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Electrical and Computer Engineering

Dr. Robert Mauro
Chair, Department of Electrical and Computer Engineering

Dr. Nevzat Ozturk
Director, Graduate Program

Mission

The Master of Science in Electrical Engineering and the Master of Science in Computer Engineering degree programs are designed to provide a higher degree of mastery of electrical and computer engineering fundamentals, emphasizing practical applications, thereby expanding the students' technological horizons and preparing professionals for advanced level positions and for admission to doctoral programs.

Objectives

The objective of these programs is to prepare graduates for successful and dynamic professional careers through a course of study that provides:

  1. a strong grasp of electrical engineering and computer engineering fundamentals through a diverse and flexible curriculum
  2. skills in practical applications, contemporary industrial needs and emerging technologies
  3. a foundation for increasing professional responsibilities or continued study at the doctoral level 

Admission Requirements

Electrical Engineering Degree

Applicants must possess one of the following:

  1. A baccalaureate degree in electrical engineering from a program accredited by the Engineering Accreditation Commission of ABET, Inc., or from a recognized foreign institution.
  2. Applicants who have a baccalaureate degree in another area of engineering, physics, or mathematics may be admitted into the program provided they complete undergraduate prerequisites specified by the Graduate Program Director. These courses must be completed with a minimum grade point average of 3.00 with no grade lower than C. These courses will not satisfy any requirements for the Master of Science in Electrical Engineering degree. Generally, students must complete prerequisite courses before they are permitted to register for graduate courses. Exceptions require the recommendation of the Graduate Program Director and the approval of the Dean of Engineering.

Computer Engineering Degree

Applicants must possess one of the following:

  1. A baccalaureate degree in computer (or electrical) engineering from a program accredited by the Engineering Accreditation Commission of the Accreditation Board for Engineering and Technology or from a recognized foreign institution.
  2. Applicants who have a baccalaureate degree in another area of engineering, physics, or mathematics may be admitted into the program provided they complete undergraduate prerequisites specified by the Graduate Program Director. These courses must be completed with a minimum grade point average of 3.00 with no grade lower than C. These courses will not satisfy any requirements for the Master of Science in Computer Engineering degree. Generally, students must complete prerequisite courses before they are permitted to register for graduate courses. Exceptions require the recommendation of the Graduate Program Director and the approval of the Dean of Engineering.

Degree Requirements

A student must complete a minimum of thirty credit hours of graduate coursework. Specific requirements follow:

Electrical Engineering Degree

Students must select one of the following:3
ECEG 701 Signals, Systems and Transforms I
ECEG 702 Signals, Systems and Transforms II
ECEG 710 Probability and Stochastic Processes
Students must also take nine courses from any offerings by the Electrical and Computer Engineering Department27
At most, two of the nine courses can be Graduate Core courses with the advice and approval of the Graduate Program Director
Six courses credits can be substituted by the master's Thesis option under the direction of a Thesis Advisor
Total Credits30

Any modifications to program requirements must be approved by the Graduate Program Director.

Computer Engineering Degree

One of the following:3
Embedded Systems
Computer Network Operations
Computer Architecture I
Students must also take nine courses from any offerings by the Electrical and Computer Engineering Department27
At most, two of the nine courses can be any Graduate Core Courses with the advice and approval of the Graduate Program Director
[Six course credits can be substituted by the master's Thesis option under the direction of a Thesis Advisor]
Total Credits30

Any modifications to program requirements must be approved by the Graduate Program Director.

Master of Science Degree Description and Options for Electrical Engineering and Computer Engineering

Master of Science students may elect to complete a Master of Science by coursework or by thesis. The coursework option entails 30 course credits; the thesis option entails 24 course credits and 6 master's thesis research credits, ECEG 799. In both cases, the minimum number of total credits is 30.  At this level, research undertaken under the thesis option should exhibit a thorough understanding of advanced scientific thought and an ability to apply advanced engineering design principles, and planning.

Manuscript Presentation 

Degree candidates must present their research to the appointed guidance committee in final manuscript form for official acceptance no later than two weeks before the end of the semester.

Graduate students registered for thesis credits must submit four final bound copies to the Electrical and Computer Engineering Department for necessary signatures one week before the end of the semester.

