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Research Clusters & M.S. Focus Areas
The Electrical Engineering and Computer Science Department has many associated research clusters, each of which is conducting cutting edge research in its area of study.
Students pursuing a Master's degree are encoraged to choose an academic focus area which is aligned with one of these departmental research clusters (with the exception being the MSIT focus areas, which are not research driven).
To find out more about each of our research clusters and their associated M.S. focus areas select them from the list to the right.
Applied Electromagnetics
EECS Professor Ron Hui has more than 16 U.S. patents for his innovations in biosensors, photonic devices, and optical communication systems.
EECS researchers investigate electromagnetic phenomena-as described by Maxwell's theory-including radiation, propagation, and scattering. They develop mathematical tools to analyze and evaluate electromagnetic solutions to practical electrical engineering devices, systems, and problems. EECS research in Applied Electromagnetics encompasses communications and sensing.
Associated Disiplines
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Associated Faculty
| Christopher Allen | Lightwave/Photonics Systems and Devices, Radar Systems Design and Analysis |
| Rongqing Hui | Optical/RF Measurement and Bioscensors, Novel Photonic Devices, Optical Communication Systems |
| Kenneth Demarest | Antennas and Lightwave Systems |
| James Stiles | Radar Remote Sensing of Vegetation, Propagation and Scattering in Random Media, Ground-Penetrating Radar, Radar Signal Processing, Applications of Information and Estimation Theory in Remote Sensing |
| Sarah Seguin | Electromagnetic Compatibility (EMC), Unintentional and Intentional Electromagnetic Interference (EMI), Electromagnetic Environmental Effects of Carbon-Fiber Composites, Radar Systems, Antenna Design |
Associated Facilities
- Optical spectrum analyzer
- 50GHz microwave network analyzer
- 40GHz digital oscilloscope
- Tunable laser sources and optical filters
- 40Gb/s and 12 Gb/s BERTs
- Electro-optic modulators, WDM multiplexers, demultiplexers
- High-speed photodetectors
- Commercial WDM systems
- High-speed digital T/R rooftop antenna
- 360 km of fiber installed for systems-level testing
- DSP rapid prototyping system
- Circuit board fabrication facility
- Logic analyzers
- Network analyzers
- Spectrum analyzers, oscilloscopes, and function generators
- Prototype PC board fabrication tools
- RF signal generators
- Variety of DSP and EM design tools
Program Objectives
- Provide a firm understanding of electromagnetic phenomena—as described by Maxwell’s theory—including radiation, propagation, and scattering.
- Provide the mathematical tools required to analyze and evaluate electromagnetic solutions to practical electrical engineering devices, systems, and problems.
- Provide a rich understanding of how electromagnetic phenomenon is applied to create engineering solutions for problems such as communications, computation, and sensing.
Core Coursework (MS)
| EECS 622 Microwave and Radio Transmission Systems |
| EECS 721 Antennas |
| EECS 723 Microwave Engineering |
| EECS 820 Advanced Electromagnetics |
Elective Coursework (MS)
| EECS 611 Electromagnetic Compatibility |
| EECS 628 Fiber Optic Communication Systems |
| EECS 713 High-Speed Digital Circuit Design |
| EECS 725 Introduction to Radar Systems |
| EECS 728 Fiber-optic measurement and sensors |
| EECS 781 Numerical Analysis I |
| EECS 782 Numerical Analysis II |
| EECS 823 Microwave Remote Sensing |
| EECS 825 Radar Systems |
| EECS 828 Advanced Fiber-Optic Communications |
| EECS 861 Random Signals and Noise |
| EECS 862 Principles of Digital Communication Systems |
| EECS 864 Multiwavelength Optical Networks |
| EECS 929 Electromagnetic Propagation and Scattering in Random Media |
| EECS 965 Detection and Estimation Theory |
| EECS 967 Mathematical Optimization with Communications Applications |
| EECS 820 Advanced Electromagnetics |
| MATH 646 Complex Variables |
| MATH 647 Applied Partial Differential Equations |
| MATH 648 Calculus of Variations and Integral Equations |
| MATH 790 Linear Algebra II |
Communications Systems
EECS Associate Professor Erik Perrins and his students are developing two-way communication systems for Smart Grids that will utilize existing wireless services.
EECS researchers integrate leading-edge research with practical implementation across a wide range of challenging communications systems problems. Current research efforts include delay-sensitive, energy-efficient wireless communication, multi-user communication systems and networks, advanced modulation techniques, channel coding, and synchronization. Building on a long and storied history in communication innovation, EECS researchers are developing the future Internet, mobile apps, optical sensors, RFID tags, and spectrum measurement and management techniques.
Associated Disiplines
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Associated Faculty
| Shannon Blunt | Adaptive Signal Processing for Radar and Communications, Array Processing, Interference Cancellation, Waveform Diversity/Design for Physical Systems, Biomedical Image Processing |
| Joseph Evans | High-Performance Networks, Mobile Networking and Wireless Systems, Pervasive Computing Systems, System Implementations |
| Victor Frost | Communication Systems and Networks |
| Rongqing Hui | Optical/RF Measurement and Bioscensors, Novel Photonic Devices, Optical Communication Systems |
| Lingjia Liu | Delay-sensitive and energy-efficient communications over wireless networks, Multi-user communication systems/networks, Cooperative communication systems/networks, Interference coordination/mitigation |
| Erik Perrins | Digital Communication Theory, Advanced Modulation Techniques, Channel Coding, Synchronization, Multiple-Input Multiple-Output Communications |
| Glenn Prescott | Software Radio Systems, Spread Spectrum and Military Communication Systems, Radio and Radar Signal Processing, DSP Applications in Acoustics and Radio Signals, Wireless Communication Systems |
| James Sterbenz | Computer networks and communication; Network science, simulation, and analysis, Future Internet architecture, design, and topology, Resilient, survivable, and disruption tolerant networks, Mobile wireless networks and MANET routing, Disruption and delay tolerant end-to-end transport |
Associated Facilities
- Optical spectrum analyzer
- 50GHz microwave network analyzer
- 40GHz digital oscilloscope
- Tunable laser sources and optical filters
- 40Gb/s and 12 Gb/s BERTs
- Electro-optic modulators, WDM multiplexers, demultiplexers
- High-speed photodetectors
- Commercial WDM systems
- High-speed digital T/R rooftop antenna
- 360 km of fiber installed for systems-level testing
- DSP rapid prototyping system
- Circuit board fabrication facility
- Logic analyzers
- Network analyzers
- Spectrum analyzers, oscilloscopes, and function generators
- Prototype PC board fabrication tools
- RF signal generators
- Communications link simulator- Simulink
- Variety of DSP and EM design tools
Program Objectives
- Understand fundamental principles and underlying technologies of communication systems.
