158 courses with the subject EECE, each shown exactly as we captured it from the college's catalog, with every element we hold. Where the wording looks broken, that is our reading of the catalog, not the college's text.
Offers elective credit for courses taken at other academic institutions. May be repeated without limit.
Engages students in problem solving from an engineering perspective, offering essential computer hardware and software knowledge and experience. Computational problem solving involves expressing solutions to engineering problems in a way that a computer can efficiently solve. As our world continues to become more automated and interconnected, it becomes increasingly important to be able to leverage computer software and hardware, enabling us to evaluate and solve real-world engineering challenges. Offers students an opportunity to learn engineering solution design, leveraging a high-level programming language appropriate for interfacing hardware-based systems. Stresses best practices in design. Coursework includes programming assignments, quizzes, and a final project, offering students a number of ways to demonstrate their understanding of the concepts.
Prerequisite(s): (GE 1111 with a minimum grade of D- or GE 1502 with a minimum grade of D- or ENGR 155M with a minimum grade of D- ); (MATH 2341 (may be taken concurrently) with a minimum grade of D- or MATH 315M (may be taken concurrently) with a minimum grade of D- ); (PHYS 1155 (may be taken concurrently) with a minimum grade of D- or PHYS 1165 (may be taken concurrently) with a minimum grade of D- or PHYS 1175 with a minimum grade of D- ); EECE 2140 (may be taken concurrently) with a minimum grade of D- Attribute(s): NUpath Analyzing/Using Data
Prerequisite(s): EECE 2140 (may be taken concurrently) with a minimum grade of D- or CS 2510 (may be taken concurrently) with a minimum grade of D-
Prerequisite(s): MATH 1342 with a minimum grade of D- or MATH 211M with a minimum grade of D- Corequisite(s): EECE 2211
Corequisite(s): EECE 2210
Prerequisite(s): CS 1800 with a minimum grade of D- or MATH 209M with a minimum grade of D- Corequisite(s): EECE 2311
Corequisite(s): EECE 2310
Prerequisite(s): EECE 2160 with a minimum grade of D- or EECE 2310 with a minimum grade of D- Corequisite(s): EECE 2323
Corequisite(s): EECE 2322
Prerequisite(s): EECE 2150 with a minimum grade of D- or EECE 2210 with a minimum grade of D- or BIOE 3210 with a minimum grade of D- Corequisite(s): EECE 2413
Corequisite(s): EECE 2412Attribute(s): NUpath Writing Intensive
Prerequisite(s): (EECE 2150 with a minimum grade of D- or EECE 2210 with a minimum grade of D- or BIOE 3210 with a minimum grade of D- ); (MATH 2341 with a minimum grade of D- or MATH 315M with a minimum grade of D- )
Prerequisite(s): (EECE 2150 with a minimum grade of D- or EECE 2210 with a minimum grade of D- or BIOE 3210 with a minimum grade of D- ); (MATH 2321 with a minimum grade of D- or MATH 316M with a minimum grade of D- ); (PHYS 1155 with a minimum grade of D- or PHYS 1165 with a minimum grade of D- or PHYS 1175 with a minimum grade of D- )Corequisite(s): EECE 2531
Prerequisite(s): (BIOE 3210 with a minimum grade of D- or EECE 2150 with a minimum grade of D- or EECE 2210 with a minimum grade of D- ); (MATH 2321 with a minimum grade of D- or MATH 316M with a minimum grade of D- ); (PHYS 1155 with a minimum grade of D- or PHYS 1165 with a minimum grade of D- or PHYS 1175 with a minimum grade of D- )Corequisite(s): EECE 2530
Prerequisite(s): EECE 2140 (may be taken concurrently) with a minimum grade of D- or CS 2100 (may be taken concurrently) with a minimum grade of D- or CIS 201M (may be taken concurrently) with a minimum grade of D-
Prerequisite(s): EECE 2160 with a minimum grade of D- or CS 1500 with a minimum grade of D-
Offers students an opportunity to develop a proposal for a design project that uses engineering technologies to improve the lives of individuals with cognitive or physical disabilities. Offers student project groups an opportunity to work with end users and caregivers at local nursing homes and special education schools to assess a specific need, research potential solutions, and develop a detailed proposal for a project. Project groups are matched with product design mentors who guide groups through the design process. Lectures cover relevant topics, including surveys of specific physical and cognitive disabilities and applicable engineering technologies. The same project may not be used to satisfy both this course and EECE 4790. May be repeated once.
