Associated Faculty
Our research in computation foundations investigates the fundamental principles that define the power and limits of computation.
We explore rigorous mathematical models, algorithmic reasoning, and theoretical frameworks that provide the intellectual backbone for advances across artificial intelligence, cybersecurity, systems, and data science. By developing new techniques to analyze efficiency, scalability, and optimization, researchers ensure that both emerging and established technologies are built on sound, provable principles.
Focus Areas
Theory of Computation
Our work in theory of computation examines automata, formal languages, and computability to better understand the capabilities and inherent limitations of computing systems. Faculty explore new models of computation and novel ways to formalize reasoning about algorithmic processes. This research helps answer foundational questions — such as what can or cannot be computed — while also providing tools that inform areas like cryptography, secure systems, and the design of resilient algorithms.
Algorithms and Computational Complexity
In algorithms and computational complexity, our research explores approximation methods, randomized algorithms, distributed and parallel computation, and complexity theory. We create new ways to reason about efficiency, scalability, and optimization in computing through developing rigorous models and provable guarantees. These advances deepen the theoretical foundations of the discipline and shape practical solutions in areas such as secure communication, data analysis, and large-scale network design.
Earn a BS in Computer Science and gain the mathematical and analytical skills to design scalable solutions, optimize performance, and drive innovation in fields ranging from secure systems to data-intensive applications.