- Understand how to apply communication theory principles in the design and analysis of communication systems.
- Understand how to realize communication systems, including simulation and efficient implementation.
Core Coursework (MS)
| EECS 861 Random Signals and Noise |
| EECS 862 Principles of Digital Communication Systems |
| EECS 844 Adaptive Signal Processing |
| EECS 865 Wireless Communication Systems |
Note: Students must take either EECS 865 or EECS 728 to fulfill their core coursework requirement.
Elective Coursework (MS)
| EECS 622 Microwave and Radio Transmission Systems |
| EECS 628 Fiber Optic Communication Systems |
| EECS 721 Antennas |
| EECS 723 Microwave Engineering |
| EECS 728 Fiber-optic measurement and sensors |
| EECS 744 Communications and Radar Digital Signal Processing |
| EECS 745 Implementation of Networks |
| EECS 766 Resource Sharing for Broadband Access Networks |
| EECS 769 Information Theory |
| EECS 780 Communication Networks |
| EECS 828 Advanced Fiber-Optic Communications |
| EECS 863 Network Analysis, Simulation, and Measurements |
| EECS 864 Multiwavelength Optical Networks |
| EECS 869 Error Control Coding |
| EECS 881 High-Performance Networking |
| EECS 882 Mobile Wireless Networking |
| EECS 888 Internet Routing Architectures |
| EECS 965 Detection and Estimation Theory |
| EECS 967 Mathematical Optimization with Communications Applications |
| EECS 983 Resilient and Survivable Networking |
| EECS 820 Advanced Electromagnetics |
Computer Systems Design
EECS Assistant Professor Prasad Kulkarni, an NSF CAREER Award Winner, is building more secure and better performing software systems.
EECS researchers design, implement, and verify software and hardware components for high assurance systems. They develop high-level programming language design, language type systems, and specification and verification of language semantics, ensuring highly reliable and secure software. From small embedded elements to large distributed computing environments, the breadth of EECS research addresses all computer systems and aspects of the system lifecycle. Researchers focus on performance, reliability, and power characteristics and their trade-offs to engineer exceptional systems.
Associated Disiplines
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Associated Faculty
| Perry Alexander | Formal Methods Application To System-Level Design |
| Xin Fu | Computer Architecture, Hardware Reliability, The Impact of Nano-Scale Technology Scaling On Multi-Core Processors, On-Chip Interconnection Network |
| Andy Gill | Functional Programming, Software Engineering, Compilers, Systems, FPGAs |
| Prasad Kulkarni | Compilers, Virtual Machines, Runtime Systems, Computer Architecture |
| Gary Minden | Digital systems, Microprocessors, Artificial intelligence |
| Douglas Niehaus | Real-Time and Embedded Systems, System and Network Performance Evaluation, High-Performance Simulation of Computer Systems and Networks, Concurrent and Distributed Programming Tools and Environments |
Associated Facilities
- Smart GDB debugging environment
- C, C++, and GDB and associated support tools
- Rosetta specification language
- Raskell evaluation environment
- PVS, SPIN, Isabelle, HOL, and SAT analysis software
- Protocols for ad-hoc sensor networks
- Xilinx and Altera FPGA/SoC prototyping systems
- Synplicity and Xilinx FPGA synthesis tools
- ModelSim VHDL/Verilog simulation tools
- Bugzilla and CVS project management tools
Hardware and software design tools for:
- Specification languages and semantics
- Language interpreters, analyzers, and compilers
- Real-time and distributed operating systems
- Distributed simulation systems
- Embedded software and hardware systems
- FPGA-based OS primitives
- Reconfigurable Systems-on-Chip
- VHDL/Verilog modeling, simulation, and synthesis
Program Objectives
- Acquire the ability to design, implement, and verify the various software and hardware components in systems whose primary constituents include computers.
- Understand the foundations of high-level programming language design, language type systems, and specification and verification of language semantics.
- Understand the process of generating and running software that realizes the performance, security, privacy, and real-time goals of the underlying problem domain.
- Understand the fundamental principles of operating systems and other runtime environments.
- Understand the design and implementation of modern computer hardware architectures and their performance, reliability, and power characteristics and trade-offs.
Core Coursework (MS)
| EECS 750 Advanced Operating Systems |
| EECS 762 Programming Language Foundation I |
| EECS 743 Advanced Computer Architecture |
| EECS 768 Virtual Machines |
Elective Coursework (MS)
| EECS 643 Advanced Computer Organization |
| EECS 645 Computer Architecture |
| EECS 662 Programming Languages |
| EECS 665 Compiler Construction |
| EECS 678 Introduction to Operating Systems |
| EECS 716 Formal Language Theory |
| EECS 735 Automated Theorem Proving |
| EECS 739 Scientific Parallel Computing |
| EECS 742 Static Analysis |
| EECS 753 Embedded and Real Time Computer Systems |
| EECS 755 Software Modeling and Analysis |
| EECS 761 Programming Paradigms |
| EECS 763 Introduction to Multiprocessor Systems on Chip (MPSoC) |
| EECS 776 Functional Programming and Domain Specific Languages |
| EECS 843 Programming Language Foundation II |
| EECS 876 Advanced Topics in Functional Languages |
Computing in the Biosciences
EECS researchers are searching for the causes of cancer and Autism, among numerous other projects supported by the high performance computing facility. The Bioinformatics Computing Facility is undergoing a major renovation that will increase computing power by 20 fold.
EECS researchers examine fundamental problems in biology and how principles and technologies of computing can be applied to life sciences. They advance computational methods and tools for applications in biological, biochemical, and medical fields. Interdisciplinary research in biosciences at KU includes modeling, analysis, data management, and algorithm optimization.
Associated Disiplines
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Associated Faculty
| Jerzy Grzymala-Busse | Knowledge Discovery, Data Mining, Machine Learning, Expert Systems, Reasoning Under Uncertainty |
| Jun Huan | Machine Learning and Data Mining, Statistical Learning, Bioinformatics, Biomedical Informatics, Health Informatics |
| James Miller | Scientific and Information Visualization, Visual Analytics, Geometric Modeling, Technology in Education, Mobile/Web-Based Applications |
| Arvin Agah | Intelligent Systems, Robotics, Medical Applications of Artificial Intelligence, Software Engineering |
Associated Facilities
Artificial intelligence development tools and languages:
- Lisp, CLOS, CLIPS, Prolog, GBB, OPS, MEM-1
Computational clusters:
- Linux cluster with 64 dual processor 3.2 Ghz Xeon processors and 64 dual core 2.8 Ghz Xeon processors for a total of 384 processors 37 TB of on-line storage Reconfigurable floating-point gate arrays
Bioinformatics software including:
- ClustalW, Emboss GENSCAN, hmmer, Ncbi toolkit
Data mining tools:
- SNOB, Cobweb, ID3, C4.5, statistical analysis packages, LERS Genomics Unified Schema installation
Information retrieval and Web tools:
- KUIR Information Retrieval Library
- Parallel development tools including MPI, Pfortran, and PC
- Parallel GROMOS for molecular dynamics
Program Objectives
- Understand basic concepts and fundamental problems in biology.
