Darinka Dentcheva
Darinka Dentcheva is a revered researcher in stochastic optimization and control using mathematical models of risk and their applications.
Data Science Master's Program
Learn the theoretical knowledge and practical skills necessary to analyze big data for functional application in business and technology.
Demand for data scientists who can glean insights from the wealth of information made available through modern technologies to aid in informed decision-making is on the rise. The data science master’s program at Stevens instills the theoretical knowledge and practical skills required for dealing with the contemporary collection, exploration, analysis, and modeling of data along with the related challenges pertaining to inference and prediction.
This interdisciplinary program prepares students for careers in fintech, business intelligence and analytics, academia, and database management, as well as government positions requiring strong skills in data analysis. Students will analyze complex data, including large scale databases, and apply state-of-the-art modeling and visualization techniques. They will participate in simulations of cyberattacks and create effective defense strategies, as well as study, in depth, the algorithms and optimization schemes underlying the latest business analytics methods.
The Stevens Advantage
Poised on the Hudson River, just 15 minutes away from downtown Manhattan, Stevens is located near the heart of one of the world’s biggest technology hubs. Proximity to New York City offers Stevens students recruitment opportunities with some of the biggest names in business and technology, including Google, Amazon, Microsoft and Bloomberg.
Stevens’ World-Class Faculty
Stevens' math department boasts one of the top algorithmic and geometric group theory teams in the world, with distinguished experts in stochastic optimization and cryptography.
Michael Zabarankin
Michael Zabarankin researches risk management and optimal control, continuous and discrete optimization, mathematical physics and variational principles…
William Aeberhard
William Aeberhard researches robust statistics, non- and semi-parametric methods, ecological applications, spatio-temporal modeling and computational statistics…
Shusen Wang
Shusen Wang researches Statistical machine learning, numerical optimization, randomized algorithms, and parallel computing.
Data Science Research
Stevens is a Premier Research Institution
The Department of Mathematical Sciences focuses its research around stochastic systems and optimization as well as algebraic cryptography. New methods in these areas have extensive implications for predictive modeling across a wide range of disciplines.