Applications of AI and Machine Learning in Electrical Engineering and Computer Engineering

Electrical and computer engineers are at the forefront in the design and implementation of tomorrow’s consumer and industrial products.  Today, because much of this work is intimately involved with the field of artificial intelligence, it is clear that many of today's and tomorrow's ECE jobs will require a considerable knowledge of AI concepts.

Because our department has a commitment to ensure that our students are prepared to assume job leadership roles when they graduate, we have developed a strong AI component in our ECE courses. For example, we currently offer graduate courses in Applied Data Mining for Engineers, Signal Detection & Estimation, Unmanned Autonomous Vehicles, Applied Machine Learning, and Bioinspired Robotic Vision Systems.

Concentration Option

The Graduate concentration option consists of prescribed courses in a specific concentration area, and is available through the Electrical Engineering and Computer Engineering graduate programs as follows:

  • Cybersecurity

Unless otherwise noted, courses in this program may be applied to a Master of Science Degree in either Electrical and Computer Engineering programs . While approval of the Graduate Program Director is required to enroll in a graduate course, admission to the Graduate Program is not required to participate in a Concentration area. It is expected, however, that individuals desiring to take graduate-level courses in a Concentration Program will have a baccalaureate degree in either an engineering field, a science or applied science field, or mathematics, and will meet the prerequisite requirements of the courses they wish to take in that Concentration. Specific information regarding Graduate Electrical and Computer Engineering Concentration is available on the Electrical and Computer Engineering website.

Find Learning That Matches Your Lifestyle

  • The 30-credit electrical engineering and computer engineering programs can be completed within one or two years.
  • Courses are available during the fall, spring, and summer semesters with schedules that are suitable for individuals working full-time.
  • Most graduate courses are delivered in either a fully online mode or in-person.

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Courses

ECEG 500. Wireless & RF Technology. 3 Credits.

Investigation of wireless and radio frequency technology including propagation characteristics, receivers and transmitters, circuit and devices. Nonlinear and noise analysis and non-ideal components. Measurement techniques including network and spectral analysis. Communications systems are emphasized but radar and RFID systems are also covered.

ECEG 521. Applied Parallel Computing. 3 Credits.

A software engineering centric course covering traditional parallel computing with message passing protocols, programming patterns for multi-core processors, application development on graphics processing units, and wide scale distributed computer systems.

ECEG 547. Optical Information Processing Systems. 3 Credits.

Response of linear spatially invariant systems; signal detection by matched filtering, mutual coherence, transform properties of linear optical imaging systems; optical information processing and filtering; linear holography.

ECEG 548. Fiber Optics Communication. 3 Credits.

Optical fiber structures and physical characteristics; electromagnetic waveguiding properties and modes, fiber materials, loss mechanisms, and dispersion. Semiconductor laser and LED sources and photodetectors. Connectors,Fiber measurements,communication aspects of fiber transmission. Fiber system examples and design procedures. Three credit.

ECEG 591. Advanced Special Topics. 3 Credits.

ECEG 592. Power Electronics. 3 Credits.

The course provides a knowledge of circuitry for the control and conversion of electrical power with high efficiency. Applications include electronic power supplies, aerospace and vehicular power systems, and renewable energy systems. Pre-requisite: Senior ECE or Graduate Status.

ECEG 700. Industrial Electric Drives. 3 Credits.

Hands-on experiments and demonstrations in industrial electric drives, requirements placed by mechanical systems on electric drives, and their various applications such as flexible production systems, energy conservation, renewable energy and transportation. Power electronics in drives using switch-mode converters and pulse width modulation to synthesize the voltages in dc and ac motor drives. Design of a controller using Matlab/Simulink.

ECEG 701. Signals, Systems, and Transforms I. 3 Credits.

Description and analysis of continuous-time signals and systems in the time and the frequency domains' Laplace transforms:inversion of transforms by coplex integrative; application to lumped and distributed parameter systems;analysis of continuous-time linear systems using state space techniques; controllability and observability : stability analysis.

ECEG 702. Signals, Systems and Transforms II. 3 Credits.

Discrete-time signals and systems; discrete convolution; sampling and quantizing;Z-transform;discrete Fourier transform; Fast Fourier transform; state space techniques for discrete-time systems; controllability and observability; stability. Three credit.

ECEG 703. Trustworthy AI Applications in Electrical & Computer Engineering. 3 Credits.