- Understand fundamental principles and technologies of computing in biosciences.
- Understand how to apply and adapt computational methods to address life sciences problems, particularly bioinformatics problems.
- Have the ability to effectively communicate to impact technological decisions.
Core Coursework (MS)
| EECS 730 Introduction to Bioinformatics |
| EECS 738 Machine Learning |
| EECS 831 Introduction to Systems Biology |
| EECS 837 Data Mining |
Elective Coursework (MS)
| EECS 638 Fundamentals of Expert Systems |
| EECS 649 Introduction to Artificial Intelligence |
| EECS 660 Fundamentals of Computer Algorithms |
| EECS 672 Introduction to Computer Graphics |
| EECS 718 Graph Algorithms |
| EECS 739 Scientific Parallel Computing |
| EECS 740 Digital Image Processing |
| EECS 741 Computer Vision |
| EECS 746 Database Systems |
| EECS 767 Information Retrieval |
| EECS 773 Advanced Graphics |
| EECS 774 Geometric Modeling |
| EECS 775 Visualization |
| EECS 781 Numerical Analysis I |
| EECS 782 Numerical Analysis II |
| EECS 830 Advanced Artificial Intelligence |
| EECS 833 Neural Networks and Fuzzy Systems |
| EECS 835 Protein Bioinformatics |
| EECS 838 Applications of Machine Learning in Bioinformatics |
| EECS 839 Mining Special Data |
| EECS 844 Adaptive Signal Processing |
| EECS 861 Random Signals and Noise |
| EECS 867 Statistical Natural Language Processing |
| EECS 940 Theoretic Foundation of Data Analysis |
| EECS 965 Detection and Estimation Theory |
| EECS 967 Mathematical Optimization with Communications Applications |
Information Assurance and Management
Note:This area is not associated with research occurring at the Electrical Engineering and Computer Science Department. It is strictly an academic area associated with the MSIT program.
Associated Disiplines
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Associated Faculty
| Perry Alexander | Formal Methods Application To System-Level Design |
| Fengjun Li | Information Security and Privacy, Healthcare Informatics, Smart Grids, Network Security, Applied Cryptography |
| Bo Luo | 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 |
| Hossein Saiedian | Software Engineering Including Software Process Improvement, Formalism in Software Development, Object-Oriented Software Development, Software Engineering Education, Software Architecture |
| James Sterbenz | Computer networks and communication; Network science, simulation, and analysis, Future Internet architecture, design, and topology, Resilient, survivable, and disruption tolerant networks, Mobile wireless networks and MANET routing, Disruption and delay tolerant end-to-end transport |
Program Objectives
The focus area in information security and assurance provides technical knowledge and practical skills in the science and methodologies for identifying important information assets, securing and protecting such assets, and assuring their availability for authorized users.Core Coursework (MS)
| EECS 710 Information Security and Assurance |
| EECS 780 Communication Networks |
| EECS 810 Software Engineering and Management |
| EECS 811 IT Project Management |
| EMGT 806 Finance for Engineers |
| EMGT 821 Strategic Analysis of Technology Project |
Elective Coursework (MS)
| EECS 711 Security Management and Audit |
| EECS 712 Network Security and its Application |
| EECS 746 Database Systems |
| EECS 882 Mobile Wireless Networking |
| EECS 767 Information Retrieval |
Intelligent Informatics
EECS Associate Professor James Miller and EECS student David Wolfe develop interactive educational tools. Prof. Miller helped lead interdisciplinary research to create a virtual environment that taught social skills to students with Autism Spectrum Disorders.
EECS researchers are developing new tools and methods in data collection, integration, cleansing, and representation. In addition to innovative data gathering and management, EECS researchers advance all aspects of modeling, including model construction, selection, averaging, evaluation, and interpretation. The multidisciplinary research identifies and deploys intelligent informatics components for efficient solutions to real-world problems in medicine, science, industry, and other numerous other fields.
Associated Disiplines
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Associated Faculty
| Jerzy Grzymala-Busse | Knowledge Discovery, Data Mining, Machine Learning, Expert Systems, Reasoning Under Uncertainty |
| Arvin Agah | Intelligent Systems, Robotics, Medical Applications of Artificial Intelligence, Software Engineering |
| Jun Huan | Machine Learning and Data Mining, Statistical Learning, Bioinformatics, Biomedical Informatics, Health Informatics |
| Nancy Kinnersley | Design and Analysis of Algorithms, Graph Theory and Graph Algorithms, Computer Science Education, Discrete Mathematics |
| Man Kong | Algorithm Design and Analysis, Combinatorial Optimizations, Graph Algorithms |
| Bo Luo | 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 |
| James Miller | Scientific and Information Visualization, Visual Analytics, Geometric Modeling, Technology in Education, Mobile/Web-Based Applications |
Associated Facilities
Multiagent development tools:
- ACCS, C++, CORBA, Java
Information retrieval and Web tools:
- KUIR Information Retrieval Library, Php, XMLSpy, MySQL, Perl
Data Mining Tools:
- SNOB, Cobweb, ID3, C4.5, statistical analysis packages
Artificial intelligence development tools and languages:
- Lisp, CLOS, CLIPS, Prolog, GBB, OPS, MEM-1
Image processing and computer vision tools:
- KUIM Image Processing Library, high-speed video, and data cable/fiber link
Human-intelligent system interaction tools:
- Mobile robots, VR user interface, head-mounted display, force feedback joysticks
- PoepleBot, two Nomad Scouts, three Kheperas, and one Pioneer robot
Software packages for virtual prototyping and kinematics and dynamics modeling, such as the visualNastran 4D and Working Model.
Program Objectives
- Understand fundamental principles and algorithms of intelligent informatics.
- Understand the data collection, data integration, data cleansing, data representation, model construction, model selection, model averaging, model evaluation, and model interpretation components in intelligent informatics.
- Understand how to identify intelligent informatics components and provide efficient solutions in solving real-world problems.
- Have the ability to effectively communicate to impact technological decisions.
