Graduate Program in Data Science (MS & PhD)

The rapid growth of data in every sector—from science and engineering to business, healthcare, and the social sciences—has fueled an unprecedented demand for advanced data analytics, machine learning, and artificial intelligence expertise. The Master of Science (MS) and Doctor of Philosophy (PhD) programs in Data Science at Stony Brook University are jointly sponsored by the Department of Applied Mathematics and Statistics (AMS) and the Department of Computer Science (CS), offering students a unique interdisciplinary education that blends strong theoretical foundations with cutting-edge computational skills.

Our programs place a strong emphasis on machine learning, AI, and statistical modeling, enabling students to develop the tools needed to extract knowledge from large, complex datasets and to design intelligent systems that can adapt and learn from data. Students benefit from world-class faculty, access to high-performance computing resources, and opportunities for collaborative research that bridges mathematics, statistics, and computer science.

Graduates of our Data Science programs enter a job market that continues to expand at a remarkable pace. According to the U.S. News & World Report, “Data Scientist” is ranked #8 in the 2025 list of 100 Best Jobs— reflecting both the strong demand and the rewarding career prospects in the field. Whether pursuing careers in industry, academia, or government, our alumni are well-prepared to lead in this data-driven era.

Given the interdisciplinary nature of data science—encompassing statistics, computer science, and applied mathematics—the program draws on the full faculty of Stony Brook University’s Departments of Applied Mathematics and Statistics and Computer Science. Here, we highlight some of our dedicated data science faculty members and staff you will encounter in your graduate studies. Their expertise spans statistical modeling, quantitative finance, machine learning (including deep learning and reinforcement learning), cloud computing, image analysis, natural language processing, and database management.

For detailed information on the Data Science graduate program admissions and course offerings, please visit our companion website.

Data Science Graduate Program Faculty and Staff

• Faculty and Staff Directory

  Zhenhua Liu (Data Science Graduate Program Director) (AMS 560 Big Data Systems, AMS 691, Section on Recent Progress in AI and Machine Learning)

  Christine Rota (Data Science Graduate Program Coordinator) (Math Tower P141; Phone: 631-632-8360; Christine.Rota@stonybrook.edu)

  Hongshik Ahn (AMS 507 Introduction to Probability)

  Yuefan Deng (AMS 530 Principles in Parallel Computing)

  Eugene Feinberg (AMS 507 Introduction to Probability)

  Pei-fen Kuan (AMS 572 Data Analysis, AMS 597 Statistical Computing)

  Jian Li (AMS 691, Section on Reinforcement Learning)

  Yi Liu (AMS 691, Section on Deep Learning)

  Pawel Polak (AMS 520 Machine Learning in Quantitative Finance)

  Silvia Sharna (AMS 572 Data Analysis, AMS 597 Statistical Computing)

  Weihao Wang (AMS 507 Introduction to Probability, AMS 521 Data Management, AMS 580 Statistical Learning)

  Song Wu (AMS 598 Big Data Analysis)

  Haipeng Xing (AMS 516 Statistical Methods in Finance)

  Chenyu You (AMS 563 Medical Image Analysis)

  Jiawei Zhou (AMS 691, Section on Natural Language Processing)

  Wei Zhu (AMS 580 Statistical Learning)

  All faculty in AMS

  All faculty in Computer Science