There are no boundaries

You are not afraid to think outside your comfort zone and stick with a problem until you find a solution. We’ll help prepare you to be a collaborator, an algorithmic thinker, and a data-fluent innovator who will thrive in a rapidly changing field.

The Department of Computer Science and Statistics provides a supportive, well-integrated center of multidisciplinary learning and research. Our faculty integrate computer science, statistics, data science, and cybersecurity while reaching beyond departmental boundaries to collaborate with scientists, artists, health care researchers, historians, and engineers across the colleges at URI. Our students grow as professionals, scholars, and citizens because they receive a strong foundation and hands-on experience in the field.


Become a truly global professional

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International Computer Science Program student, Richard Burke standing in front of the Brandenburg gate during his year abroad in Germany

Announcements and Jobs

  • Oana Ignat, Towards Language-Vision Models for Positive Societal Impact (2/16/2024) - When: Monday 2/19 from 1:00 to 2:00 PM Where: Tyler 055 Abstract: Solving complex real-world problems often requires AI models that can process information from multiple modalities, such as language and vision, which can align with the needs of people from diverse backgrounds. An effective AI model will not only learn how to interact with […]
  • Kaleel Mahmood, On the Robustness of Vision Transformers to Adversarial Examples (2/14/2024) - When: Friday 2/16 from 10:00 to 11:00 AM Where: Ranger 202 Abstract: Machine learning has become ubiquitous, being deployed in a range for domains like self driving cars, medical imaging and face recognition. With this increased use of machine learning an important question arises, how secure are these systems? In this presentation we dive into […]
  • Taslima Akter, Designing Privacy Enhancing Technology for Blind and Low-Vision (BLV) People (2/8/2024) - WHen: Tuesday 2/13 from 1:00 to 2:00 PM. Where: Quinn 214 Abstract: Advancements in computer vision and machine learning have empowered Blind and Low-Vision (BLV) individuals through camera-based assistive applications. These systems, capable of recognizing objects, identifying colors, and reading text, provide independence to BLV users. However, the reliance on camera-based assistive systems introduces privacy […]
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