Graduate Course Descriptions

3 credits

Software management studies processes and concepts for planning and monitoring all software life-cycle phases. Topics include management models and structures, project planning including scheduling, effort estimation and risk management, project personnel and organization, project control (monitoring, measurement, correction and performance standards), software configuration management, and process description languages and tools. Crosslisted with CISC 611.

3 credits

Key software design concepts are introduced. Topics include basic design concepts, principles of good design, design strategies, software architecture and styles of architectural design, and design and architectural notations and languages. Detailed design, including design patterns and component design are also covered. Implementation issues that affect the design, including design support tools and tools for analyzing designs are discussed. Crosslisted with CISC 612

3 credits

Rigorous methods to elicit, analyze, and specify the requirements of a software system. The tasks range from identifying stakeholders and their goals producing a precise software specification document. Topics may include data flow diagrams, use cases, UML sequence and collaboration diagrams, finite state machines, requirements for real-time and concurrent systems, entity-relationship diagrams, and logic-based specifications, as well as the analysis of specifications for consistency and completeness. Crosslisted with CISC 613.

3 credits

Formal approaches to the specification, verification, and design of software systems. Topics include representing programs as transition systems; liveness and safety properties; state space reachability; explicit, symbolic and automata-based model checking; temporal logics; symbolic execution; automated theorem-proving; and relational calculus. Learn to use state-of-the-art tools based on these methods, such as the model checker Spin. Crosslisted with CISC 614.

3 credits

Study of software testing and maintenance methodologies for modern software. Topics include approaches to automatic test case generation, test oracles, test coverage analysis, regression testing, program understanding, and software maintenance tools. A primary focus will be automation in software testing and maintenance approaches. Crosslisted with CISC 615.

3 credits

Introduction to compiler design, syntax and semantics, code generation and optimization. Design of high performance computers together with high performance optimizing compilers as an integral unit. Software/hardware tradeoffs in pipelined computers, super-scaler computers, and computers embedded in other systems.

3 credits

Course covers hardware/software co-design approaches for building embedded systems. Topics include, but are not limited to: microprocessors and FPGAs; VHD; C; and Python; gate-level, register transfer level, and IP level design; hardware/software co-design; memory, bus, and IO ports; IP cores and customization; hardware accelerators, and cyber security.
RESTRICTIONS: Students should have previous knowledge of VHDL programming language.

3 credits

This course focuses on the design, fabrication, and construction of Printed Circuit Boards and on using FPGA design kits.

PREREQ: CISC 220, CPEG 222

3 credits

Advanced current mirrors, voltage references, amplifiers, frequency compensation, negative feedback systems and stability, Opamps, IC layout.

RESTRICTIONS: Knowledge of fundamentals of semiconductor diodes, field-effect and bipolar transistors; single-stage amplifier circuits and small-signal analysis; operational amplifier basics.

3 credits

Foundation principles, architectures, and techniques employed in computer and communication networks. Focuses on mechanisms used in TCP/IP protocol suite. Topics include connection management, end-to-end reliable data transfer, sliding window protocols, quality of service, flow control, congestion control, routing, LANs, framing, error control, analog versus digital transmission, packet versus circuit switching, multiplexing.

PREREQ: An undergraduate level course in computer architecture and operating systems.

RESTRICTIONS: Knowledge of probability and statistics recommended. Credit cannot be received for any of the following courses: CISC 250, CPEG 419, CISC 450, ELEG 651.

3 credits

Provides an introduction to the principles of parallel computer architecture. Begins at a level that assumes experience in introductory undergraduate courses such as digital system design, computer architecture, and microprocessor based systems. Crosslisted with ELEG 652.

3 credits

New commodity computing devices, e.g., GPUs, bring the originally elite high performance computing into the reach of general public. Principles of program optimization, GPU and IBM Cell architecture, along with concepts and techniques for optimizing general purpose computing on the new hardware.

3 credits

With the increasing amount of textual information, it is important to develop effective search engines, such as Google, to help users manage and exploit the information. Examine the underlying technologies of search engines and get hands-on project experience. Requires good programming skills.