Offers first- and second-year students an opportunity to pursue project and other independent inquiry opportunities under faculty supervision. The course is initiated with a student-developed proposal, including expected learning outcomes and research products, which is approved by a faculty member in the department. Requires permission of instructor.
Offers elective credit for courses taken at other academic institutions. May be repeated without limit.
Offers an opportunity to document student contributions to research projects or creative endeavors. May be repeated up to nine times.
Prerequisite(s): EECE 2322 with a minimum grade of D- ; EECE 2323 with a minimum grade of D-
Provides a basic treatment of electronic materials from atomic, molecular, and application viewpoints. Topics include atomic structure and bonding in materials, structure of materials, and crystal defects. These topics lay a foundation for the introduction of thermal and electronic conduction, which is the underlying physics of electronic devices. Finally, the electronic properties of semiconductors, dielectric, magnetic, superconducting, and optical materials are examined. The latter half deals with an introduction to the state of the art in electronic materials, including semiconductor nanoelectronics, magnetic semiconductors and spintronics, molecular electronics, carbon nanotubes, conducting polymers, diamondlike carbon, and other topics representing recent technological breakthroughs in the area of electronic materials.
Prerequisite(s): EECE 2150 with a minimum grade of D- ; (MATH 2341 with a minimum grade of D- or MATH 315M with a minimum grade of D- )
Prerequisite(s): EECE 2412 with a minimum grade of D-
Prerequisite(s): EECE 2150 with a minimum grade of D- ; (MATH 2341 with a minimum grade of D- or MATH 315M with a minimum grade of D- )
Offers elective credit for courses taken at other academic institutions. May be repeated without limit.
Prerequisite(s): CS 3000 with a minimum grade of D- or EECE 2560 with a minimum grade of D-
Prerequisite(s): EECE 3324 with a minimum grade of D- or CS 3650 with a minimum grade of D- Corequisite(s): EECE 4535
Corequisite(s): EECE 4534
Prerequisite(s): EECE 2412 with a minimum grade of D-
Prerequisite(s): EECE 2412 with a minimum grade of D-
Prerequisite(s): EECE 2160 with a minimum grade of D- ; EECE 2412 with a minimum grade of D-
Prerequisite(s): EECE 2322 with a minimum grade of D-
Prerequisite(s): BIOE 3210 with a minimum grade of D- or EECE 2150 with a minimum grade of D- or EECE 2210 with a minimum grade of D- or PHYS 1155 with a minimum grade of D-
Prerequisite(s): (MATH 1242 with a minimum grade of D- or MATH 1342 with a minimum grade of D- or MATH 211M with a minimum grade of D- ); (PHYS 1145 with a minimum grade of D- or PHYS 1151 with a minimum grade of D- or PHYS 261M with a minimum grade of D- or PHYS 1171 with a minimum grade of D- )
Prerequisite(s): (MATH 2341 with a minimum grade of D- or MATH 315M with a minimum grade of D- ); (GE 1111 with a minimum grade of D- or GE 1502 with a minimum grade of D- )
Prerequisite(s): EECE 2322 with a minimum grade of D- or EECE 2412 with a minimum grade of D- or EECE 2520 with a minimum grade of D- or EECE 2530 with a minimum grade of D- or EECE 2540 with a minimum grade of D- or EECE 2560 with a minimum grade of D- or CS 3000 with a minimum grade of D- Attribute(s): NUpath Capstone Experience, NUpath Creative Express/Innov, NUpath Writing Intensive
Prerequisite(s): EECE 2322 with a minimum grade of D- or EECE 2412 with a minimum grade of D- or EECE 2520 with a minimum grade of D- or EECE 2530 with a minimum grade of D- or EECE 2540 with a minimum grade of D- or EECE 2560 with a minimum grade of D- or CS 3000 with a minimum grade of D- Attribute(s): NUpath Capstone Experience, NUpath Creative Express/Innov, NUpath Writing Intensive
Prerequisite(s): EECE 4790 with a minimum grade of D- or EECE 4791 with a minimum grade of D- Attribute(s): NUpath Capstone Experience, NUpath Creative Express/Innov, NUpath Writing Intensive
Offers elective credit for courses taken at other academic institutions. May be repeated without limit.
