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Undergraduate and Graduate Computer Science, Statistics, Data Science, and Cybersecurity

Undergraduate Programs

Computer science is a vibrant and rapidly changing discipline. Our undergraduate curricula are aligned with the ACM & IEEE 2013 Curriculum Guidelines. Courses in machine learning, computer vision, and secure programming add to the core problem-solving expertise needed in diverse industrial settings. Experiential learning provides students a practical and rounded curriculum.

Graduate Programs

The department offers M.S. and Ph.D. degrees in Computer Science and Statistics, a graduate certificate in Cyber Security, and a PSM degree in Cyber Security. Our programs are committed to meeting the needs of both industry professionals and full-time graduate students. For selected full-time students, the department may offer teaching and research assistantships that pay a stipend and cover tuition, fees, and insurance.

Research

The Department of Computer Science and Statistics supports the work of scholars and students who are adept in taking an agile, interdisciplinary approach to solving problems. As our department encompasses both computer science and statistics, the areas of research specialization are wide-ranging.

International Computer Science Program student Richard Burke standing in front of the Brandenburg gate

International Program

Computer science in the internet age is an international field with an ever-increasing need for multilingual, interculturally savvy professionals. The Computer Science Department collaborates with URI’s International Engineering Program (IEP) and the Department of Languages to offer the unique International Computer Science Program (ICSP).

Announcements and Jobs

Women in AI Workshop (4/16/2025) - When: Wednesday, April 16, 4:30-6:00 pm Where: Ballentine 115 Our Computer Science IGT Scholars are presenting a Women in AI Workshop that is open to all who are interested. The workshop will include a panel of women who have worked in the field of Artificial Intelligence in a variety of capacities: Panel: Dawn Fitzgerald – […]
Stephen Bach, Rigorously Benchmarking LLMs for Translating Text to Structured Planning Languages (3/19/2025) - When: Friday, 4/18/25 11:00 am; Where: Bliss 260 Abstract: Can large language models (LLMs) help with planning? And how should we even measure that ability? In this talk, I will present our work on Planetarium, a benchmark that evaluates LLMs’ ability to generate PDDL (Planning Domain Definition Language) code from natural language descriptions of planning […]
Hang Hua, Advancing Generative AI for Multimodal Intelligence (3/4/2025) - When: Friday, 3/7 11 am – 12 pm; Where: Tyler Hall 055. Abstract: Generative AI is transforming how machines interact with and augment human capabilities. However, achieving artificial general intelligence (AGI) requires addressing significant challenges in retrained language models (PLM) and multimodal large language models (MLLMs), including the brittleness of language model fine-tuning, imbalanced vision-language […]