4 credits

Study of CMOS VLSI devices, circuits and systems implemented in VLSI. CAD tools for the design and simulation of VLSI. Topics include the performance and limitations of VLSI systems, low level circuit design and system design with an emphasis on digital systems. Major chip design project required.

PREREQ: Students should have previous knowledge of logic design and MOS transistor operation.

3 credits

Introduction to computer and network security and covers the foundation security policies and methods to provide confidentiality, integrity, and availability, as well as cryptography, auditing, and user security. Topics are reinforced with hands-on exercises run in a virtual machine environment. May be crosslisted with CISC 665, ELEG 665, MISY 665.

RESTRICTIONS: Students who received credit in CISC 465, CISC 665, CPEG 465, ELEG 465, ELEG 665, MISY 465 or MISY 665 are not eligible to take this course without permission.

1–12 credits

Independent Study

3 credits

This seminar-style cybersecurity course covers one specific discipline of information security known as application security. This discipline (APPSEC) refers to the development of software that can continue to function correctly even under constant scrutiny and attack by determined adversaries.

RESTRICTIONS: Programming experience in a high level language (e.g. C, C++, java, python). Credit cannot be received for both CPEG 470 and CPEG 670.

3 credits

This cybersecurity course introduces techniques used to (1) identify strengths and exploit weaknesses in networked systems or hosts, and (2) reverse engineer programs of unknown origin and identify their function so to classify them as malware and highlight the level of risk that they represent.

PREREQ: CPEG 465/CPEG 665 or CPEG 494/CPEG 694. Programming experience in assembly language (CISC 260, CPEG 222, or equivalent).

RESTRICTIONS: Credit cannot be received for both CPEG 471 and CPEG 671.

3 credits

This cybersecurity course explores modern Cryptography covering algorithms and cryptosystems, cryptanalysis, and best practices for application and implementation of crypto in software systems.

PREREQ: CPEG 465/CPEG 665 or MATH 549 or equivalent.

RESTRICTIONS: Programming experience in a high level language (e.g. C, C++, java, python). Credit cannot be received for both CPEG 472and CPEG 672.

3 credits

This cybersecurity course introduces the virtualization and cloud computing technologies used in most modern online services. The unique and conventional security issues related to protecting these types of systems are addressed and reinforced with hands-on exercises run in a virtual machine environment.

PREREQ: CPEG 465/CPEG 665, ELEG 465/ELEG 665, CISC 465/CISC 665, MISY 465/MISY 665 or CPEG 494/CPEG 694, ELEG 494/ELEG 694 or experience with virtualization and computer networking.

RESTRICTIONS: Credit cannot be received for both CPEG 473 and CPEG 673.

3 credits

The main emphasis of this course is cybersecurity for embedded systems devices and Internet of Things. The major topics covered include the instruction set and CPUs of embedded devices, the design of secure computing architectures from assembly program design to operating systems. Additional emphasis is given to Internet of Things applications, such as smart homes, embedded microprocessors, and automotive systems.

PREREQ: CPEG 665.

RESTRICTIONS: Credit cannot be received for both CPEG 475 and CPEG 675.

3 credits

This cybersecurity course introduces the theory and practices used to help make a computer program secure and provide the skills needed to implement programs that are free from vulnerabilities.

RESTRICTIONS: Programming experience in a high level language (e.g. C, C++, java, python). Credit cannot be received for both CPEG 476 and CPEG 676. Graduate or upper level software course (design, etc.) recommended.

3 credits

Technical practicum guided by the individual student’s interests. The student will contribute a significant software engineering project either on campus or in association with an off-campus private business or government agency. Must be arranged with, and approved in advance by, a CIS or ECE faculty member. Crosslisted with CISC 691.

3 credits

Practical treatment of the defensive techniques used to harden computer systems to make them less vulnerable to cyber-attacks. Defect management, configuration/hardening, account control, logs/auditing, and risk assessment are covered and reinforced with hands-on exercises run in a virtual machine environment.
May be crosslisted with ELEG 694.

