, honors, and a full record of experience and presentations.
Research At a Glance
Research agenda:optimization and decision support under uncertainty in public and infrastructure systems.Current work:airline network resilience and dynamic recovery using Dynamic Mode Decomposition and network-based analysis.Flagship output:accepted IISE conference proceedings paper on park-location optimization under imperfect information.Methods:mixed-integer optimization, bi-level and regret-aware modeling, network optimization, and data-driven analysis.
Research Direction
Each project on this site is evidence for the same broader research direction: decision support is only as strong as the assumptions behind it. I am especially interested in models that stay informative even when data are incomplete, objectives are imperfect proxies, or the real system is more complex than the optimization model can fully represent.
Selected Projects
I include only a few projects here to show the kinds of modeling questions and technical tradeoffs that shape my research trajectory.
Optimization of Park Access with Imperfect Information
Research project
- Studies how park-location recommendations change when competing measures of need disagree.
- I took the main role in formulating and coding the model, wrote the methods section, and edited the full paper text.
- Led to an accepted conference proceedings paper, poster presentations, and ongoing work on parameterization regret in public planning.
Airline Network Dynamic Recovery
Current research project
- Examines how airline networks respond to disruption and recover over time.
- Uses Dynamic Mode Decomposition and network-based analysis to study resilience patterns that static summaries can miss.
- Extends my interest in decision support under imperfect information to large transportation systems.
Multi-Objective Workforce Scheduling Under Preference Constraints
Course project
- Developed a bi-objective integer programming model to balance staffing coverage with employee shift preferences in a real scheduling setting.
- Applied the epsilon-constraint method to generate a Pareto frontier under availability, shift-limit, and leadership constraints.
- Found that improving coverage typically required increasing unwanted assignments almost one-for-one, highlighting a tight tradeoff between operational and human-centered objectives.
- Reflects my broader interest in decision-making under competing objectives and constrained information.
Research Journey
NetSys Research Lab
The NetSys Research Lab at the University of Oklahoma studies the performance, robustness, and resilience of cyber-physical-social systems and interdependent networks.
My current work examines airline network resilience through Dynamic Mode Decomposition and network-based analysis, with the goal of understanding how disruptions propagate and how large transportation systems recover over time.
Tucker Research Group
The Tucker Research Group at Clemson University studies how operations research can improve access, social good, and decision-making in systems under strain.
During the Human-Centered Operations Research and Engineering (H-CORE) REU, I worked on park-access optimization in Greenville County, South Carolina, studying how different need indices and modeling assumptions change recommended investment decisions.
That project led to an accepted IISE conference paper, multiple poster presentations, and my continuing interest in regret-aware optimization for public planning.