Core Coursework (MS)
| EECS 738 Machine Learning |
| EECS 741 Computer Vision |
| EECS 767 Information Retrieval |
| EECS 837 Data Mining |
Elective Coursework (MS)
| EECS 638 Fundamentals of Expert Systems |
| EECS 649 Introduction to Artificial Intelligence |
| EECS 662 Programming Languages |
| EECS 672 Introduction to Computer Graphics |
| EECS 716 Formal Language Theory |
| EECS 718 Graph Algorithms |
| EECS 735 Automated Theorem Proving |
| EECS 741 Computer Vision |
| EECS 746 Database Systems |
| EECS 747 Mobile Robotics |
| EECS 755 Software Modeling and Analysis |
| EECS 761 Programming Paradigms |
| EECS 764 Analysis of Algorithms |
| EECS 773 Advanced Graphics |
| EECS 774 Geometric Modeling |
| EECS 775 Visualization |
| EECS 830 Advanced Artificial Intelligence |
| EECS 839 Mining Special Data |
| EECS 841 Computer Vision |
| EECS 867 Statistical Natural Language Processing |
| EECS 940 Theoretic Foundation of Data Analysis |
| MATH 727 Probability Theory |
| MATH 728 Statistics |
Internet Engineering and Management
Note:This area is not associated with research occurring at the Electrical Engineering and Computer Science Department. It is strictly an academic area associated with the MSIT program.
Associated Disiplines
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Associated Faculty
| James Sterbenz | Computer networks and communication; Network science, simulation, and analysis, Future Internet architecture, design, and topology, Resilient, survivable, and disruption tolerant networks, Mobile wireless networks and MANET routing, Disruption and delay tolerant end-to-end transport |
Program Objectives
The focus area in Internet engineering covers important topics related to computer networks, the Internet and Web, wireless and mobile networking, networking performance tuning and routing architectures, information and network security, information retrieval, storage and transmission, and other important topics related to Internet applications and operations.Core Coursework (MS)
| EECS 710 Information Security and Assurance |
| EECS 780 Communication Networks |
| EECS 810 Software Engineering and Management |
| EECS 811 IT Project Management |
| EMGT 806 Finance for Engineers |
| EMGT 821 Strategic Analysis of Technology Project |
Elective Coursework (MS)
| EECS 712 Network Security and its Application |
| EECS 746 Database Systems |
| EECS 767 Information Retrieval |
| EECS 881 High-Performance Networking |
| EECS 882 Mobile Wireless Networking |
Languages and Semantics
EECS Assistant Professor Andy Gill (left) is creating powerful, innovative tools that provide greater transparency and scrutiny when building large complex computer systems.
EECS researchers develop cutting-edge programming techniques along with efficient language interpreters and compilers to ensure efficient, reliable, and secure software in high assurance systems. They extend functional language technology, closing the gap between high level specifications and highly efficient implementations. New technologies have diverse application areas in telemetry, high performance computing and real-time systems.
Associated Disiplines
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Associated Faculty
| Perry Alexander | Formal Methods Application To System-Level Design |
| Jerzy Grzymala-Busse | Knowledge Discovery, Data Mining, Machine Learning, Expert Systems, Reasoning Under Uncertainty |
| Andy Gill | Functional Programming, Software Engineering, Compilers, Systems, FPGAs |
| Nancy Kinnersley | Design and Analysis of Algorithms, Graph Theory and Graph Algorithms, Computer Science Education, Discrete Mathematics |
Associated Facilities
- Smart GDB debugging environment
- C, C++, GDB and associated support tools
- Rosetta specification language
- Raskell evaluation environment
- PVS, SPIN, Isabelle, HOL and SAT analysis software
- Protocols for ad hoc sensor networks
- Xilinx and Altera FPGA/SoC prototyping systems
- Synplicity and Xilinx FPGA synthesis tools
- ModelSim VHDL/Verilog simulation tools
- Bugzilla and CVS project management tools
Hardware and software design tools for:
- Specification languages and semantics
- Language interpreters, analyzers, and compilers
- Real-time and distributed operating systems
- Distributed simulation systems
- Embedded software and hardware systems
- FPGA-based OS primitives
- Reconfigurable Systems-on-chip
- VHDL/Verilog modeling, simulation and synthesis
Program Objectives
- Understand the design of languages and language features.
- Understand how to define and manipulate mathematical definitions of language semantics.
- Understand cutting-edge programming techniques using advanced techniques.
- Understand the development of efficient language interpreters and compilers.
Core Coursework (MS)
| EECS 755 Software Modeling and Analysis |
| EECS 762 Programming Language Foundation I |
| EECS 776 Functional Programming and Domain Specific Languages |
| EECS 876 Advanced Topics in Functional Languages |
Elective Coursework (MS)
| EECS 649 Introduction to Artificial Intelligence |
| EECS 660 Fundamentals of Computer Algorithms |
| EECS 662 Programming Languages |
| EECS 716 Formal Language Theory |
| EECS 718 Graph Algorithms |
| EECS 735 Automated Theorem Proving |
| EECS 738 Machine Learning |
| EECS 741 Computer Vision |
| EECS 742 Static Analysis |
| EECS 746 Database Systems |
| EECS 761 Programming Paradigms |
| EECS 767 Information Retrieval |
| EECS 818 Software Architecture |
| EECS 819 Cryptography |
| EECS 830 Advanced Artificial Intelligence |
| EECS 837 Data Mining |
| EECS 839 Mining Special Data |
| EECS 841 Computer Vision |
| EECS 843 Programming Language Foundation II |
| EECS 867 Statistical Natural Language Processing |
| EECS 940 Theoretic Foundation of Data Analysis |
| EECS 955 Theoretical Foundations of Software Construction |
| EECS 743 Advanced Computer Architecture |
| EECS 764 Analysis of Algorithms |
Network Engineering
EECS Distinguished Professor Victor Frost has contributed to the design and analysis of technology that supports the Internet and other vital communication networks. He has served as principal or co-investigator on more than 80 projects.
EECS researchers advance communication networks and the underlying physical transmission of information. Their varied expertise enables them to develop architecture, algorithms, protocols, and other advanced networking concepts with an emphasis on the lower to middle layers of the protocol stack. EECS research in this area includes the development of resilient and survivable networks for the future Internet.