3 credits

Introduction to digital forensics as used to analyze criminal evidence in computer systems and digital media. Forensic tools and techniques for storage and memory analysis of windows/linux, network traffic, documentation are covered and reinforced with hands-on exercises run in a virtual machine environment. May be crosslisted with ELEG 695.

3 credits

Examine varied topics in cybersecurity to coincide with the interests of students and current faculty. Potential topics include: (1) applications, web or cloud security, (2) risk management and incident response, (3) malware and reverse engineering, or (4) wireless, smartphone, or SCADA security. May be crosslisted with ELEG 696.

3 credits

This seminar course explores areas in advanced computer and network security not covered in introductory cybersecurity classes. Course provides insight into realistic complex defensive and offensive cybersecurity topics such as DoS attacks, DNS security, Email spam, On-line Authentication, Phishing, Cloud Security, Malware, and Web security.

PREREQ: CPEG 465/CPEG 665. Familiarity with basic networking protocols and operating systems.

RESTRICTIONS: Credit cannot be received for both CPEG 497 and CPEG 697.

3 credits

This course focuses on the design of reliable, robust, and secure computing systems, ranging from low-end embedded systems to high-end supercomputers. Through paper reading and discussion, students will learn cutting-edge techniques in enhancing reliability and security of different computing systems. The course will also train the students to read and review scientific articles, summarize and present a given research topic, as well as write literature surveys. May be crosslisted with ELEG 852.

RESTRICTIONS: May be repeated two times for credit.

3 credits

Introduction to reliability challenges in computer systems, including permanent, transient, and intermittent faults. Various types of redundancy for fault tolerant computing will be studied. Hardware/software approaches for reliability enhancement in various computer systems will be examined, emphasizing tradeoffs involving performance, power, and reliability.

1–12 credits

Independent Study.

1–6 credits

Independent and laboratory study conducted for the purpose of contributing new data and theory in some field of Cybersecurity in which information is lacking. Although supervised, the work will be independent in character to encourage the development of initiative.

3 credits

This course provides a comprehensive coverage of both the theoretical foundation and numerical algorithms for convex optimization. The main objectives of this course are to give students the tools and training to recognize convex optimization problems that arise in applications, and to present the basic theory of such problems as well as how to solve them numerically. Topics covered in this course include: Convex sets, functions, and optimization problems; Basics of convex analysis; Least-squares, linear and quadratic programs, semidefinite programming, minimax; Optimality conditions, duality theory, theorems of alternative; Descent methods, Newton’s method, interior-point method; Applications.

RESTRICTIONS: Knowledge of linear algebra (e.g. MATH 351) and probability theory (e.g. ELEG 310); mathematical maturity in general.

3 credits

This advanced course on machine learning features an in-depth treatment of modern learning theory and emphasizes its interplay with real-world learning algorithms. The main goal of this course is to get students started in research, in particular, to help them transition from knowing how to implement towards exploring why to do this and how to do better. Students will carry out research projects, and the hope is that some of these projects will result in research papers that can be published in top machine learning venues. Major topics covered include the following. PAC Learning Framework: Empirical Risk Minimization.

RESTRICTIONS: Exposure to a first course on machine learning (e.g. ELEG/FSAN 815), or knowledge on probability theory (e.g. ELEG 310) and linear algebra (MATH 351); mathematical maturity in general.

3 credits

An introduction to digital imaging systems, their mathematical modeling, and the imaging pipeline processing and optimization addressed using conventional signal processing tools as well deep learning and convolutional neural networks. Topics covered include sensors, Fourier analysis, sampling, filtering, aliasing, de-blurring, de-mosaicing, and super-resolution. Signal processing and deep learning solution for computer tomography, 3D LiDAR imaging, and hyper-spectral imaging are covered.

PREREQ: ELEG 305

3 credits

Engineering Machine Learning Systems are applied in an array of real-world applications. This course focuses on their conceptualization, estimation, computational implementation, and optimization. Topics supervised and unsupervised learning, linear and logistic regression, dimensionality reduction, regularization, neural networks, convolution neural networks, decision trees, and select additional deep learning topics.

PREREQ: Basic probability theory, discrete math, simple calculus, linear algebra (preferred), and programming experience, particularly in Python, or equivalents.

