Projects

Generative Inverse Optimization

Generative AI has swept the nation, in many ways leaving traditional optimization behind. However, it ironically borrows heavily from the optimization toolbox.
In this project, we look to generate models from large datasets, in a similar fashion to AI. Unlike AI, however, we will be working with datasets that form optimization problems and learning those instead.
Through this project, we hope to learn more about the overlap between modern-day AI and OR, and how the two fields can continue to build eachother up over time.

The Impact of AI Scribes on Primary Care Practitioners

AI scribe technology has been rapidly deployed in practitioners offices in the past year or two, but the studies in terms of efficacy and where it is and isn't helpful are just catching up. We are working on one of these studies!

The Homecare Provider Allocation Problem

Dispatching home care workers to patients is a natural problem for operations research, in that it is difficult, multistage and data-intensive. In this project, we look for ways to make this very large project tractible and adjustable for non-expert users that will be using the end-systems.

Incorporating Robustness into Radiation Therapy Treatment Planning

When planning radiation therapy plans, or optimizing in general, the greediness of the underlying algorithms can have negative impacts on plan selection. In this multi-year body of work, we investigate the interplay between very large models and uncertainty, studying which kinds of approaches are best to mitigate uncertainty in various scenarios.

Geometric Beam Angle Optimization

When clinicians plan radiation therapy treatment plans for step-and-shoot radiation therapy, the beam angles must be chosen before any calculation can be made. These angles are often selected to be equidistant, due to the difficulty in determining the best angles *a-priori*. The literature has employed heuristic approaches that have been shown to work better than this naive equidistant approach. However, what if there were more knowledge-based approaches to doing so?