This course will examine some of the issues and consequences for humanity and the environment caused by the increasing use of Artificial Intelligence (AI) and related technologies in engineering applications. The course covers trustworthiness AI principles and practices in data preparation, algorithm design, product development, and system deployment. It will also investigate how processes for AI development and deployment could be adapted to operate more effectively within legal frameworks while simultaneously satisfying safety goals. Students will evaluate existing electrical and computer engineering applications for addressing known challenges such as fairness, privacy, and liability.

ECEG 704. Bioinstrumentation. 3 Credits.

Design principles of biomedical devices, bioelectronics, medical nanodevices, transducers, sensors, interface electronics, microcontrollers, and engineering programming. Signal modalities, bioelectrical signal monitoring, acquisition, analysis, and processing. Case studies and platform-based designs of medical devices, and instrumentation.

ECEG 705. Applied Data Mining for Engineers. 3 Credits.

This course will provide students with an understanding of fundamental data mining methodologies and with the ability to formulate and solve problems with them. Special emphasis attention will be paid to practical, efficient and statistically sound techniques. Hands-on experience with data mining software, primarily R, to allow development of basic execution skills.

ECEG 706. Radiation and Optics. 3 Credits.

Radiation and simple radiating systems, wave optics, interference and diffraction: first order and higher order coherence functions; Fourier optics, properties of coherent optical beams. Three credit.

ECEG 709. Linear Mathematical Methods. 3 Credits.

Matrix calculations; linear systems and linear vector spaces; operators and their representation; function of operators and matrices; systems of differential equations; Eigen function representations; electrical engineering applications.

ECEG 710. Probability and Stochastic Processes. 3 Credits.

Random variables, distribution and density functions: functions of random variables;random processes'stationarity, ergodicity, correlation functions and power spectra' noise theory'system analysis with stochastic inputs: Gaussian, Markoff and Poisson processes.

ECEG 715. Power Electronics. 3 Credits.

Electronic converters for DC-DC, & AC-DC rectification, HVDC inversion techniques, Production of variable frequency AC power for motor drive applications. Techniques for connecting distributed energy sources to the AC power grid. High efficiency power electronics for hybrid electric vehicles. Electronic techniques for Power Factor Correction. Use of laboratory experiences and PSpice computer simulations to supplement analytical circuit solution methods.

ECEG 716. Fuzzy Systems. 3 Credits.

A study of the concept of fuzzy set theory including operations on fuzzy sets, fuzzy relations, fuzzy measures, fuzzy logic, with emphasis on engineering applications.

ECEG 717. Mobile Applications and Cybersecurity. 3 Credits.

The proliferation of smart, consumer mobile, and medical devices provide new security vulnerabilities. This course will focus on the security features and limitations on smartphones, mobile telecommunication systems, portable healthcare monitoring devices, and sensor networks. Materials will cover smartphone security, mobile location privacy, wireless sensor security, and security challenges in medical device industry.

ECEG 721. Embedded Systems. 3 Credits.

Design of embedded systems including system level modeling/specification, and architecture synthesis, compilation for area/power/performance, code compression, scheduling and real-time operating systems, and verification and functional validation of embedded systems. Case studies and platform-based design encompassing microcontrollers/digital signal processors, distributed computing and peripherals.

ECEG 722. Switching & Automata Theory. 3 Credits.

Analysis and synthesis of finite state machines; Turing and universal machines; information lossless machines; modular realization of machines; introduction to machine languages and computability.

ECEG 723. Software Engineering. 3 Credits.

The evolution of programming from art to science. Program design tools and techniques; structured programming and modular design; complexity, storage, and processing-time analysis; program testing and debugging; software reliability, repair and availability. Three credit.

ECEG 724. Computer Architecture II. 3 Credits.

Computer Systems; multi processors and pipelined processors; array processors; computer networks; techniques for analysis of computer systems.

ECEG 725. Microprocessor Systems. 3 Credits.

Detailed study of the 8086 and 68000 families of 16-bit microprocessors, including their architecture, instruction sets, programming, interfacing, and interrupt handling. Applications to communications, control, and instrumentation. Selected additional topics such as bit-slice microprocessors and graphics processors.Prerequisite or Co-requisite:ECEG 520 or equivalent or approval of Instructor.

ECEG 726. Transmission of Digital Data. 3 Credits.

