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Businesses and organizations of all shapes and sizes use models to understand and improve the performance of their operations. For example, online retailers use models to quantify the impact of different order fulfillment policies. On-demand transportation systems use models to make better decisions on how to assign passengers to drivers. Fintech companies use models to make automated trading decisions on millisecond time scales.

The data & modeling group at Cornell Tech includes quantitative researchers with backgrounds in computer science, electrical engineering, business, and operations research, developing models for decision-making problems in a variety of areas including logistics, retail, marketing, biotech, finance, and healthcare. Their work involves building models to automate decision-making processes, designing algorithms to efficiently solve these models, and using statistics and machine learning techniques to make predictions.

Our research group works with a number of large tech companies and startups. Through such interactions, we are able to play a leading role in implementing the next generation of sophisticated models in practice, while having the opportunity to find out about research problems that are of critical interest to the industry.