Courses | VD Academic Affairs

History and overview of distributed systems. Fundamentals of distributed systems and algorithms. Problems, methodologies, paradigms and models necessary for understanding and designing distributed applications. Topics may include: system models, process communication, distributed shared memory, web services, fault tolerance, real/logical/virtual time, distributed algorithms, authentication and security, naming, object-oriented structuring of distributed systems, distributed file systems, communication support for distributed systems. Theoretical concepts will be complemented with practical examples.

The course will offer a concise introduction to quantum computation, developing the basic elements of this new branch of computational theory without assuming any background in physics. It begins with a novel introduction to the quantum theory from a computer-science perspective. It illustrates the quantum-computational approach with several elementary examples of quantum speed-up, before moving to the major applications: Shor's factoring algorithm, Grover's search algorithm, and quantum error correction.

The course will begin with an introduction of data mining field, including why data mining, what is data mining, what kinds of data can be mined, what kinds of patterns can be mined, an overview of technologies, the major issues in data mining, and a brief history of data mining community.

Introductory course for seniors and graduate students covering the practices, issues, and theoretical foundations of organizing and analyzing information and information content for the purpose of providing access to textual and non-textual information resources. Introduces students to the principles of unstructured information storage and retrieval systems.

This course is concerned with the computer acquisition and analysis of image data. Computer vision is the construction of explicit meaningful descriptions of physical objects or other observable phenomena from images. The emphasis is on physical, mathematical, and information-processing aspects of the vision. Topics to be covered include image formation, edge detection and segmentation, convolution, image enhancement techniques, extraction of features such as color, texture, and shape, object detection, 3-D vision, and computer vision system architectures and applications.

The nature of robotics and the role of intelligence in the context of robotics. Overview of robotic systems: state-of-the-art robot systems, planning vs. reactive control, uncertainty in control, sensing, and world models. Configuration space. The role of planning in robotics and relevant techniques. Robot programming, the range of software that supports robotic activity. Navigation and control, strategies for particular environments. Ethical issues associated with robotics and intelligent behavior.

Topics include building decision support and expert systems, knowledge representation and knowledge processing, design a knowledge base to transfer human knowledge into expert system, tools for building expert systems logic programming, expert system shells (Clips, Jess, VISIRULE etc). Emphasis on the use of domain-specific knowledge to obtain expert performance in programs.

This course is designed for senior in Computer Engineering major to introduce them to the fundamentals and theories of machine learning algorithms. Students will be taught the theory, design and implementation of different machine learning algorithms such as Bayes classifiers, decision trees, neural networks, DNN, evolutionary algorithms, inductive learning. Students will implement and compare different algorithms for learning problems. The project is an integral component of this course.

In this course, students will be introduced to the basic principles and problems of computer graphics. They will study mathematical background to understand and implement these basic principles of computer graphics and rendering systems. Students will learn how to use a standard graphics API (Application Programming Interface) to create, render, and manipulate interactively structured two-and three-dimensional models.

Advanced topics in commercial and research oriented databases systems including catalogs, physical storage techniques, query processing, optimization, transaction management, concurrency control, disaster recovery, security, integrity, extended data types, triggers and rules, distributed databases, warehouses and parallelism.

In this course, students will be introduced to principles and current technologies of computer-based multimedia systems. They will study current media types (images, video, audio, graphics etc) and how they are used to create multimedia content. Issues in effectively representing, processing, and compressing multimedia data will be addressed. The students will be familiarized with the range of tools used in creating computer-based multimedia.

Embedded operating systems (EOS) are known as real-time operating systems (RTOS) and also getting more pervasive in our daily lives. Topics of interest include basic OS functions, a relevant hardware review, interrupt sand interrupt handling, semaphores and peripheral I/O operations, real-time scheduling principles and implementation, latency, task management, shared data and synchronization, timers, message passing and memory management, timeline design and performance analysis using metrics and tests, understand RTOS and the resource management, quality of service issues, concurrency, firmware and ROM-resident system code, and debugging live systems. These concepts will be reinforced through C programming and assembly language assignments and project using the Linux operating system. Practical hands-on experience in building real-time applications running under an EOS.

Introduction to concepts, principles and practice of wireless and mobile communications and networking. Multiples access protocols for wireless networks. Mobile Internet protocol. Mobile aware adaptation. Extending the client-server model to accommodate mobility. The role of middleware and support tools. Performance issues. Security and legal implications of wireless communications. Emerging technologies.

Introduction to the theory and practice of computer and network security. Fundamentals of secure networks and systems. Symmetric cryptography primitives, block ciphers and modes of operation. Introduction to number theory and its applications to public key cryptography algorithms. Authentication and integrity concepts, Hash functions, Message Authentication Codes and Digital Signatures. Key distribution and management. Real-life Networking protocols (IPSec, SSL, wireless networks). TCP-IP with a threat focus and attacks. Packet filtering, Firewall, and Intrusion Detection systems. Ethical issues.

Theory and application of analytic methods for evaluating the performance and for capacity planning of computer networks. Review of the basic probability theory. Advanced methods in probabilistic analysis. Random processes. Markovian queuing models. Network protocols. Traffic modelling. Event driven simulation.