HUSEYIN TOPALOGLU: We designed the operations research program to raise quantitative experts, business analysts, and data scientists that could use large amounts of data, cutting-edge computation, and mathematical algorithms to drive business intelligence. GREGORY PEKAR: The ORIE program at Cornell Tech, I think, is a good mix of applied math, computer science, and statistics. And we really try to merge all three disciplines together to get something really, I think, that's applicable to real-life problems. ITAI GURVICH: Operations research is about the modeling and data-driven optimization of business processes. And our mission is to educate professionals that have the skill to take real problems and translate them to this language of mathematical models that they can then use to inform better decisions. NATHAN KALLUS: Operations research is being deployed in wider and wider contexts. In this very city, we're seeing it being used by Uber, by Amazon, by Citibike to drive the logistics of how to position its various vehicles. HUSEYIN TOPALOGLU: The program that we have here at Cornell Tech has an interdisciplinary nature. And our operations research student always work together with the other students from other disciplines. So for example, when they do a project, they could be working in a team of six students. And two of these students could be operations research students. Two of them could be computer science students, one could be information science student, one could be an MBA student. XIA (LYDIA) LI: Here, like, you enjoy the atmosphere that different students contribute together to complete one product. From the very beginning, like scratch your ideas, brainstorming, to the very end, like deliverables. NOEL ALEXANDER: My team last semester was a team of two MBAs in computer science and operations research. And we worked on a project in fintech. When you think about a problem in fintech, it really speaks to interdisciplinary work. You have MBAs who understand the financial aspects. When you think about finance, you need a lot of data. So that's where our OR person comes in. When you think about actually developing the code and the frontend solution, that's where a computer science student is perfect. So that was really, for me, what affirms how you could bring all these different backgrounds together and actually build something that really work can have that real-world impact. HUSEYIN TOPALOGLU: Studio gives our students the chance to solve real business problems, interacting with real-world companies, using real-world data. And it allows them to see how solving a real business problem, or designing a real business is different from a textbook exercise. NOEL ALEXANDER: You really have to have that vested interest in tech and how it can be used to solve problems in the world through entrepreneurship. You're going to sit through product studio. You're going to sit through startup studio, and all the classes that go along with it like product management. And you're really going to want to be interested in those concepts to obviously get through the classes and do well. And there's a lot to learn from it. GREGORY PEKAR: Everyone is capable of being really creative and think about things in different ways that you wouldn't necessarily think about beforehand. I think some of our classes here just kind of teach us to do that. NOEL ALEXANDER: There's no sort of teaching curriculum around entrepreneurship. Some places do it, but here, you sort of learn by doing. And I think that's been very valuable. XIA (LYDIA) LI: Because of all the courses I learned, both technical classes and business classes, it gave me the confidence to become a qualified data scientist. [MUSIC PLAYING]