Associated Disiplines
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Associated Faculty
| Joseph Evans | High-Performance Networks, Mobile Networking and Wireless Systems, Pervasive Computing Systems, System Implementations |
| Victor Frost | Communication Systems and Networks |
| Lingjia Liu | Delay-sensitive and energy-efficient communications over wireless networks, Multi-user communication systems/networks, Cooperative communication systems/networks, Interference coordination/mitigation |
| Gary Minden | Digital systems, Microprocessors, Artificial intelligence |
| James Sterbenz | Computer networks and communication; Network science, simulation, and analysis, Future Internet architecture, design, and topology, Resilient, survivable, and disruption tolerant networks, Mobile wireless networks and MANET routing, Disruption and delay tolerant end-to-end transport |
Associated Facilities
- Routers
- Connections to Sprint fiber optic backbone
- Connections to the GENI and GpENI experimental testbeds
- Software radios
- RFID performance benchmarking facilities
- Discrete Event Simulator - Extend
- Network Simulator ns-3
Program Objectives
- Understand fundamental principles of communication networks and the underlying physical transmission of information, with emphasis on the lower to middle layers of the protocol stack.
- Understand the lower to middle layer architecture, design, algorithms, protocols, and performance issues.
- Have the ability to effectively communicate advanced networking concepts.
Core Coursework (MS)
| EECS 745 Implementation of Networks |
| EECS 780 Communication Networks |
| EECS 861 Random Signals and Noise |
| EECS 863 Network Analysis, Simulation, and Measurements |
Note: EECS 780 is not required for students who have taken EECS 563 as a KU undergraduate, in that case any another course from the elective list can be used as the 4th core course; and EECS 780 may be used as an elective.
Elective Coursework (MS)
| EECS 622 Microwave and Radio Transmission Systems |
| EECS 628 Fiber Optic Communication Systems |
| EECS 710 Information Security and Assurance |
| EECS 711 Security Management and Audit |
| EECS 712 Network Security and its Application |
| EECS 744 Communications and Radar Digital Signal Processing |
| EECS 766 Resource Sharing for Broadband Access Networks |
| EECS 769 Information Theory |
| EECS 828 Advanced Fiber-Optic Communications |
| EECS 844 Adaptive Signal Processing |
| EECS 862 Principles of Digital Communication Systems |
| EECS 864 Multiwavelength Optical Networks |
| EECS 865 Wireless Communication Systems |
| EECS 869 Error Control Coding |
| EECS 881 High-Performance Networking |
| EECS 882 Mobile Wireless Networking |
| EECS 888 Internet Routing Architectures |
| EECS 965 Detection and Estimation Theory |
| EECS 967 Mathematical Optimization with Communications Applications |
| EECS 983 Resilient and Survivable Networking |
| EECS 765 Introduction to Cryptography and Computer Security |
| EECS 866 Network Security |
| MATH 725 Graph Theory |
Network Systems
EECS graduate student Qian Wang measures signal power while developing innovative long-range detection techniques to locate mobile improvised explosive devices.
EECS researchers continue their pioneering investigations in the fundamental structure of communication networks and network application software. Researchers focus on the architecture, design, algorithms, and protocol issues with a special focus on the middle to upper layers of the protocol stack. EECS research has produced innovative approaches to resilient networking and protocols that will permit greater spectrum sharing and more efficient use of the finite resource.
Associated Disiplines
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Associated Faculty
| Gary Minden | Digital systems, Microprocessors, Artificial intelligence |
| Victor Frost | Communication Systems and Networks |
| Joseph Evans | High-Performance Networks, Mobile Networking and Wireless Systems, Pervasive Computing Systems, System Implementations |
| Douglas Niehaus | Real-Time and Embedded Systems, System and Network Performance Evaluation, High-Performance Simulation of Computer Systems and Networks, Concurrent and Distributed Programming Tools and Environments |
| James Sterbenz | Computer networks and communication; Network science, simulation, and analysis, Future Internet architecture, design, and topology, Resilient, survivable, and disruption tolerant networks, Mobile wireless networks and MANET routing, Disruption and delay tolerant end-to-end transport |
Associated Facilities
- Routers
- Computational cluster with over 1,000 processors connected to 37 TB of on-line storage
- Discrete Event Simulator - Extend
- Network Simulator ns-3
- Connections to the GENI and GpENI experimental testbeds
- Connections to Sprint fiber optic backbone
- Software radios
Program Objectives
- Understand fundamental principles of communication networks, the science of their structure, and application software with emphasis on the middle to upper layers of the protocol stack.
- Understand the networked applications and middle to upper layers architecture, design, algorithms, and protocol issues.
- Have the ability to effectively communicate advanced networking concepts.
Core Coursework (MS)
| EECS 718 Graph Algorithms |
| EECS 745 Implementation of Networks |
| EECS 750 Advanced Operating Systems |
| EECS 780 Communication Networks |
Note: EECS 780 is not required for students who have taken EECS 563 as a KU undergraduate, in that case any another course from the elective list can be used as the 4th core course; and EECS 780 may be used as an elective.
Elective Coursework (MS)
| EECS 710 Information Security and Assurance |
| EECS 711 Security Management and Audit |
| EECS 712 Network Security and its Application |
| EECS 746 Database Systems |
| EECS 753 Embedded and Real Time Computer Systems |
| EECS 766 Resource Sharing for Broadband Access Networks |
| EECS 767 Information Retrieval |
| EECS 780 Communication Networks |
| EECS 819 Cryptography |
| EECS 861 Random Signals and Noise |
| EECS 862 Principles of Digital Communication Systems |
| EECS 863 Network Analysis, Simulation, and Measurements |
| EECS 864 Multiwavelength Optical Networks |
| EECS 865 Wireless Communication Systems |
| EECS 869 Error Control Coding |
| EECS 881 High-Performance Networking |
| EECS 882 Mobile Wireless Networking |
| EECS 888 Internet Routing Architectures |
| EECS 967 Mathematical Optimization with Communications Applications |
| EECS 983 Resilient and Survivable Networking |
| EECS 765 Introduction to Cryptography and Computer Security |
| EECS 866 Network Security |
| MATH 725 Graph Theory |
Radar Systems and Remote Sensing
EECS Assistant Professor Sarah Seguin and EECS graduate student Kyle Byers build a radar system to be used on a polar ice cap mission. Dr. Seguin is an expert in electromagnetic compatibility (EMC), radar systems, and antenna design.
EECS researchers explore numerous facets within radar systems including experimental system development, theoretical signal processing, and electromagnetics. Building on a long and storied history in radar innovation, current research delves into multiple-input and multiple-output (MIMO) radar, pulse agility, compressive sensing, adaptive transmission, high-power spectral efficiency, antenna array, and electromagnetic compatibility. KU is internationally known for its radar research and development in climate change.
