Pathways 2024 participants

Welcome to CSta

We combine Computer Science, Statistics, AI, Data Science, and Cybersecurity to enhance multidisciplinary learning and research for undergrads and grads. Cross campus and industry collaborations involve faculty, students, scientists, artists, health care researchers, historians, and engineers.

Undergraduate & Graduate Courses

See our courses in Computer Science, Statistics, Data Science, and Cybersecurity, ranging from computing foundations to theory and statistics to systems and artificial intelligence.

courses
A monitor with code

Undergraduate Programs

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

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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.

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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

Our research and academics help serve a global community. The Computer Science and Statistics Department collaborates with URI’s International Engineering Program (IEP) and the Department of Languages to offer the unique International Computer Science Program (ICSP).

Announcements

  • Alina Jade Barnett [Talk] Alina Jade Barnett: Inherently Interpretable Deep Learning Models (3/5/2026) - When: Friday, March 13, 3:00 PM Where: Tyler 055 Abstract AI models now perform high-stakes tasks traditionally reserved for skilled professionals, often surpassing human expert performance. Despite these advances, the “black box” (i.e., uninterpretable) nature of many machine learning algorithms poses significant challenges. Opaque models resist troubleshooting, cannot justify their decisions, and lack accountability—limitations that […]
  • [Talk] Chenyang Zhong: Faithful and Efficient Synthetic Data Generation via Penalized Optimal Transport Network (2/27/2026) - When: Wednesday, March 4, 3:00 PM Where: Pharmacy 240 Abstract The generation of synthetic data whose distributions faithfully emulate the true data-generating mechanism is of critical importance in modern statistics and data science, with applications ranging from systematic model evaluation to augmenting limited datasets. While Wasserstein Generative Adversarial Networks have shown promise in this area, […]
  • [Talk] Ruyu Zhou: Differential Privacy and Statistics: Privatized Inference and the Inherent Privacy of Sampling (2/26/2026) - When: Friday, March 6, 3:00 PM Where: Tyler 055 Abstract Privacy-preserving data analysis has become a central challenge in modern statistics, with Differential Privacy (DP) emerging as the gold standard for protecting individual-level information. In this talk, I will present two projects at the intersection of DP and statistics. First, focusing on privatized inference, I […]
  • IACR [Talk] Data and Discussion DS event: Academic and Professional Opportunities (2/25/2026) - When: (Date Change) Friday, April 3, Time TBA Where: TBA Abstract Join us for an engaging Data Science event featuring Alena Korshunova (MBA), currently a Business Intelligence Analyst at FM Global, who will share insights into her career path and experience working in industry. This is a wonderful opportunity to learn about real-world applications of […]
  • Mike Conti [Talk] Mike Conti: Analysis of Early Interventions to Retain Underrepresented Students in Computer Science (2/19/2026) - When: Friday, February 27, 3:00 PM Where: Changed to Zoom Abstract Computer science, like many STEM disciplines, faces persistent challenges in recruiting and retaining women and individuals from racially and ethnically minoritized backgrounds. This study examines whether targeted interventions can produce sustained improvements in academic performance and sense of belonging among these underrepresented groups. By […]
  • [Talk] Efficient Gaussian Process Surrogates for Blackbox Optimization and Posterior Approximation (2/18/2026) - When: Friday, February 20, 11:00 AM Where: Pharmacy 240 Abstract In this talk, we explore efficient Gaussian process surrogate modeling in two distinct contexts: bandit optimization and blackbox posterior approximation. For optimization, we propose novel noise-free Bayesian optimization strategies that incorporate a random exploration step to enhance the accuracy of Gaussian process surrogate models. The […]
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