3 credits

Fundamentals of ocean and atmosphere remote sensing including space platforms, their orbits, instruments, data retrieval and image processing methods. Oceanographic and atmospheric applications of remote sensing and new developments in sensors and data analyses. Crosslisted with MAST 606.

1 credit

BASIC ELECTRICAL MACHINES

RESTRICTIONS: No ELEG or CPEG majors may take the course.

3 credits

Introduction to electric power systems and interfaces with energy sources. Covers electric power generation, transmission, distribution; residential, commercial, and industrial systems; components, operation, losses, metering and load management.

3 credits

Thermodynamic laws and concepts; thermodynamic potentials, Legendre transformations, and Maxwell relations. Concepts of probability. Statistical mechanics concepts: microstates and macrostates; ensembles; partition functions; connections to thermodynamics. Many particle systems, equations of state, chemical potential, phase equilibria, phase transitions, Monte Carlo simulations in statistical physics. Crosslisted with PHYS 616.

3 credits

An examination and analysis of smart grid technologies, applications, and transformational impacts on the electric utilities. Topics include smart grid fundamentals, objectives, technologies (power, communications and information), architectures, applications, evolution, and implementation challenges.

3 credits

3 credits

State-space analysis of linear dynamical systems. Solution of state-space equations, and analysis of structural system properties based on eigenvalues and eigenvectors. Similarity transformations and decompositions. Lyapunov stability. Observability and controllability. State feedback control design. Crosslisted with MEEG 621.

PREREQ: MATH349 or MATH351 or graduate status.

3 credits

The basic goals, principles and techniques of semiconductor materials processing are discussed. Emphasis is on physical explanations of how devices and processes work rather than on elaborate mathematical models.

3 credits

This course focuses on the fundamentals and practical consideration of the myriad techniques that are used to characterize electronic materials. It includes the theoretical underpinnings of the techniques and discusses applicability and limitations. Crosslisted with MSEG 629.

3 credits

Introduces basics of solar cell technology, applications, and systems. Presents critical issues in research, manufacturing, cost and performance. Compares Si wafer and thin film solar technology. Analyzes off-grid, residential, building integrated, centralized power systems. Discusses other solar energy concepts.

3 credits

Information theory establishes the theoretical limits that can be achieved in communications systems, and provides insights about how to achieve these limits in practical systems. Covers lossless and lossy compression, and studies the maximum information rate achievable in communications over noisy channels.

PREREQ: Undergraduate course in probability.

3 credits

Theory of discrete-time signals and systems with emphasis on the frequency domain description of digital filtering and discrete spectrum analysis, fast Fourier transform, z-transform, digital filter design, relationship to analog signal processing. domain description of digital filtering and discrete spectrum analysis, fast Fourier transform, z-transform, digital filter design, relationship to analog.

3 credits

Provides the mathematical foundation for advanced studies in information processing. In addition, Matlab and Simulink, tools commonly used by electrical and other engineers, are introduced in the context of assisting in solving the mathematical problems. Examines differential equations and matrix and linear algebra. Solution to both linear and non-linear ordinary differential equation are found analytically and with Matlab. For problems without analytical solutions, numerical ones are sought using Simulink.

PREREQ: Must be a graduate of an accredited undergraduate engineering program.

3 credits

Fourier transform, z-transform, digital filter design, relationship to analog.

RESTRICTIONS: Requires permission of instructor.

3 credits

Reviews basic concepts of discrete and continuous time signals, control systems, and linear algebra. Transforms, sampling, aliasing, linear algebra and systems of equations, matrix factorizations, eigenvalues and eigenvectors, least squares, and the Cayley-Hamilton theorem are studied.

PREREQ: ELEG305 and MATH342 or MATH349 or equivalents

3 credits

The theory and applications of digital communications including modulation, pulse shaping, and optimum receiver design for additive white gaussian noise and bandlimited channels.

PREREQ: Undergraduate course in probability, signals and linear systems

3 credits

Introduction to random vectors and random processes and second-order moment and spectral characterizations. Linear transformations of stationary processes. Parameter estimation. Orthogonality principle and optimal linear filtering. Levison recursion and lattice prediction filters. AR and ARMA models and their Yule-Walker characterizations. Classical and modern spectrum estimation.

PREREQ: Undergraduate courses in probability and signals and linear systems

3 credits

Energy flows are examined in our society including all sources, conversions and conversion efficiencies, and end uses. Both existing and alternative energy sources are presented, especially with regard to total resource availability. Thermodynamics of conversion efficiency is covered, as well as efficiency measures available in end use.

RESTRICTIONS: Freshman level calculus.

3 credits

A fundamental course in optoelectronic materials and devices suitable for undergraduate level and graduate students in electrical engineering, engineering physics, materials science and other related engineering departments. It serves as a stepstone class for ELEG 682.

3 credits

The radiation characteristics of antennas, numerical and analytical antenna analysis methods and design techniques for many types of antenna. Topics include wire antennas, antenna arrays, broadband antennas and microstrip antennas.

PREREQ: ELEG 320 or ELEG 413.

3 credits

This course presents a systems approach to designing RF systems for wireless and mobile communications. It covers topics including: (1) A review of Electromagnetics, (2) Transmission line theory with Smith Charts, (3) RF and Microwave Sources, (4) RF Amplifiers (discuss classes of amplifiers and the effects of noise figure, compression and non-linearities), (5) RF Mixer design (discuss types and figures of merit, including conversion loss, harmonic distortion, etc.), (6) RF Filter Design (overview of first and higher order filters), (7) Analog-to-Digital as well as Digital-to-Analog Converters, (8) Noise (cover the origin of thermal noise, shot and flicker noise as well as others in the context of probability theory), (9) Antennas (brief overview in the context of their input impedance and bandwidth from a systems perspective), (10) Atmospheric and environmental considerations of signal propagation and loss, (11) RF Photonics, and (12) Applications including: computing networks, wireless communications, Radar, and electronic sensing

3 credits

An introductory course in the analysis and design of passive RF components and microwave circuits. The goal is to bridge the gap between our theoretical EM courses and practical methods for the analysis, design and characterization of RF circuits. A design project will constitute a major part of the course.

3 credits

Introduction to the operating principles of nanoscale optical and electronic devices, with emphasis on how nanotechnology and quantum mechanics affect devices with reduced sizes and dimensions. Develops the performance and limitations of devices based on quantum wells, wires, dots, and nanophase materials.

3 credits

Techniques for the design of optical filters and optoelectronic devices with thin films and the fundamental electromagnetic and solid state physics that determine the optical properties of solids.

RESTRICTIONS: Students should have some electromagnetics and solid state physics background.

3 credits

Development and application of Maxwell’s equations as they apply to the analysis of guided wave, radiation, and scattering problems. Topics include wave propagation, reflection and transmission, vector potentials, transmission lines and cavities, and special emphasis on antennas and scattering structures.

3 credits

Instruction in design and fabrication of simple bi-polar and MOS integrated circuits. Specific topics include semiconductor device and integrated circuit design, photolithographic mask design and fabrication, photolithography, N-diffusion and P-diffusion, P-MOS, metallization, and device and integrated circuit testing.

3 credits

Foundation principles, architectures, and techniques employed in computer and communication networks. Focuses on mechanisms used in TCP/IP protocol suite. Topics include connection management, end-to-end reliable data transfer, sliding window protocols, quality of service, flow control, congestion control, routing, LANs, framing, error control, analog versus digital transmission, packet versus circuit switching, multiplexing. Crosslisted with CISC 650.

RESTRICTIONS: Knowledge of probability and statistics recommended. Credit cannot be received for CISC 650 and any of the following courses: CIS250, CPEG419, CIS450, ELEG651.

3 credits

Provides an introduction to the principles of parallel computer architecture. Begins at a level that assumes experience in introductory undergraduate courses such as digital system design, computer architecture, and microprocessor based systems. May be crosslisted with CPEG 652.

3 credits

This is the second course in electric power systems which covers the construction materials and design principles of indoor and underground three phase low and high voltage electric power systems, system economics, reliability, load characteristics, load management, and metering.

