Cynthia Rudin says that her job is to encourage future managers to make decisions grounded in data, and this is exactly the mindset that earned her a spot on the 40 under 40 list of best business school professors by Poets & Quants.
As an associate professor of statistics at MIT’s Sloan School of Management, Rudin specializes in big data, applied statistics, data mining, and machine learning.
Rudin and her students are putting their theories into practice by designing predictive models and knowledge discovery systems to help inform decision makers. They are working with a variety of different industries including race car teams, police detectives, doctors, power engineers, marketing experts, and many others who are interested in data-centered prediction problems. “One of the reasons our research is effective is because we have such knowledgeable collaborators with domain expertise,” says Rudin.
Here are a few examples of complex problems that Rudin is using data to solve:
- Predicting stroke in patients with atrial fibrillation
- Diagnosing sleep apnea
- Predicting power outages caused by manhole fires and explosions
- Detecting patterns of crime committed by the same individual or group of individuals
- Predicting recidivism of prisoners to allocate social services and determine bail
“My goal in teaching is to help people understand how and why data driven tools can be useful,” says Rudin.
Before coming to Sloan in 2009, Rudin earned her PhD in applied and computational mathematics from Princeton University and worked as a research scientist at both Columbia and New York University. Her work has been featured in Businessweek, The Wall Street Journal, the New York Times, the Boston Globe, the Times of London, WIRED Science, U.S. News and World Report, and IEEE Computer.