Operations Research (OR) is a discipline that originated at MIT during World War II, applying mathematical and analytical methods to optimize complex decision-making processes.
Initially, OR focused on military logistics and resource allocation, helping plan transportation routes, supply chains, and manufacturing schedules. The field's core methodologies include mathematical optimization, simulation, queueing theory, and decision analysis.
Today, Operations Research has expanded far beyond its original applications and now impacts virtually every industry:
Modern OR increasingly intersects with data science, machine learning, and artificial intelligence, creating powerful new approaches to solving complex real-world problems. Take my initial research interests below as an example:
My initial focus was on contextualizing the behavior and utility of machine learning models as they interplay with humans or in the design of algorithms! With the proliferation of Large Language Models (LLMs) and the general excitement over their integration into our day–to–day lives, the question of how to properly utilize their capabilities becomes vital. Questions like the ones below once peaked my interest: