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.
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.
Associated Disciplines
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Associated Programs
Associated Faculty
Primary Research Interests
- Formal Methods, Verification, and Synthesis
- Trusted Computing
- System-Level Design Languages and Semantics
- Specification Languages
Primary Research Interests
- Knowledge Discovery
- Data Mining
- Machine Learning
- Expert Systems
- Reasoning Under Uncertainty
Primary Research Interests
- Algorithm Design and Analysis
- Combinatorial Optimizations
- Graph Algorithms
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
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.
Core Coursework (MS)
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Elective Coursework (MS)
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Explore: EECS Courses