Associated Disiplines
Explore: DisciplinesAssociated Programs
Associated Faculty
| Christopher Allen | Lightwave/Photonics Systems and Devices, Radar Systems Design and Analysis |
| Shannon Blunt | Adaptive Signal Processing for Radar and Communications, Array Processing, Interference Cancellation, Waveform Diversity/Design for Physical Systems, Biomedical Image Processing |
| Kenneth Demarest | Antennas and Lightwave Systems |
| Rongqing Hui | Optical/RF Measurement and Bioscensors, Novel Photonic Devices, Optical Communication Systems |
| Carlton Leuschen | Radar Sounding, Radar Altimetry, Ground-Penetrating Radar |
| Glenn Prescott | Software Radio Systems, Spread Spectrum and Military Communication Systems, Radio and Radar Signal Processing, DSP Applications in Acoustics and Radio Signals, Wireless Communication Systems |
| Sarah Seguin | Electromagnetic Compatibility (EMC), Unintentional and Intentional Electromagnetic Interference (EMI), Electromagnetic Environmental Effects of Carbon-Fiber Composites, Radar Systems, Antenna Design |
| James Stiles | Radar Remote Sensing of Vegetation, Propagation and Scattering in Random Media, Ground-Penetrating Radar, Radar Signal Processing, Applications of Information and Estimation Theory in Remote Sensing |
Associated Facilities
- Optical spectrum analyzer
- 50GHz microwave network analyzer
- 40GHz digital oscilloscope
- Tunable laser sources and optical filters
- 40Gb/s and 12 Gb/s BERTs
- Electro-optic modulators, WDM multiplexers, demultiplexers
- High-speed photodetectors
- Commercial WDM systems
- High-speed digital T/R rooftop antenna
- 360 km of fiber installed for systems-level testing
- DSP rapid prototyping system
- Circuit board fabrication facility
- Logic analyzers
- Network analyzers
- Spectrum analyzers, oscilloscopes, and function generators
- Prototype PC board fabrication tools
- RF signal generators
- Variety of DSP and EM design tools
Program Objectives
- Describing the basic operating principles, performance characteristics, and block diagrams of various radar systems.
- Comparing the various signal processing algorithms used in modern radar systems.
- Describing electromagnetic propagation, scattering and emission characteristics of natural targets and media as well as discussing the underlying physical properties that determine these characteristics.
Core Coursework (MS)
| EECS 723 Microwave Engineering |
| EECS 725 Introduction to Radar Systems |
| EECS 744 Communications and Radar Digital Signal Processing |
| EECS 820 Advanced Electromagnetics |
| EECS 861 Random Signals and Noise |
Note: Students must take either EECS 720 or EECS 861 to fulfill their core coursework requirement.
Elective Coursework (MS)
| EECS 611 Electromagnetic Compatibility |
| EECS 622 Microwave and Radio Transmission Systems |
| EECS 628 Fiber Optic Communication Systems |
| EECS 644 Introduction to Digital Signal Processing |
| EECS 713 High-Speed Digital Circuit Design |
| EECS 721 Antennas |
| EECS 728 Fiber-optic measurement and sensors |
| EECS 823 Microwave Remote Sensing |
| EECS 825 Radar Systems |
| EECS 844 Adaptive Signal Processing |
| EECS 861 Random Signals and Noise |
| EECS 929 Electromagnetic Propagation and Scattering in Random Media |
| EECS 965 Detection and Estimation Theory |
| EECS 820 Advanced Electromagnetics |
Note(s): If students wish to take both EECS 720 and EECS 861 they may count one course for credit towards fulfulling their elective coursework requirement.
Explore: EECS CoursesRF Systems Engineering
EECS Professor Christopher Allen helps a student mount antennas on a sled bound for Greenland. KU is leading a global research effort to better understand the polar regions and their climatic effects on Earth.
The conveyance of information via electromagnetic propagation is an organizing theme for much of the research activities at KU EECS. For electromagnetic communications and sensing, the problem essentially is one of maximizing the capacity of this information on transmit, and then maximizing the accuracy of information retrieval on receive. The design of these electromagnetic (RF) systems thus require a complex convergence of engineering knowledge, such as electromagnetic propagation and scattering, microwave components and theory, signal processing, estimation and detection theory, and information and coding theory.
Associated Disiplines
Explore: DisciplinesAssociated Programs
Associated Faculty
| Sarah Seguin | Electromagnetic Compatibility (EMC), Unintentional and Intentional Electromagnetic Interference (EMI), Electromagnetic Environmental Effects of Carbon-Fiber Composites, Radar Systems, Antenna Design |
| Christopher Allen | Lightwave/Photonics Systems and Devices, Radar Systems Design and Analysis |
| Victor Frost | Communication Systems and Networks |
| Lingjia Liu | Delay-sensitive and energy-efficient communications over wireless networks, Multi-user communication systems/networks, Cooperative communication systems/networks, Interference coordination/mitigation |
| Erik Perrins | Digital Communication Theory, Advanced Modulation Techniques, Channel Coding, Synchronization, Multiple-Input Multiple-Output Communications |
| Shannon Blunt | Adaptive Signal Processing for Radar and Communications, Array Processing, Interference Cancellation, Waveform Diversity/Design for Physical Systems, Biomedical Image Processing |
| David Petr | Audio Signal Processing, Network Performance |
| James Stiles | Radar Remote Sensing of Vegetation, Propagation and Scattering in Random Media, Ground-Penetrating Radar, Radar Signal Processing, Applications of Information and Estimation Theory in Remote Sensing |
| Glenn Prescott | Software Radio Systems, Spread Spectrum and Military Communication Systems, Radio and Radar Signal Processing, DSP Applications in Acoustics and Radio Signals, Wireless Communication Systems |
Associated Facilities
- Optical spectrum analyzer
- 50GHz microwave network analyzer
- 40GHz digital oscilloscope
- Tunable laser sources and optical filters
- 40Gb/s and 12 Gb/s BERTs
- Electro-optic modulators, WDM multiplexers, demultiplexers
- High-speed photodetectors
- Commercial WDM systems
- High-speed digital T/R rooftop antenna
- 360 km of fiber installed for systems-level testing
- DSP rapid prototyping system
- Circuit board fabrication facility
- Logic analyzers
- Network analyzers
- Spectrum analyzers, oscilloscopes, and function generators
- Prototype PC board fabrication tools
- RF signal generators
- Communications link simulator- Simulink
- Variety of DSP and EM design tools
- Xilinx and Altera FPGA/SoC prototyping systems
- Synplicity and Xilinx FPGA synthesis tools
- ModelSim VHDL/Verilog simulation tools
- Prototype PC board fabrication tools
- Simulink
- Computational cluster with over 1,000 processors connected to 37 TB of on-line storage
Program Objectives
- Understand the propagation of both bounded and unbounded electromagnetic waves.
- Understand the function of microwave components and transmission line theory.
- Understand the design and operation of microwave systems, including receiver and transmitter architecture, as well as antenna performance and function.
- Understand the theory and application of transmitting digital information via electromagnetic propagation.