The Architecture of Digital DataTransmission Systems. The protocols:TCP/IP models.The physical layer:Wire, cable, fiber, terrestrial microwave and satellite microwave.The key concepts: bandwidth, noise, channel capacity and error detection and correction. The applications:modulation and modems. Multiplexing: FDM, slotted TDM, and statistical TDM.The data link: asynchronous and synchronous transmission, circuit switching, packet switching.

ECEG 727. Computer Network Operations. 3 Credits.

A structured coverage of Data and Computer Communications Networks. Protocols from the physical and data link layers to the applications layer. Network modeling and fundamentals of performance analysis. Time delay and reliability. Design issues, tools,and procedures regarding capacity assignments, terminal assignment, and switching node location. Routing. Examples from high speed Local Area Networks.

ECEG 728. Operating Systems. 3 Credits.

A study of the modular design of operating systems; the concept of interrupts, multiple processors and I/O programming; memory management techniques, demand paging and virtual memory; job scheduling algorithms, race conditions between processes; file systems, analytic tools for the evaluation of operating systems. Prerequisite:ECEG 520 or equivalent.

ECEG 729. Artificial Intelligence. 3 Credits.

Computer-based systems with the potential to learn, understand, interpret and arrive at conclusions in a manner considered intelligent if a person was making decisions. Topics will be taken from expert systems, fuzzy logic and neural nets with emphasis on machine applications.

ECEG 730. Modern Portable Wireless Devices. 3 Credits.

Wireless communication systems for mobile and autonomous devices, healthcare monitoring devices, with emphasis on: cellular concept & trunking, spread spectrum systems security and multiple access techniques, speech coding, power control. Antennas and channel propagation characteristics and techniques for mitigation of propagation-related degradation factors. Analysis & design of systems following standards & protocols for the latest generation of wireless networks. Key examples of mobile portable devices, medical devices, system characteristics, and architecture design. Pre-requisites: EECE 303, EECE 315. Co-requisite: EECE 304.

ECEG 731. Control Systems. 3 Credits.

Multivariable systems; controllability and observability; observer design and pole assignment; stability analysis.

ECEG 732. Optimal Control Theory. 3 Credits.

Performance measures: dynamic programming and its application to optimal control problems; calculus of variations; minimum principle; numerical techniques for finding optimal controls and trajectories. Prerequisite:ENGG 630.

ECEG 733. Digital Control System Analysis and Design. 3 Credits.

State space representation of discrete-time systems. Stability, observability, controllability. Digital controller design using transform techniques. State space design methods.

ECEG 734. Bulk Power System Operation. 3 Credits.

Operation of the bulk electric power system in North America. Basic types of high voltage equipment and station configurations. Methods and equipment to control power flow and voltage levels on the power systems.

ECEG 735. Direct Energy Conversion. 3 Credits.

Principles of energy conversion; thermoelectric, photovoltaic, and thermionic generators; magneto hydrodynamic power generators: solar and nuclear energy conversion. Three credit.

ECEG 736. Power & Energy Systems. 3 Credits.

Overview of modern interconnected power system and smart grid operation. Develop appropriate models for an interconnected power system, and perform power flow and short circuit analysis. Students will write a basic power flow computer program.

ECEG 737. NERC Standards & Operation. 3 Credits.

North American Electric Reliability Corporation (NERC) standards and related compliance concerns in relationship to operational principles of the power systems.

ECEG 738. Protective Relays. 3 Credits.

Analysis of faulted power systems, symmetrical and asymmetrical systems, transient stability, emergency control and system protection.

ECEG 739. Relay Systems. 3 Credits.

Power system operation, three-phase system calculations and modeling of power system elements. Protective devices and their principles of operation. Pilot protection of transmission lines, generator protection and transformer protection.

ECEG 740. Electro-Optics. 3 Credits.

Propagation of rays and beams, optical resonators; theory of laser oscillation; modulation of laser beams; optical detection.

ECEG 741. Quantum Electronics. 3 Credits.

Interaction of radiation with matter, spontaneous and simulated emission and absorption; semi-classical theory of lasers; traveling wave and cavity lasers; laser saturation; noise limitation of light detectors and amplifiers.

ECEG 742. Computer Vision & Imaging. 3 Credits.

Detection, image formation, and engineering design of vision and imaging sensors and systems. Unmanned aerial and underwater imaging systems, biomedical image recognition, medical image understanding, inspection, and robotics applications.

