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Research

Department of Computer Engineering faculty members are interested in the following areas:

  • Dr. Ahmed. Fault-tolerant computing, computer architectures, ATM networks, computer networks, architectures for signal processing algorithms, software testing, software quality assurance, computer network management and Internet computing applications in business.

  • Dr. Al-Ali. Microprocessors, microcomputers, microcontrollers, embedded systems, data acquisition units and PLC hardware/software architectures, and computer applications in industry (industrial plant remote monitoring and control using GSM, GPRS, MMS networks and the Internet).

  • Dr. Al-Rousan. Multiprocessors: Scalable Coherent Interface (SCI) based, scheduling, cache coherent protocol, multiprocessors design, simulations; fuzzy and neural applications in control; sign languages, letter and image recognition; networking: protocol; wireless mobile networks; fault-tolerant systems design and their reliabilities; Internet applications; distance learning; and Web-based monitoring.

  • Dr. Eberlein. Requirements engineering, software engineering, time-constrained requirements engineering, agile processes, business process engineering, conceptual modeling, decision support systems and design of telecommunication services.

  • Dr. Qadah. Serial/distributed database and intelligent systems, software engineering and development, object-oriented technology and networking/Internet/intranet.

  • Dr. Ozkul. Computer architecture, embedded system design, data acquisition and interfacing using computers, interdisciplinary industrial computer applications, alternative computing technologies, fuzzy decision making, industrial computing networks and computer vision.

  • Dr. Sagahyroon. VLSI testing, power consumption in CMOS VLSI circuits, hardware description languages and computer architecture.

  • Dr. Zualkernan. Enhancing standards for e-learning including SCORM, QTI and SIF to better support reusable learning objects, implementation issues in reusable learning objects, methodologies for development of reusable learning objects, software architecture to support reusable learning objects, peer-to-peer architectures for reusable learning objects, adaptive architectures for e-learning, validation and verification of reusable learning objects, pedagogical foundations for reusable learning objects, reusable learning objects for the design task.

 

 
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