- Understand the applications of signal processing for filtering , estimating, and detecting signals in a high-interference environment.
- Have the ability to effectively communicate complex, abstract concepts.
Core Coursework (MS)
| EECS 713 High-Speed Digital Circuit Design |
| EECS 723 Microwave Engineering |
| EECS 744 Communications and Radar Digital Signal Processing |
| EECS 861 Random Signals and Noise |
Elective Coursework (MS)
| EECS 662 Programming Languages |
| EECS 721 Antennas |
| EECS 725 Introduction to Radar Systems |
| EECS 823 Microwave Remote Sensing |
| EECS 844 Adaptive Signal Processing |
| EECS 862 Principles of Digital Communication Systems |
| EECS 865 Wireless Communication Systems |
| EECS 869 Error Control Coding |
| EECS 965 Detection and Estimation Theory |
| EECS 967 Mathematical Optimization with Communications Applications |
Note(s): No more than one MSIT courses at the Edwards campus from the following list:
| EECS 710 Information Security and Assurance |
| EECS 780 Communication Networks |
| EECS 810 Software Engineering and Management |
| EECS 811 IT Project Management |
| EECS 711 Security Management and Audit |
| EECS 712 Network Security and its Application |
| EECS 746 Database Systems |
| EECS 767 Information Retrieval |
| EECS 812 Software Requirements Engineering |
| EECS 814 Software Quality Assurance |
| EECS 818 Software Architecture |
| EECS 881 High-Performance Networking |
| EECS 882 Mobile Wireless Networking |
Security and Assurance
EECS Research Associate Professor Daniel Deavours holds his innovative radio frequency identification (RFID) tags. Dr. Deavours is a pioneer in the next-generation tracking technology that ensures safer, more transparent supply chains.
EECS researchers develop, verify, and field high assurance information systems. Expertise includes theoretical modeling, synthesis and verification, security modeling and analysis, network and database security. Additionally, researchers explore user privacy and security issues in centralized, distributed, and Web environments. Expanding leading-edge cyber security and defense mechanisms earned EECS a federal National Center of Academic Excellence in Information Assurance Education designation.
Associated Disiplines
Explore: DisciplinesAssociated Programs
Associated Faculty
| Perry Alexander | Formal Methods Application To System-Level Design |
| Jerzy Grzymala-Busse | Knowledge Discovery, Data Mining, Machine Learning, Expert Systems, Reasoning Under Uncertainty |
| Joseph Evans | High-Performance Networks, Mobile Networking and Wireless Systems, Pervasive Computing Systems, System Implementations |
| Xin Fu | Computer Architecture, Hardware Reliability, The Impact of Nano-Scale Technology Scaling On Multi-Core Processors, On-Chip Interconnection Network |
| Andy Gill | Functional Programming, Software Engineering, Compilers, Systems, FPGAs |
| Fengjun Li | Information Security and Privacy, Healthcare Informatics, Smart Grids, Network Security, Applied Cryptography |
| Bo Luo | 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 |
| Gary Minden | Digital systems, Microprocessors, Artificial intelligence |
| Hossein Saiedian | Software Engineering Including Software Process Improvement, Formalism in Software Development, Object-Oriented Software Development, Software Engineering Education, Software Architecture |
| James Sterbenz | Computer networks and communication; Network science, simulation, and analysis, Future Internet architecture, design, and topology, Resilient, survivable, and disruption tolerant networks, Mobile wireless networks and MANET routing, Disruption and delay tolerant end-to-end transport |
Associated Facilities
- SELinux installation
- Virtualization environment
- SAL, PVS, and Isabelle verification tools and expertise
- Rosetta specification and analysis capabilities
- Computational cluster with over 1,000 processors connected to 37 TB of on-line storage
Program Objectives
- Understand the cryptographic foundations of information security.
- Understand and able to employ common encryption/decryption protocols.
- Understand the fundamental principles, models and algorithms in information and systems security.
- Understand the risks, vulnerabilities, threats, and attacks in computer and communications systems.
- Understand the state-of-art protection and defense mechanisms, and the theoretical foundations behind the mechanisms.
- Understand the theories, principles, and state-of-art practices on dependably and fault-tolerant systems.
- Understand user privacy issues and protection mechanisms, in centralized, distributed, and Web environments.
Core Coursework (MS)
| EECS 755 Software Modeling and Analysis |
| EECS 765 Introduction to Cryptography and Computer Security |
| EECS 866 Network Security |
| EECS 983 Resilient and Survivable Networking |
Elective Coursework (MS)
| EECS 711 Security Management and Audit |
| EECS 716 Formal Language Theory |
| EECS 718 Graph Algorithms |
| EECS 735 Automated Theorem Proving |
| EECS 738 Machine Learning |
| EECS 742 Static Analysis |
| EECS 745 Implementation of Networks |
| EECS 750 Advanced Operating Systems |
| EECS 753 Embedded and Real Time Computer Systems |
| EECS 762 Programming Language Foundation I |
| EECS 764 Analysis of Algorithms |
| EECS 767 Information Retrieval |
| EECS 780 Communication Networks |
| EECS 781 Numerical Analysis I |
| EECS 782 Numerical Analysis II |
| EECS 818 Software Architecture |
| EECS 819 Cryptography |
| EECS 830 Advanced Artificial Intelligence |
| EECS 837 Data Mining |
| EECS 843 Programming Language Foundation II |
| EECS 863 Network Analysis, Simulation, and Measurements |
| EECS 865 Wireless Communication Systems |
| EECS 869 Error Control Coding |
| EECS 881 High-Performance Networking |
| EECS 882 Mobile Wireless Networking |
| EECS 776 Functional Programming and Domain Specific Languages |
| EECS 876 Advanced Topics in Functional Languages |
Signal Processing
PhD student John Jakabosky runs a proof-of-concept experiment on transmitter-in-the-loop optimization of advanced radar waveforms.
EECS researchers are building innovative signal processing techniques that exploit noise and interference for additional information or as cover for covert messages. They are developing static/adaptive filtering schemes that will better enable cooperative communication systems and networks. Remote sensing research of the polar ice caps has led to numerous developments in signal processing. New techniques and methods are being explored in computer vision, digital image processing, optical sensors, and other current EECS research.
