Math with a purpose—using probability and statistics for the greater good
Sean Sinclair, a Ph.D. student in Cornell Engineering’s School of Operations Research and Information Engineering (ORIE), sees the entire world as a mix of probability and optimization problems. “Something I enjoyed as an undergrad and still enjoy doing today is working a lot with probability and statistics and using them to optimize the way that we run algorithms in the real world to address actual problems,” he said.
This love of math was not always evident, though. “To be honest, when I was kid, I was awful in school,” Sinclair said. “It wasn’t until high school, when I started working with this one teacher, Deb Post, that I really started to find my stride.” For much of his high school career, Sinclair did not attend traditional math classes. Instead, he worked with Post, staffing a math help desk and engaging in independent study. In this way, he discovered his love of teaching alongside his fascination with probability and statistics.
Today, Sinclair is starting the fourth year of his doctoral studies at Cornell and working with ORIE Professors Christina Yu and Sid Banarjee on ways to use math to optimize the operations of the Food Bank of the Southern Tier. This non-profit organization works to meet the weekly food needs of more than 20,000 people in a six-county area of upstate New York that spans nearly 4,000 square miles.
Sinclair explained that the COVID-19 pandemic has forced changes to the way the food bank gets food to people. “Trucks from the food bank have to travel to different locations throughout the day, and at each location they have to decide how much food to distribute, not knowing how much food will be needed at subsequent stops,” he said . Sinclair uses a framework for sequential decision-making that can optimize the organization’s operations even under conditions of uncertainty.
This work is certainly in keeping with advice Sinclair received from his undergraduate advisor at Montreal’s McGill University, where he majored in mathematics. Shortly after graduating from McGill, Sinclair joined the U.S. Peace Corps and taught math in Ghana for three years. Upon his return to the U.S., he met with his former advisor who told him that studying operations research would give Sinclair a way to do “math with a purpose.”
Sinclair has realized the truth of this at Cornell. “I look around the department and see how relevant so much of the work is,” he said. “COVID testing policies, classroom assignments, final exam schedules, ambulance deployment — these are all challenges people in ORIE are tackling.”
This year, Sinclair plans to broaden his focus to include the creation of a simulator for the broad category of problems represented by the food bank’s challenge. “There are these stereotypical operations research-type problems that involve sequential decision-making,” he said. “And we want people that study reinforcement learning to be able to test their algorithms on these types of problems, too. Right now, there’s no good way for them to do that.”
Sinclair’s work on this project is especially gratifying because it allows him to combine the research he loves with teaching and mentoring undergraduates. “I love working with people through the struggle of trying to understand how something works,” he said. “I remember that struggle very clearly from when I was a kid, and it feels good now to help students make sense of things.” He is hoping to eventually find a position that allows him to keep this balance.
“Once I graduate I want to find a faculty position at a university that allows for a satisfying balance between teaching and research,” Sinclair said. “I don’t see myself running a high-powered super-serious research lab, but I also don’t imagine devoting all of my time to teaching. I truly enjoy both and want to find a department that matches my priorities.”
When Sinclair is not thinking about probability, statistics, and optimization, he can be found on his bicycle or on Cornell’s Lindseth Climbing Wall — two activities that allow him the chance to focus intently on the immediate challenge and offer a break from the stressors of academia.