3 credits

A microgrid is a self-reliant electrical grid with multiple energy sources, storage and local control that can operate either connected to or disconnected from the conventional electric grid. Microgrids incorporate new technologies, such as solar photovoltaic (PV) modules, lithium-ion batteries, fuel cells, electric vehicles (EV), and energy management systems on scales from kilowatts to megawatts. In the event of a natural disaster or cyber-attack, microgrids are designed to provide their hosts with 100% reliable energy supply.

​​This course will cover the design and operation of reliable, economical microgrids integrating generation (photovoltaics, fuel cells, gas generators, and wind turbines), energy storage, sensing, communication, cybersecurity, and control. Concepts will be reinforced through the students’ use of industry-standard HOMER Grid software tool for techno-economic analysis. We will include both case-studies of existing microgrids and student design projects using HOMER Grid.

3 credits

Foundations for the creation of successful advanced mobile services, including the interplay of business and technology evolution, methodologies, architectures and paradigm shifts that accompany the development of converged user centric intelligent telecommunication services from location sensitive and navigation services, to social networking and remote sensing.

3 credits

Focuses on the critical financial, legal, scientific and engineering issues that must be confronted during the initial planning stages of a start-up enterprise. Students work in teams to develop a business plan for a real world/business product offering.

0 credits

Lectures and discussions by guest speakers, faculty and students on specialized topics in materials and devices.

0 credits

Lectures and discussions by guest speakers, faculty and students on specialized topics in digital systems.

0 credits

Lectures and discussions by guest speakers, faculty and students on specialized topics in signal processing and communications.

0 credits

Lectures and discussions by guest speakers, faculty, and students on specialized topics in biomedical engineering.

3 credits

Introduction to computer and network security and covers the foundation security policies and methods to provide confidentiality, integrity, and availability, as well as cryptography, auditing, and user security. Topics are reinforced with hands-on exercises run in a virtual machine environment. Crosslisted with CPEG 665, CISC 665 and MISY 665.

RESTRICTIONS: Students who received credit in CISC 465, CISC 665, CPEG 465, CPEG 665, ELEG 465, MISY 465 or MISY 665 are not eligible to take this course without permission.

1–12 credits

1–12 credits

3 credits

This course covers the fundamentals of detection and estimation theory for statistical signal processing. Topics include hypothesis testing theory, signal detection theory for both deterministic and random signals, signal estimation theory with various optimal estimators for both deterministic and random parameters, and their properties and performance analysis.

RESTRICTIONS: Knowledge of material covered in ELEG 305, ELEG 306, ELEG 310 or equivalent courses.

3 credits

Brief review of the semiconductor devices principles, including two terminal and three terminal devices: PN diodes, Tunneling Diodes, MOSFETs, Tunneling Diodes, Bipolar Junction Transistors, high frequency electronics like S parameters will be introduced. High frequency electronic devices principles will be discussed. Material transfer process, Lithography, metal deposition, atomic layer deposition, will be demonstrated. The full fabrication process of making MOSFET using III-V materials on insulator will be instructed and conducted. Students gets hands-on experience on advanced device design and fabrication technology.

PREREQ: ELEG 340 or ELEG 422 or equivalent course.

3 credits

Mathematical methods in Human Physiology, covering cellular, tissue, organ, and integrated systems. Dynamic modeling of homeostasis, endocrine regulatory systems, immune response dynamics, mutation and selection. Mathematical methods covered include linear and nonlinear differential equations, Lyapunov analysis, mass action, Hamming spaces, reaction-diffusion equations, and simulation. Crosslisted with BMEG 671.

3 credits

Physics, instrumentation, system design, and image reconstruction algorithms will be covered for the following modalities: radiography, x-ray computed tomography (CT), single photon emission computed tomography (SPECT), positron emission tomography (PET), magnetic resonance imaging (MRI), and real-time ultrasound. Crosslisted with BMEG 679.

3 credits

Introduces important technology of remote sensing to further our understanding of Earth’s environment. Gain an in-depth look at the principles, techniques and applications of remote sensing. Basic skills in computer processing of digital satellite images using ENVI and ArcGIS software are provided. Crosslisted with MAST 681 and GEOG 681.

