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Research Tracks

Students are encouraged to choose most of their graduate electives within a single research track, by consulting with their advisor. Each student must take a minimum of two electives from the Department of Computer Engineering. Students are allowed to take relevant courses from other academic programs, including electrical engineering, computer science, and software engineering, for specific research focus. The following research tracks and elective courses are available.


Computer Architecture

Computer Architecture - Computer architecture area deals with hardware resource management, instruction set architectures and their close connection with the underlying hardware, and the interconnection and communication of those hardware components. Some of the current computer architecture challenges that are being tackled in the Computer Engineering Department include energy efficient architectures, high performance architectures, graphic processing units (GPUs), reconfigurable hardware, chip multiprocessors, and Networks-on-Chips. Faculty working in this area: Lopez-Alarcon, GangulyKudithipudiLukowiakMeltonShaaban.

Available Graduate Electives (600-level and above) courses:

  • CMPE-655 Multiple Processor Systems
  • CMPE-660 Reconfigurable Computing
  • CMPE-665 Performance Engineering of Real-Time and Embedded Systems
  • CMPE-731 Design and Test of Multi-core Chips
  • CMPE-750 Advanced Computer Architecture
  • CMPE-755 High Performance Architectures
  • CSCI-654 Foundations of Parallel Computing
  • CSCI-652 Distributed Systems
  • CSCI-742 Compiler Construction


Integrated Circuits and Systems

Integrated Circuits and Systems - Modern processors demand high computational density, small form factors, and low energy dissipation with extremely high performance demands. This is enabled by the nanoscale and heterogeneous integration of transistors and other emerging devices at the massive-scale. Such nanocomputers will open unimaginable opportunities as well as challenges to Computer Engineers. This research focuses designing computers with emerging novel technologies in the presence of severe physical constraints; investigating dynamic reconfigurability to exploit the power of nano-scale electronics for building reliable computing systems; and studying the applicability of emerging technologies to address challenges in computing hardware of the future. Faculty working in this area:  GangulyKudithipudiLukowiak.

Available Graduate Electives (600-level and above) courses:

  • CMPE-630 Digital Integrated Circuit Design
  • CMPE-655 Multiple Processor Systems
  • CMPE-730 Advanced Digital Integrated Circuit Design
  • CMPE-731 Design and Test of Multi-core Chips
  • CMPE-750 Advanced Computer Architecture
  • EEEE-602 Random Signals ad Noise
  • EEEE-610 Analog Electronics
  • EEEE-620 Design of Digital Systems
  • EEEE-712 Advanced Field Effect Devices
  • EEEE-713 Solid State Physics
  • EEEE-720 Advanced Topics in Digital Systems Design
  • EEEE-726 Mixed Signal IC Design
  • EEEE-730 Advanced Analog IC Design


Networks and Security

Networks and Security - The prevalence of interconnected computing, sensing and actuating devices have transformed our way of life. Ubiquitous access to data using/from these devices with reliable performance as well as security assurance presents exciting challenges for engineers and scientists. Resilient to environmental uncertainty, system failures and cyber attacks requires advances in hardware, software and networking techniques. The research track on Networks and Security in Computer Engineering focuses on intelligent wireless and sensor networks, cryptographic engineering, and predictive cyber situation awareness. Faculty working in this area: KwasinskiLukowiakYang.

Available Graduate Electives (600-level and above) courses:

  • CMPE-661 Hardware and Software Design for Cryptographic Applications
  • CMPE-670 Data and Communication Networks
  • CMPE-770 Wireless Networks
  • CMPE-789 Machine Intelligence
  • CSCI-642 Secure Coding
  • CSCI-662 Foundations of Cryptography
  • CSCI-720 Big Data Analytics
  • CSCI-734 Foundations of Security Measurement and Evaluation
  • CSCI-735 Foundations of Intelligent Security Systems
  • CSCI-736 Neural Networks and Machine Learning
  • CSCI-762 Advanced Cryptography
  • CSEC-743 Computer Viruses and Malicious Software
  • CSEC-744 Network Security
  • NSSA-612 Network Modeling and Analysis
  • NSSA-711 Advanced Routing Protocols
  • NSSA-715 Network Design and Performance
  • EEEE-602 Random Signals and Noise
  • EEEE-693 Digital Data Communication
  • EEEE-797 Wireless Communication


Computer Vision and Machine Intelligence

Computer Vision and Machine Intelligence - Visual information is ubiquitous and ever more important for applications such as robotics, healthcare, human-computer interaction, biometrics, surveillance, games, entertainment, transportation and commerce.  Computer Vision focuses on extracting information from image and video data for modeling, interpretation, detection, tracking and recognition.  Machine Intelligence methods deal with human-machine interaction, artificial intelligence, agent reasoning, and robotics.  Algorithm development for these areas spans image processing, pattern recognition and machine learning, and is intimately related to system design and hardware implementations. Faculty working in this area: SavakisPtucha.

Available Graduate Electives (600-level and above) courses:

  • CMPE-680 Digital Image Processing Algorithms
  • CMPE-685 Computer Vision
  • CMPE-789 Machine Intelligence
  • EEEE-647 Artificial Intelligence Explorations
  • EEEE-670 Pattern Recognition
  • EEEE-685 Principles of Robotics
  • EEEE-780 Digital Video Processing
  • EEEE-781 Image and Video Compression
  • IMGS-756 Advanced Digital Image Processing
  • CSCI-713 Applied Perception in Graphics and Visualization
  • CSCI-715 Applications in Virtual Reality
  • CSCI-719 Topics in Computer Graphics
  • CSCI-720 Big Data Analytics
  • CSCI-731 Advanced Computer Vision


Signal Processing, Control and Embedded Systems

Signal Processing, Control and Embedded Systems - This research area is concerned with algorithms and devices used at the core of system that interacts with our physical world. As such, this area considers the sensing, analysis and modeling of dynamic systems with the intent of measuring information about a system, communicating this information and processing it to adapt its behavior. Application areas are robust feedback-based control where uncertainty in the dynamics and environment must be considered during the design process and signal processing algorithms and devices for system sensing and adaptation. Faculty working in this area: CockburnKwasinskiMelton.

Available Graduate Electives (600-level and above) courses:

  • CMPE-663 Real-time and Embedded Systems
  • CMPE-664 Modeling of Real-time Systems
  • CMPE-665 Performance Engineering of Real-Time and Embedded Systems
  • EEEE-602 Random Signals and Noise
  • EEEE-610 Analog Electronics
  • EEEE-661 Modern Control Theory
  • EEEE-733 Robust Control
  • EEEE-765 Optimal Control
  • EEEE-768 Adaptive Signal Processing
  • EEEE-793 Error Detection and Error Correction
  • EEEE-794 Information Theory
  • MATH-781 Wavelets and Applications
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