ECEG 743. Biomedical Imaging Systems. 3 Credits.

Engineering and physical principles of biomedical modalities, as applied to clinical diagnostics and pharmaceutics, gene arrays and Omics imaging technologies central to the detection process, system design, data analysis and classification. Clinical examples.

ECEG 744. Signal Detection & Estimation. 3 Credits.

Hypothesis testing; decision criteria: North and Wiener filtering; detection and estimation of signals with known and random parameters in white and colored Gaussian noise; recursive estimation of constant and time-varying signal parameters; Kalman-Bucy filtering; applications to communication systems, radar and biological signal processing. Prerequisite: ECEG 710.

ECEG 745. Medical Device Miniaturization. 3 Credits.

Engineering design of miniaturized medical devices, operating on electrical, and quantum principles, with reduced form factor and weight, while reducing power consumption and boosting performance. Integration trends, functionality, scalability, reconfigurability. Case studies and platform-based designs of miniaturized medical devices, such as medical implantable devices, heart monitors, pacemakers, video cameras.

ECEG 746. Digital Signal Processing. 3 Credits.

Discrete time signals and systems analysis' infinite and finite impulse response digital filter design techniques, random discrete time signals and spectral analysis, detection and estimation of signals in noise Kalman filters.

ECEG 747. Image Processing and Pattern Recognition. 3 Credits.

Digital image processing for manipulation and enhancement of images, development of advanced techniques for object recognition, object classification, image reconstruction, image compression, and feature extraction. Computational analytic and interpretive approaches to optimize extraction and use of imaging data. Engineering, robotic, industrial, medical, and remote sensing applications.

ECEG 748. Applied Machine Learning. 3 Credits.

Design of systems that learn from data and improve with experience. Fundamental concepts and methods of machine learning, including the description and analysis of several modern algorithms, their theorectical basis, and the illustration of their applications. Supervised and unsupervised machine learning.

ECEG 749. Unmanned Autonomous Vehicles. 3 Credits.

History of the UAV, basics of mechatronic design, common sensor payloads, high-definition cameras, sonars, lidars, vision and imaging design parameters. Major design challenges, laws and regulations, operations and safety.

ECEG 750. Antenna Engineering. 3 Credits.

Analysis and design of various antenna types such as dipoles, horns, reflectors, apertures, microstrip and wire antennas. Electronically scanned arrays. Radiation pattern antenna impedance, gain, directivity, bandwidth, beam width, and frequency dependence. Reciprocity between receiving and transmitting antennas. Amplitude tapering to achieve desired sidelobe characteristics.

ECEG 751. Microwave Circuits. 3 Credits.

Transmission lines and waveguides; circuit representation of waveguide systems using impedance and scattering formulation , impedance transformation and matching; Faraday rotation in ferrites; passive microwave devices; terminations; attenuators; couplers, circulators, the magic tee; emphasis on developing a circuit view point for analyzing microwave devices.

ECEG 752. Pharmaceutical Bioinformatics. 3 Credits.

Computer based technologies and informatics and computational methods that interfaces with all areas related to the discovery and development drugs, for understanding their functions, mapping processes of the cells and understanding how to use these properties to effectively develop novel drugs.

ECEG 753. Applied Bioinformatics. 3 Credits.

Bioinformatics principles applied to microscopic and biomedical image acquisition methods and applications, methods and applications of image analysis and related machine learning, pattern recognition and data mining techniques, image oriented multidimensional. Methods and applications for the analysis of post-translational modifications, proteomic, mass spectroscopic, and chemoinformatic data.

ECEG 755. Bionanophotonics. 3 Credits.

Nanoparticles for optical bioimaging, optical diagnostics and light guided and activated therapy. Use of nanoparticles platforms for intracellular diagnostics and targeted drug delivery, PEBBLE nonsensors.

ECEG 756. Drug Delivery Systems. 3 Credits.

Instrumentation, devices, and techniques to characterize the physiochemical, optical properties, and in vitro immunological, biological, and stability characteristics of drugs delivery, proteins, and nanomaterials.

ECEG 757. Bioinspired Robotic Vision Systems. 3 Credits.

Introduction to autonomous computer vision systems. Vision-based bio-inspired systems, guidance, and control, for unmanned aerial vehicles (UAVs), unmanned underwater vehicles (UWVs), medical robotic surgery, and robotic applications.