Attribute(s): NUpath Integration Experience
Offers independent work under the direction of members of the department on a chosen topic. Course content depends on instructor. May be repeated without limit.
Prerequisite(s): MATH 2341 with a minimum grade of D- or MATH 315M with a minimum grade of D- or graduate program admission
Prerequisite(s): EECE 2540 with a minimum grade of D- or CS 3700 with a minimum grade of D- or graduate program admission
Prerequisite(s): ((MATH 1342 with a minimum grade of D- or MATH 211M with a minimum grade of D- ); PHYS 1155 with a minimum grade of D- ) or graduate program admission
Prerequisite(s): ((MATH 2321 with a minimum grade of D- or MATH 316M with a minimum grade of D- ); PHYS 1155 with a minimum grade of D- ; (CHEM 1151 with a minimum grade of D- or CHEM 1211 with a minimum grade of D- or CHEM 233M with a minimum grade of D- )) or graduate program admission
Prerequisite(s): EECE 2560 with a minimum grade of C- or CS 3000 with a minimum grade of C- or graduate program admission
Prerequisite(s): EECE 2540 with a minimum grade of D- or graduate program admission
Prerequisite(s): (EECE 2520 with a minimum grade of D- ; EECE 2560 with a minimum grade of D- ) or CS 3000 with a minimum grade of D- or graduate program admission
Prerequisite(s): (EECE 2160 with a minimum grade of D- ; EECE 2520 with a minimum grade of D- ) or graduate program admission
Prerequisite(s): ((MATH 3081 with a minimum grade of D- or EECE 3468 with a minimum grade of D- ); (EECE 2160 with a minimum grade of D- or EECE 2210 with a minimum grade of D- )) or graduate program admission
Prerequisite(s): EECE 3400 with a minimum grade of D- or graduate program admission
Prerequisite(s): EECE 2530 with a minimum grade of D- or EECE 3400 with a minimum grade of D- or graduate program admission
Prerequisite(s): EECE 3464 with a minimum grade of D- or EECE 2520 with a minimum grade of D- or graduate program admission
Prerequisite(s): EECE 3468 with a minimum grade of D- or graduate program admission
Prerequisite(s): EECE 2412 with a minimum grade of D- or graduate program admission
Prerequisite(s): ((MATH 2321 with a minimum grade of D- or MATH 316M with a minimum grade of D- ); (PHYS 1155 with a minimum grade of D- or PHYS 1165 with a minimum grade of D- )) or graduate program admission
Prerequisite(s): EECE 5580 with a minimum grade of C- or EECE 5580 with a minimum grade of D-
Prerequisite(s): (EECE 2520 with a minimum grade of D- ; (EECE 3468 with a minimum grade of D- or MATH 3081 with a minimum grade of D- ) or DS 5020 with a minimum grade of C- ) or graduate program admission
Prerequisite(s): (EECE 3468 with a minimum grade of D- or MATH 3081 with a minimum grade of D- or MATH 2331 with a minimum grade of D- or IE 3412 with a minimum grade of D- ) or graduate program admission
Prerequisite(s): ((EECE 3464 with a minimum grade of D- or EECE 2520 with a minimum grade of D- ); (EECE 3468 with a minimum grade of D- or MATH 3081 with a minimum grade of D- )) or graduate program admission
Introduces topics such as image formation, segmentation, feature extraction, matching, shape recovery, dynamic scene analysis, and object recognition. Computer vision brings together imaging devices, computers, and sophisticated algorithms to solve problems in industrial inspection, autonomous navigation, human-computer interfaces, medicine, image retrieval from databases, realistic computer graphics rendering, document analysis, and remote sensing. The goal of computer vision is to make useful decisions about real physical objects and scenes based on sensed images. Computer vision is an exciting but disorganized field that builds on very diverse disciplines such as image processing, statistics, pattern recognition, control theory, system identification, physics, geometry, computer graphics, and learning theory. Requires good programming experience in Matlab or C++.