Associated Disiplines
Explore: DisciplinesAssociated Programs
Associated Faculty
| Shannon Blunt | Adaptive Signal Processing for Radar and Communications, Array Processing, Interference Cancellation, Waveform Diversity/Design for Physical Systems, Biomedical Image Processing |
| Rongqing Hui | Optical/RF Measurement and Bioscensors, Novel Photonic Devices, Optical Communication Systems |
| Carlton Leuschen | Radar Sounding, Radar Altimetry, Ground-Penetrating Radar |
| Lingjia Liu | Delay-sensitive and energy-efficient communications over wireless networks, Multi-user communication systems/networks, Cooperative communication systems/networks, Interference coordination/mitigation |
| Erik Perrins | Digital Communication Theory, Advanced Modulation Techniques, Channel Coding, Synchronization, Multiple-Input Multiple-Output Communications |
| David Petr | Audio Signal Processing, Network Performance |
| Glenn Prescott | Software Radio Systems, Spread Spectrum and Military Communication Systems, Radio and Radar Signal Processing, DSP Applications in Acoustics and Radio Signals, Wireless Communication Systems |
| James Stiles | Radar Remote Sensing of Vegetation, Propagation and Scattering in Random Media, Ground-Penetrating Radar, Radar Signal Processing, Applications of Information and Estimation Theory in Remote Sensing |
Associated Facilities
- Xilinx and Altera FPGA/SoC prototyping systems
- Synplicity and Xilinx FPGA synthesis tools
- ModelSim VHDL/Verilog simulation tools
- Spectrum analyzers, oscilloscopes, and function generators
- Prototype PC board fabrication tools
- RF signal generators
- Simulink
- Computational cluster with over 1,000 processors connected to 37 TB of on-line storage
Program Objectives
- Understand the fundamental principles involved with extracting signals from noise and interference.
- Understand how to design appropriate static/adaptive filtering schemes according to the particular application, availability of prior information, and operational environment.
- Understand the fundamental limitations imposed by physical systems that bound realizable performance.
- Have the ability to effectively communicate complex, abstract concepts.
Core Coursework (MS)
| EECS 744 Communications and Radar Digital Signal Processing |
| EECS 844 Adaptive Signal Processing |
| EECS 861 Random Signals and Noise |
| EECS 965 Detection and Estimation Theory |
Elective Coursework (MS)
| EECS 611 Electromagnetic Compatibility |
| EECS 622 Microwave and Radio Transmission Systems |
| EECS 628 Fiber Optic Communication Systems |
| EECS 713 High-Speed Digital Circuit Design |
| EECS 721 Antennas |
| EECS 723 Microwave Engineering |
| EECS 725 Introduction to Radar Systems |
| EECS 728 Fiber-optic measurement and sensors |
| EECS 738 Machine Learning |
| EECS 740 Digital Image Processing |
| EECS 741 Computer Vision |
| EECS 769 Information Theory |
| EECS 823 Microwave Remote Sensing |
| EECS 824 Microwave Remote Sensing II |
| EECS 825 Radar Systems |
| EECS 828 Advanced Fiber-Optic Communications |
| EECS 833 Neural Networks and Fuzzy Systems |
| EECS 841 Computer Vision |
| EECS 862 Principles of Digital Communication Systems |
| EECS 865 Wireless Communication Systems |
| EECS 869 Error Control Coding |
| EECS 929 Electromagnetic Propagation and Scattering in Random Media |
| EECS 940 Theoretic Foundation of Data Analysis |
| EECS 967 Mathematical Optimization with Communications Applications |
| EECS 820 Advanced Electromagnetics |
Software Engineering and Management
Note:This area is not associated with research occurring at the Electrical Engineering and Computer Science Department. It is strictly an academic area associated with the MSIT program.
Associated Disiplines
Explore: DisciplinesAssociated Programs
Associated Faculty
| Hossein Saiedian | Software Engineering Including Software Process Improvement, Formalism in Software Development, Object-Oriented Software Development, Software Engineering Education, Software Architecture |
Program Objectives
This focus area aims at uniting theory with industrial-strength practices to provide a solid education in software development, management and maintenance. The program contents emphasize skills in requirements engineering, software architecture, software project managements, software quality assurance, and object technologies.Core Coursework (MS)
| EECS 710 Information Security and Assurance |
| EECS 780 Communication Networks |
| EECS 810 Software Engineering and Management |
| EECS 811 IT Project Management |
| EMGT 806 Finance for Engineers |
| EMGT 821 Strategic Analysis of Technology Project |
Elective Coursework (MS)
| EECS 712 Network Security and its Application |
| EECS 746 Database Systems |
| EECS 812 Software Requirements Engineering |
| EECS 814 Software Quality Assurance |
| EECS 818 Software Architecture |
Theory of Computing
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 Disiplines
Explore: DisciplinesAssociated Programs
Associated Faculty
| Perry Alexander | Formal Methods Application To System-Level Design |
| Jerzy Grzymala-Busse | Knowledge Discovery, Data Mining, Machine Learning, Expert Systems, Reasoning Under Uncertainty |
| Andy Gill | Functional Programming, Software Engineering, Compilers, Systems, FPGAs |
| Nancy Kinnersley | Design and Analysis of Algorithms, Graph Theory and Graph Algorithms, Computer Science Education, Discrete Mathematics |
| Man Kong | Algorithm Design and Analysis, Combinatorial Optimizations, Graph Algorithms |
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)
| EECS 716 Formal Language Theory |
| EECS 718 Graph Algorithms |
| EECS 762 Programming Language Foundation I |
| EECS 764 Analysis of Algorithms |
Elective Coursework (MS)
| EECS 649 Introduction to Artificial Intelligence |
| EECS 660 Fundamentals of Computer Algorithms |
| EECS 662 Programming Languages |
| EECS 735 Automated Theorem Proving |
| EECS 738 Machine Learning |
| EECS 742 Static Analysis |
| EECS 762 Programming Language Foundation I |
| EECS 741 Computer Vision |
| EECS 841 Computer Vision |
| EECS 746 Database Systems |
| EECS 755 Software Modeling and Analysis |
| EECS 761 Programming Paradigms |
| EECS 767 Information Retrieval |
| EECS 818 Software Architecture |
| EECS 819 Cryptography |
| EECS 830 Advanced Artificial Intelligence |
| EECS 837 Data Mining |
| EECS 839 Mining Special Data |
| EECS 843 Programming Language Foundation II |
| EECS 867 Statistical Natural Language Processing |
| EECS 940 Theoretic Foundation of Data Analysis |
| EECS 955 Theoretical Foundations of Software Construction |
| EECS 776 Functional Programming and Domain Specific Languages |
| EECS 876 Advanced Topics in Functional Languages |
| Applied Electromagnetics |
| Communications Systems |
| Computer Systems Design |
| Computing in the Biosciences |
| Information Assurance and Management |
| Intelligent Informatics |
| Internet Engineering and Management |
| Languages and Semantics |
| Network Engineering |
| Network Systems |
| Radar Systems and Remote Sensing |
| RF Systems Engineering |
| Security and Assurance |
| Signal Processing |
| Software Engineering and Management |
| Theory of Computing |
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