ECEG 758. Cybersecurity Systems. 3 Credits.

Cybersecurity as it relates to systems and then on the engineering principles for secure systems. The course focuses on the differences between threats and vulnerabilities, examples of cybersecurity attacks and events, frameworks, requirements and principles for securing systems.

ECEG 759. Quantum Cryptography. 3 Credits.

Methods that seeks to solve the problem of how to securely send cryptographic keys between two parties by encoding them within light particles, or photons. Quantum cryptography and key distribution technique.

ECEG 760. Data and Applications Security. 3 Credits.

Principles, technologies, tools and trends for data and applications security. Biometrics; digital forensics; secure e-commerce; secure sensor information management.

ECEG 761. Network Security Systems. 3 Credits.

Theoretical and practical aspects of network security. Security of TCP/IP applications; firewalls; wireless LAN security; denial-of-service defense.

ECEG 762. Modeling and Simulation. 3 Credits.

Review of probability distributions;random number testing and generation; mathematical models; Markov chains; simulation methods; data analysis; Monte Carlo methods.

ECEG 763. Data Struct & Cmpt Algorithms. 3 Credits.

Sequential and parallel algorithms for non-numerical and numerical applications. Algorithm complexity analysis, basic data structures, searching, sorting graph and numerical algorithms. 3 credits.

ECEG 764. Data Base Mgmt Systems(DBMS). 3 Credits.

Software and hardware design problems for DBMS; an overview of data base systems, data manipulation languages, normal forms, machine architectures.

ECEG 765. Computer Graphics. 3 Credits.

Basic concepts of computer graphics systems including display devices, graphics software and the display of solid object. Point plotting procedures; line drawing algorithms and circle generators. Displays and controllers; storage and refresh devices. Two dimensional transformations; clipping and windowing. Graphics software; windowing functions, display files; geometric models. Interactive raster graphics. Three dimensional graphics including surface display, perspective and hidden surface removal.

ECEG 766. Mobile Communication Networks. 3 Credits.

This course provides an overview of the latest developments and trends in wireless mobile communications, and addresses the impact of wireless transmission and user mobility on the design and management of wireless mobile systems. In addition to study the technical issues and state-of-the-art techniques in the operation and management of mobile communications networks; To learn the engineering principles and system evaluation methods used in the design of mobile communications networks. This course will cover selected Mobile Communications Networks topics in each of the following areas: Overview of wireless communications, Cellular wireless networks, 2G, 2.5G and 3G cellular networks, Long Term Evolution (LTE) - 3.5G, Future of 5G cellular networks, Wireless local area networks (Wi-Fi), Wireless personal area networks (Bluetooth, UWB, ZigBee), and Mobility management and radio resource management.

ECEG 767. Big Data, and Deep Learning. 3 Credits.

Neural-fuzzy networks, big data analysis, classification, clustering, pattern discovery and prediction. Extraction of useful information from spatio-temporal data. Industrial, healthcare, and commercial applications.

ECEG 768. Green Energy Sources. 3 Credits.

This course presents basic information on Energy outlook, interconnection issues of distributed alternate energy resources, efficiency of power production, electric energy conversion and storage (fossil fuel, nuclear, hydro, solar, fuel cells, wind, and batteries). This course also explores the different energy link integration methodologies using Matlab/Simulink.

ECEG 769. Introduction to Remote Sensing. 3 Credits.

This course is intended to provide an introduction to remote sensing of objects with applications in defense and environment. The course covers the basic principles of image sensors and techniques, image interpretation, remote sensing theory, and digital image analysis in relation to optical, thermal and microwave remote sensing systems. Examples of remote sensing applications will be presented along with methods for obtaining quantitative information from remote sensing imagery. Students will be expected to engage in a special topic evaluation. Course equivalent: EECE 422.

ECEG 770. Intro to Space Systems. 3 Credits.

This course is intended to provide the fundamental principles of space systems, in terms of electro-optical sensing, robotic vision, and imaging. Critical space missions such as monitoring of the integrity of spacecraft structures, detection of debris, object recognition and classification will be presented and discussed. Defense and commercial applications will be introduced and discussed. Students will be expected to engage in a special topic evaluation.

ECEG 771. Cloud Computing & Physical Sys. 3 Credits.