3 credits

Principles of classical optics and their applications. Topics include wave optics, material dispersion, geometrical optics, ray tracing, ABCD matrices, birefringence and Jones’ formalism, Gaussian optics, coherence, interference, diffraction, pulse propagation and non-linear optics. Specific applications including optical components and instrumentation, imaging techniques, resonators and Fourier optics. Apply fundamental principles of optics and interaction between light and matter (photonics).

3 credits

This seminar covers design of electric vehicles and charging infrastructure, existing and needed policies, consumer perspective on electric vehicles, and the use of electric vehicles for grid services, including leveling variable generation. Crosslisted with MAST 684.

3 credits

Introduction of basic RADAR concepts and operational scenarios. The RADAR range is developed as are concepts related to RADAR cross-section, waveform design, antennas, transmitter and receivers.

3 credits

This is a basic course in motor and generator performance and application. Students will learn about electric power and energy, mechanical power and energy, and the torque, speed, efficiency, and economics of the various motor and generator designs.

3 credits

Practical treatment of the defensive techniques used to harden computer systems to make them less vulnerable to cyber-attacks. Defect management, configuration/hardening, account control, logs/auditing, and risk assessment are covered and reinforced with hands-on exercises run in a virtual machine environment. Crosslisted with CPEG 694.

3 credits

Introduction to digital forensics as used to analyze criminal evidence in computer systems and digital media. Forensic tools and techniques for storage and memory analysis of windows/linux, network traffic, documentation are covered and reinforced with hands-on exercises run in a virtual machine environment. Crosslisted with CPEG 695.

3 credits

Examine varied topics in cybersecurity to coincide with the interests of students and current faculty. Potential topics include: (1) applications, web or cloud security, (2) risk management and incident response, (3) malware and reverse engineering, or (4) wireless, smartphone, or SCADA security. Crosslisted with CPEG 696.

3 credits

Computational/mathematical techniques for modeling & analysis of biological systems. Includes properties of gene-regulatory and signaling networks; network reconstruction from data; stochastic modeling to study cellular variation & physiological modeling. Crosslisted with BINF 695.

3 credits

Provides a technical review of systems biology approaches including genomics, transcriptomics, proteomics, metabolomics, and bioinformatics as well as applications in tissue engineering, stem cell differentiation, and drug delivery. Intended for PhD students in interdisciplinary life science and engineering programs. Crosslisted with BINF 816.

3 credits

Mathematical preliminaries. Maxwell equations. Symmetries, potentials and conservation laws for general electromagnetic field. Electrostatics and multipole expansion. Conducting and dielectric matter. Laplace and Poisson equations. Magnetostatics and multipole expansion. Magnetic force and energy. Magnetic matter. Dynamic and quasistatic fields. Crosslisted with PHYS 809.

3 credits

Standard and modern developments in channel coding. Reviews information theory topics, then introduces convolutional codes and trellis-coded modulation, iterative decoding, including turbo codes and low-density parity check codes.

3 credits

Fundamentals and current techniques in wireless digital communications, including propagation, modem design, fading countermeasures, and multiple access techniques, such as FDMA, TDMA, and CDMA.

PREREQ: Probability and linear systems.

3 credits

Basic concepts of quantum statistical mechanics, density matrix, and quantum partition function. Ideal Bose and Fermi gases; Bose-Einstein condensation. Mean field and Landau theories of phase transitions; critical phenomena; introduction to renormalization group methods. Linear response theory and Boltzman equation. Interacting quantum many-particle systems. Crosslisted with PHYS 813.

3 Credits

Introductory course in machine learning that covers the basic theory, algorithms, and applications with examples in financial, medicine, and engineering. How can machines learn, how they do it, and how well can they learn? Linear, nonlinear, and neural network models. Regularization methods and principles of sparsity priors to address overfitting. Training vs. testing, the VC dimension and bias-variance trade offs. Support vector machines, and deep learning networks including convolutional, recurring, generative, and transformer neural networks. Concepts reinforced in tensor flow experiments. Recommended: Basic programming skills, a first course in linear algebra and statistics. May be crosslisted with FSAN 815.