Prerequisite(s): EECE 3324 with a minimum grade of D- or CS 3650 with a minimum grade of D- or graduate program admission
Prerequisite(s): ((EECE 2540 with a minimum grade of D- ; (EECE 4534 with a minimum grade of D- or EECE 3324 with a minimum grade of D- )) or (CS 3650 with a minimum grade of D- ; (CS 3700 with a minimum grade of D- or EECE 2540 with a minimum grade of D- )) or (EECE 7205 with a minimum grade of C- or EECE 7376 with a minimum grade of C- or CS 5600 with a minimum grade of C- ))
Introduces relevant topics and concepts in visualization, including computer graphics, visual data representation, physical and human vision models, numerical representation of knowledge and concept, animation techniques, pattern analysis, and computational methods. Topics include tools and techniques for practical visualization and elements of related fields, including computer graphics, human perception, computer vision, imaging science, multimedia, human-computer interaction, computational science, and information theory. Covers examples from a variety of scientific, medical, interactive multimedia, and artistic applications. Includes hands-on exercises and projects. Emphasizes modern engineering applications of computer vision, graphics, and pattern classification methodologies for data visualization.
Prerequisite(s): EECE 3326 with a minimum grade of D- or EECE 2560 with a minimum grade of D- or CS 3000 with a minimum grade of D- or graduate program admission
Prerequisite(s): EECE 3468 with a minimum grade of D- or MATH 3081 with a minimum grade of D- or MATH 1215 with a minimum grade of D- or MATH 2280 with a minimum grade of D- or IE 3412 with a minimum grade of D- or CIVE 3464 with a minimum grade of D- or BIOE 2365 with a minimum grade of D- or MGSC 2301 with a minimum grade of D- or BUSM 224M with a minimum grade of D- or graduate program admission
Prerequisite(s): ((MATH 3081 with a minimum grade of D- or EECE 3468 with a minimum grade of D- ); (EECE 2560 with a minimum grade of D- or CS 3000 with a minimum grade of D- or CS 4800 with a minimum grade of D- )) or EECE 5644 with a minimum grade of C- or DS 5220 with a minimum grade of C- or DS 5230 with a minimum grade of C-
Prerequisite(s): EECE 3440 with a minimum grade of D- or EECE 2530 with a minimum grade of D- or graduate program admission
Prerequisite(s): EECE 3410 with a minimum grade of D- or graduate program admission
Prerequisite(s): (EECE 2530 with a minimum grade of D- ; (MATH 2341 with a minimum grade of D- or MATH 315M with a minimum grade of D- )) or graduate program admission
Prerequisite(s): ((EECE 2150 with a minimum grade of D- or EECE 2210 with a minimum grade of D- or BIOE 3210 with a minimum grade of D- ); (EECE 2530 with a minimum grade of D- )) or graduate program admission
Prerequisite(s): MATH 2341 with a minimum grade of D- or MATH 315M with a minimum grade of D- or graduate program admission
Prerequisite(s): ((BIOE 3210 with a minimum grade of D- or EECE 2150 with a minimum grade of D- or EECE 2210 with a minimum grade of D- ); (EECE 4646 with a minimum grade of D- or EECE 2530 with a minimum grade of D- )) or graduate program admission
Prerequisite(s): ((BIOE 3210 with a minimum grade of C- or EECE 2150 with a minimum grade of C- or EECE 2210 with a minimum grade of C- ); EECE 2520 with a minimum grade of C- ; (MATH 2341 with a minimum grade of C- or MATH 315M with a minimum grade of C- ); (EECE 3468 with a minimum grade of C- or MATH 3081 with a minimum grade of C- )) or graduate program admission
Prerequisite(s): ((ME 4555 with a minimum grade of D- or EECE 2520 with a minimum grade of D- ); EECE 3468 with a minimum grade of D- ) or graduate program admission
Prerequisite(s): CS 6140 with a minimum grade of C- or DS 4400 with a minimum grade of D- or EECE 5644 with a minimum grade of C- or EECE 5644 with a minimum grade of D-
Examines, in this interdisciplinary course, modern energy usage, consequences, and options to support sustainable energy development from a variety of fundamental and applied perspectives. Emphasizes both (1) physical and chemical processes in materials for the conversion of energy and (2) how to design a system with renewable energy for applications such as electricity generation and transmission. Takes a systems analysis point of view. Topics include energy conservation; fossil fuels; and energy conversion methods for solar, geothermal, wind, hydro, bioenergy, electrochemical, and similar methods.
