EECS researchers work with interdisciplinary collaborators to develop computational capabilities enabling research in a variety of scientific disciplines including computational medicine, electronic circuit design, and climate science. Central to this effort is the development of algorithms of all types: numerical, non-numerical, sequential, and parallel. A variety of paradigms are exploited, including artificial intelligence for use with image processing, computer vision, and robotics as well as visualization which is now widely recognized as an integral part of the scientific discovery process, not just a method for displaying final results.
Associated Disciplines
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Associated Programs
Associated Faculty
Primary Research Interests
- Intelligent Systems
- Robotics
- Medical Applications of Artificial Intelligence
- Software Engineering
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
- Information security and privacy, database security
- Information retrieval, Web and online social networks
- Security and privacy issues in smart grid systems
- XML and conventional database systems, data management
Primary Research Interests
- Computer Graphics
- Visualization
- Geometric Modeling
- Technology in Education
Primary Research Interests
- High Performance Scientific Computing Algorithms
- Parallel Unstructured Mesh and Optimization Algorithms
- Model Order Reduction
- Computational Medicine
- Image Processing
Primary Research Interests
- Efficient Algorithms For External Memory
- Compressed Text Indexes and Data Structures
- Data Compression
- Database Access and Data Mining
- Machine Learning and Prediction
Associated Facilities
Advanced Computing Facility cluster with over 350 nodes and 6000 CPU cores connected to 125TB of on-line storage. Some GPUs and phi co-processors are also available as part of the ACF cluster.
Program Objectives
- Understand the design and analysis of numerical algorithms.
- Understand the design and analysis of non-numerical algorithms.
- Understand how to develop algorithms capable of artificial intelligence.
- Understand how to develop algorithms for use in image processing and visualizations of scientific data.
- Understand how to apply the various types of algorithms described above to provide efficient and numerically reliable solutions to real-world problems.
- Have the ability to effectively communicate to impact technological decisions.
Core Coursework (MS)
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Note: Select two of the three 600-level core courses listed above.
Elective Coursework (MS)
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Explore: EECS Courses
