Theory of Computing


EECS researchers are advancing the techniques for analyzing time and space complexity of software systems. They extend functional language technology, closing the gap between high level specifications and highly efficient implementations. Research in this area contributes to the understanding of basic techniques for specifying mathematical structures for describing software artifacts.

 

PhD student John Jakabosky
EECS Professor Arvin Agah, left, and EECS doctoral student Christopher Redford have developed an innovative exchange in which interconnected sensor nodes provide simple summaries to the network in order to minimize power and costs.

Program Objectives

  • Understand mathematical concepts of formal languages.
  • Understand techniques for analyzing time and space complexity of software systems.
  • Understand basic techniques for specifying mathematical structures for describing software artifacts.

Associated Faculty

Perry Alexander
AT&T Foundation Distinguished Professor of Electrical Engineering and Computer Science
Director of the Institute for Information Sciences
 palexand@ku.edu
 785-864-8833
 Perry Alexander's Website
 2022 Eaton Hall

Primary Research Interests

  • Formal Methods, Verification, and Synthesis
  • Trusted Computing
  • System-Level Design Languages and Semantics
  • Specification Languages

Jerzy Grzymala-Busse

Primary Research Interests

  • Data mining
  • Knowledge discovery
  • Machine learning
  • Expert systems
  • Reasoning under uncertainty
  • Rough set theory

Man Kong
Associate Professor Emeritus
 kong@ku.edu

Primary Research Interests

  • Design and Analysis of Algorithms
  • Combinatorial Optimizations
  • Graph Algorithms

Suzanne Shontz

Primary Research Interests

  • High Performance Scientific Computing Algorithms
  • Parallel Unstructured Mesh and Optimization Algorithms
  • Model Order Reduction
  • Computational Medicine
  • Image Processing

Associated Facilities

  • Computational cluster with over 1,000 processors connected to 37 TB of on-line storage



Associated Disciplines

Core Coursework (MS)

Courses

Elective Coursework (MS)

Courses