Giuseppe Ateniese
Dr. Ateniese is a leader in security applications of machine learning. He received the CAREER award from NSF for his work in privacy and security.
Ph.D. in Data Science
Artificial intelligence is the hottest topic in business and science, yet there’s a shortage of thought leaders capable of studying, understanding and applying advances in A.I. and machine learning in practical ways.
At Stevens, the interdisciplinary Ph.D. in Data Science prepares inquisitive students to become pioneers in this space through a rigorous curriculum emphasizing mathematical and statistical modeling, machine learning, computational systems and data management. The program is administered through both the Schaefer School of Engineering and Science and the School of Business at Stevens, ensuring a diverse curriculum that responds to demand for data scientists with extensive knowledge of the theories, techniques and applications associated with data and artificial intelligence. Graduates become research leaders in academia or industry, where they lead the organization’s forays through the data revolution and into the age of A.I. and machine learning.
Data Science faculty
As a Data Science student, you'll work closely with faculty whose research is responsible for important breakthroughs in artificial intelligence, deep learning, computational intelligence and more.
David Belanger
A former chief scientist at AT&T Labs, Dr. Belanger has earned more than 30 patents related to data science and business analytics.
Germán Creamer
A highly cited business researcher investigating applications of machine learning and social network algorithms to solve finance problems.
Ionut Florescu
Dr. Florescu is an expert in creating stochastic models for practical application. He leads an international conference on high frequency in finance.
Ted Lappas
An expert in data mining and deep learning, Dr. Lappas is an authority in the business impact of fake reviews in social media.
Jeffrey Nickerson
Dr. Nickerson has won many grants from NSF to explore crowd creativity, collective intelligence and information systems design.
Antonio Nicolosi
Dr. Nicolosi is an accomplished researcher whose work in cryptography and security in distributed systems is breaking new ground in data science.
Steve Yang
Dr. Yang's work in systemic risk, fraud detection and behavioral finance is changing how companies operate in the finance space.
Doctoral concentrations
Students in the Data Science program choose one of the available concentrations or, working closely with their faculty advisor, create a custom concentration of their own.
Financial services
The data-driven disruption in finance continues to be the story of the industry. Topics covered in this concentration are focused on creating opportunities in robo-advising, financial innovation, portfolio optimization, fraud detection and beyond through careful study of topics like data visualization and analytics, machine learning, natural language processing and text mining.
Life sciences
The use of data science techniques is increasingly helping researchers unlock new discoveries in the traditional sciences. This concentration prepares you to solve problems through analysis of experimental, drug performance and patient data and techniques such as statistical modeling, data management and machine learning.
High-tech labs power impactful research
To be a thought leader in data science, you must be an excellent researcher. At Stevens, you'll work in high-tech labs and with faculty in world-renowned centers to prepare you for career success.
An edge in fintech
The Hanlon Financial Systems Center's two labs offer unrivaled financial analytics and data visualization capabilities.
Institute for A.I.
The Stevens Institute for Artificial Intelligence is the hub connecting dozens of researchers investigating A.I. and machine learning.
Health and A.I.
The Health and A.I. Laboratory aims to improve human health through the development of artificial intelligence methods.
Bio boost
Work at the Computational Systems Biology Lab involves modeling biological systems in the study of complex systems with diverse elements.
Contact Us
Ph.D. in Data Science
Location On Campus
Gateway Center
Contact Types
Department Leaders
Yue Ning
Assistant Professor