3 credits

Introduction to the analysis and processing of massive and/or high-dimensional data. Large-scale machine learning problems can involve growth in the number of data points, features, target variables, or related prediction tasks. Approaches to address these cases rely on concepts from optimization theory, statistics, and artificial neural networks. Computational and statistical scaling from both theoretical and practical perspectives are covered. May be crosslisted with FSAN 817 and CISC 817.

3 credits

Introduces the major modern computational methods for the analysis of frequency domain electromagnetics problems. The finite element method and the method of moments are covered. Students will apply these techniques to radiation and scattering problems involving metal and dielectrics.

PREREQ: ELEG 648.

3 credits

Modern telecommunications and datacom systems operate at frequencies in the radio frequency (RF) and microwave range. The basic concepts and technologies required to design RF and microwave devices and circuits are explained. Examples of applications to wireless and lightwave systems are discussed.

RESTRICTIONS: Undergraduates require permission from the instructor.

3 credits

Provides an understanding of the basic principles underlying the field of optical information processing. Emphasis are on coherent optical image processing based on Fourier optics, holography, and acousto-optics.

PREREQ: ELEG 640 and ELEG 648 or permission of instructor

3 credits

Modern machine learning methodologies are covered & concepts are reinforced through implementations focusing on array of contemporary classification problems. Topics include linear and logistic regression, neural networks, support vector machines, clustering, dimensionality reduction & deep learning.

3 credits

This (graduate-only) elective involves students solving soft materials (MAT) focused projects submitted by scientists in industry and national laboratories using high-performance computing (HPC) and/or data science (DS). Each project is tackled by a team of ~3-4 students with 1-2 students from HPC/DS technical background and 1-2 from MAT technical background. The co-instructors and industrial/national lab mentors (who submitted the projects) guide the teams through teamwork, collaboration, and oral & written communication exercises. Crosslisted with CHEG 848.

3 credits

Concentrated study on selected areas in Financial Services Analytics. Crosslisted with FSAN 850 and CISC 850.

3 credits

This course focuses on the design of reliable, robust, and secure computing systems, ranging from low-end embedded systems to high-end supercomputers. Through paper reading and discussion, students will learn cutting-edge techniques in enhancing reliability and security of different computing systems. The course will also train the students to read and review scientific articles, summarize and present a given research topic, as well as write literature surveys. Crosslisted with CPEG 852.

RESTRICTIONS: May be repeated two times for credit.

3 credits

Explains basic goals, principles and techniques of integrated optics. Topics include optical wave guides, scattering and absorption, couplers, electro-optic modulators, acousto-optic modulators, semiconductor lasers, photonic crystals and optical detectors. Includes applications of optical integrated circuits. Emphasis on physical explanations of how devices and systems work rather than on elaborate mathematical models.

3 credits

Principles of device operation and circuit characteristics for microwave/millimeter-wave FET, IMPATT, TRAPPATT, Gunn diode, varactor diode, p-i-n diode, tunnel diode. Sub-millimeter-wave and terahertz-frequency devices also described. Covers both waveguide circuits and microwave integrated circuits. Emphasis on physical explanations of how devices and systems work rather than on elaborate mathematical models.

3 credits

Fundamentals and recent developments in the growth of epitaxial films of electronic/optical materials and devices. Topics include vacuum technology, growth thermodynamics, heterojunction physics, materials characterization, and practical considerations. Focus on molecular beam epitaxy, but discuss complementary techniques. Crosslisted with MSEG 860.

1–12 credits

1–12 credits

1–6 credits

Laboratory study conducted for the purpose of contributing new data and theory in some fields of electrical engineering in which information is lacking. Although supervised, the work will be independent in character to encourage the development of initiative.

3–12 Credits

Research and readings in preparation of dissertation topic and/or qualifying examinations for doctoral students before admission to candidacy but after completion of all required course work.

RESTRICTIONS: Not open to students who have been admitted to candidacy.

1–12 Credits