This course provides a comprehensive study of computer cloud concepts, architectures, and physical systems, technical challenges and advantages across the varied cloud service models. The course covers the essentials necessary to leverage cloud computing in a pragmatic way so that computational efficiency, cost, global scale, and productivity can be fully realized. Industrial and consumer applications and services, such as e-commerce, Industry 4, Internet of Things (IoT), video and audio streaming, will be presented.

ECEG 777. Quantum Computing. 3 Credits.

This course provides a theoretical and practical treatment of quantum computing. Topics covered include physics of information processing, quantum logic, quantum algorithms including quantum states as Hilbert space vectors and their matrix representations. Shor's factoring algorithm and Grover's search algorithm, quantum error correction, quantum communication, and cryptography. Applications in cybersecurity, financial modeling, drug development and artificial intelligence.

ECEG 779. Remote Sens Sys Techniques. 3 Credits.

This course is intended to provide the engineering and physical principles to remote sensing of objects. This course covers the principles of image sensors and techniques, image formation, interpretation and analysis, interpretation, remote sensing theory, digital image analysis. Machine learning and deep learning techniques will be applied for object recognition and classification. Defense, commercial and environmental applications will be introduced and discussed.

ECEG 780. Space Systems Engineering. 3 Credits.

This course is intended to provide the engineering and physical principles for the design of space systems. Enhanced understanding of the big picture of space systems engineering processes and their application in the mission life cycle will be presented; with emphasis on the electro-optical sensing, detection, classification, monitoring of space resident objects (SRO)s. Advanced machine learning and deep learning techniques will be presented for object detection, tracking, recognition and classification. Defense, and commercial applications will be introduced and discussed.

ECEG 781. Computer Architecture I. 3 Credits.

Evolution of computer architecture spanning from the CISC machines to the RISC machines, from the pipelined to superscalar architectures; from multithreaded to parallel processors. Hardware and software processor design trade-off and performance evaluation; Data representation and instruction sets. Control design: Hardware and microprogrammed. Memory organization: Virtual segmentation and cache; system organization: Bus control and 1/O. Pre-requisite: Senior Status Equivalent to EECE 520.

ECEG 782. Grid Integration of Wind Energy. 3 Credits.

The objective of this course is to familiarize students with various essential aspects in harnessing wind energy and its conversion and delivery as electricity. A broad understanding of essential elements in wind-electric systems: turbines, wind- plant development and their integration into the utility grid, environmental impacts, wind forecasting and more. Cross-listed with EECE 482.

ECEG 790. Advanced Topics in Artificial Intelligence (AI) in Electrical & Computer Engineering. 3 Credits.

The course explores advanced electrical and computer engineering based Artificial Intelligence (AI) systems and tool chains on a variety of levels. The focus of the course is to utilize AI techniques to solve large-scale engineering problems. The course will cover topics of current interest to graduate electrical engineering and computer engineering students. The subject matter of the course will be announced prior to the start of the semester.

ECEG 792. Adv Proj Electrical/Comp Engr. 3 Credits.

ECEG 793. Advanced Study in Electrical or Computer Engineering. 3 Credits.

Individual study of a selected topic in electrical engineering under the supervision of a staff member.

ECEG 794. Special Topic: in Electrical Engineering. 3 Credits.

Topics of current interest to graduate Electrical Engineering students; subject matter will be announced in advance of semester offering.

ECEG 795. Special Topic: in Computer Engineering. 3 Credits.

Topics of current interest to graduate Computer Engineering students; subject matter will be announced in advance of semester offering.

ECEG 796. Special Topic: in Electrical and Computer Engineering. 3 Credits.

ECEG 797. Sustainable Energy Sources. 3 Credits.

This course presents basic information on Energy outlook, interconnection issues of distributed alternate energy resources, efficiency of power production, electric energy conversion and storage (fossil fuel, nuclear, hydro, solar, fuel cells, wind, and batteries). This course also explores the different energy link integration methodologies. Pre-requisite: Senior Status.

ECEG 799. Master's Thesis Research. 1-6 Credit.

A Master of Science thesis option entails 24 course credits and 6 master’s research credits, namely, ECEG 799. Research undertaken under the thesis option should exhibit a thorough understanding of advanced scientific thought and an ability to apply advanced engineering design principles, and planning.