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

  • Marco Alvarez, Transforming Research and Higher Education with Generative AI and Foundation Models (4/4/2024) - When: Friday April 5. – noon-1 p.m. Where: Bliss 190 This talk delves into the transformative potential of generative AI and foundation models in both scientific research and higher education. Foundation models represent a seismic shift in AI capabilities, empowering researchers to analyze data, generate hypotheses, and uncover knowledge with unprecedented efficiency. Trained on vast […]
  • Yuwen Gu, fastkqr: A Fast Algorithm for Kernel Quantile Regression (3/20/2024) - When: Friday, March 22, from 2:00 PM to 3:00 PM Where: ENGR 045 Abstract: Quantile regression is a powerful tool for robust and heterogeneous learning that has seen applications in a diverse range of applied areas. Its broader application, however, is often hindered by the substantial computational demands arising from the nonsmooth quantile loss function. […]
  • Caiwen Ding, Co-Designing Algorithms and Hardware for Efficient Machine Learning (ML): Advancing the Democratization of ML (3/6/2024) - When: Friday, March 8th, from 2:00 PM to 3:00 PM Where: ENGR 045 Abstract: The rapid deployment of ML has witnessed various challenges such as prolonged computation and high memory footprint on systems. In this talk, we will present several ML acceleration frameworks through algorithm-hardware co-design on various computing platforms. The first part presents a […]