Courses Conducting

Currently Conducting

Course

Title
CSE 324
Prerequisite: CSE 122 with a grade of C or higher
Co-requisite: CSE 213
Usually offered in the Spring semester. Introduction to low (micro/macro) and high level languages (L/HLLs) -- features and positions within the computer system. definition of HLLs of syntax and semantics. Data types, control structures, concurrency, declarations, procedures. Recursion and recursive definitions. Procedural and data abstraction. Critique of major programming languages features and design issues (e.g., power, efficiency, security, modularity, readability, etc).Examples from major realms of current programming languages -- imperative (block structured, object oriented), declarative (function, logic) paradigms.
CSE 489-06
CSE 489D-06
Intro Neural Networks Apps Spring Undergraduate
Prerequisite: CSE 213, 222 with a grade of C or higher and consent of instructor
Usually offered in the Spring semester. Undergraduate special topics in computer science. For a list of recent offerings, please visit the department’s website.
CSE 565-01
CSE 565D-01
Neural Networks Spring Graduate
Prerequisite: CSE 344; MATH 254 and 382 with a grade of C or higher, or consent of instructor
Neuron modeling. The perceptron and multilayer perceptrons. Learning algorithms. The Kohonen model, the Grossberg model, the Hopfield model. Associative memory. Applications. Recent developments in the field.
CSE 489-02
CSE 489D-02M
Smart&Secure Sensor Net Apps Spring Undergraduate
Prerequisite: CSE 213, 222 with a grade of C or higher and consent of instructor
Undergraduate special topics in computer science. For a list of recent offerings, please visit the department’s website.
CSE 353
Prerequisite: CSE 222 with a grade of C or higher
Introduction to computer networking, the ISOOSI protocol stack, LAN, MAN, and WAN. Physical layer: transmission media (wireline and wireless); data signaling, modulation, and coding; multiplexing. Fiber optics networking technology: protocols & examples. Data link Layer: error/flow control— protocols design issues; MAC protocols for channel access and allocation. Wireless technology and protocols standards — IEEE 802.11 physical layer and MAC sublayer protocols. Network layer: subnet switching (CS/DG/VC) & routing protocols (Non/ Adaptive); Congestion Control and QoS protocols. ISO vs. (TCP-UDP)/IP the Internet protocol stacks. Internet relays and protocols, e.g., routers, gateways, etc. Introduction to network security. Application layer protocols, E.G., DNS, E-mail, etc. (Same as IT 353.)
CSE 553
Prerequisite: CSE 453 with a grade of C or higher
Models of computer networks. Design and analysis issues. Abstract syntax notation, data compression, security and authentication. Recent developments in the field.
CSE 525
Prerequisite: CSE 325 and 331 with a grade of C or higher or consent of instructor
Advanced topics in operating systems such as real-time, distributed systems, fault-tolerance, parallel I/O, performance, safety-critical systems, and verification.

Courses Developed by Dr Hamdy

Course

Title
IT 453
CSE 453
Prerequisite: CSE 353 with a grade of C or higher
In depts. Coverage of layering protocols; stacks (ISOOSI and TCP/IP) and computer networks architectures, modern examples of LANs, MANs, WANs protocols/architectures. Recent developments in Fiber optics technology — protocols and architectures. High speed “all-fiber-optics” networks. Internetworking: global addresses/ names and translation, virtual networks and tunnels, routing, subnetworks switching protocols, IPv6, multicasting, Mobile IP. End-to-end protocols, TCP and UDP. Advances in Congestion control and resource allocation. Client-server models & applications. The QoS mechanism integrated/differentiated, ATM QoS. Network security: information and link security, encryption, internetworking security, IPsec, firewalls, VPN, wireless security. Analysis of networks protocols.
CSE 454
Computer Graphics Undergraduate
Prerequisite: CSE 213, 222; MATH 254 each with a grade of C or higher
Design and implementation of visual interfaces. Graphics input and output hardware, display programming, 2-D transformations, approximation techniques for curve and surface representation. Introduction to the creation of 3- D computer-generated images, color theory, lighting and shading.
CSE 452
CSE 452D
Prerequisite: CSE 325 and CSE 353 each with a C or higher, or consent of instructor
Introduction to sensory technology with special focus on wireless sensor networks (WSNs) applications, topologies, deployment, sensed data manipulation, mobile ad-hoc wireless communication, security. Low power consumption and data rates WSNs protocols (e.g., ZigBee/IEEE808.15.4). Students will get familiar with sensor nodes' hardware (motes and sensor boards) and programming (TinyOS and ZigBee application objects) via a set of practical lab/field experiments that covers the design, implementation, deployment, and data collection/analysis of some actual WSNs data/vent acquisition systems (e.g., environment monitoring, remote asynchronous event detection--forest fire, border intrusion, tsunami, earthquake, volcanic activities, etc).
CSE 489
CSE 485
Prerequisite: CSE Graduate Standing
An introduction to the methodology and skills required for academic research with emphasis on computer science. Students will learn the skills involved in discussing technical ideas; articulating research problems; critiquing, writing, and defending research proposals; reading, reviewing, and presenting research articles with appropriate visual aids; and exploring ethical issues associated with research. Students are expected to attend all presentations by outside speakers in the CS Speaker Series during the semester. Typically offered each fall.
CSE 589
CSE 585
Prerequisite: Senior standing, one semester of upper division courses in computer science, and consent of the instructor
A research seminar for undergraduate students with a focus either on special topics in computer science or on the methodology and skills required for research in computer science. Use as technical electives is limited (see requirements above), but may be taken multiple times as a general elective.
CSE 565-01
CSE 565D-01
Neural Networks Spring Graduate
Prerequisite: CSE 344; MATH 254 and 382 with a grade of C or higher, or consent of instructor
Neuron modeling. The perceptron and multilayer perceptrons. Learning algorithms. The Kohonen model, the Grossberg model, the Hopfield model. Associative memory. Applications. Recent developments in the field.
CSE 501
for non-major Computer Science students.
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Teaching Contribution

  • Development of six undergraduate and eleven graduate classes.
  • Introduction of the “Neural Networks” and “Sensor Networks” subjects in our CSE department.
  • Refinement and teaching of the subject of “principles of programming languages”, for 20 years.
  • In addition, I helped in the formation of the Information Technology specialization field at NMT, and I am teaching IT networking classes.