Prerequisite(s): ((EECE 3440 with a minimum grade of D- or EECE 2530 with a minimum grade of D- ); (EECE 3464 with a minimum grade of D- or EECE 2520 with a minimum grade of D- )) or graduate program admissionCorequisite(s): EECE 5681
Corequisite(s): EECE 5680
Prerequisite(s): EECE 3440 with a minimum grade of D- or EECE 2530 with a minimum grade of D- or graduate program admission
Prerequisite(s): (EECE 2412 with a minimum grade of D- ; (EECE 3464 with a minimum grade of D- or EECE 2520 with a minimum grade of D- )) or graduate program admissionCorequisite(s): EECE 5685
Corequisite(s): EECE 5684
Prerequisite(s): EECE 2150 with a minimum grade of D- or graduate program admission
Prerequisite(s): (EECE 2412 with a minimum grade of D- ; EECE 2530 with a minimum grade of D- ) or graduate program admission
Prerequisite(s): EECE 2530 with a minimum grade of D- or graduate program admission
Prerequisite(s): EECE 2530 with a minimum grade of D- or graduate program admission
Prerequisite(s): EECE 3464 with a minimum grade of D- or EECE 2520 with a minimum grade of D- or graduate program admission
Covers special topics in electrical and computer engineering. Topics are selected by the instructor and vary from semester to semester. May be repeated up to four times.
Prerequisite(s): EECE 3324 (may be taken concurrently) with a minimum grade of D- or CS 3650 (may be taken concurrently) with a minimum grade of D- or CS 5600 (may be taken concurrently) with a minimum grade of D- or graduate program admission
Delves deeply, in collaboration with a faculty member, into a specialized subject typically not covered extensively in the standard electrical and computer engineering curriculum. The topic may involve analysis, experimentation, computational methods, or a blend of these approaches. Potential outcomes include producing a comprehensive report, gathering experimental data, or designing and evaluating algorithms.
Offers elective credit for courses taken at other academic institutions. May be repeated without limit.
Introduces optics, presenting the engineering concepts necessary to understand and evaluate electro-optical systems. Begins with a brief but rigorous treatment of geometric optics, including matrix methods, aberrations, and pupils and windows, with practical examples of optical instruments and electro-optical systems. Topics include polarization; interference; diffraction; and optical properties of crystals, thin films, optical resonators, guided waves, modulators, and detectors. Presents concepts with examples from modern optical systems such as LiDAR, fiber-optical sensors, range finders, infrared systems, and optical communication systems. Requires a bachelor of science in engineering or physics.
Prerequisite(s): EECE 5554 with a minimum grade of C-
Covers fundamental algebraic concepts and algebraic structures. Topics include linear operators and their representations; matrices, algebraic equations, equivalence, and similarity transformations; introduction to the state-variable theory of continuous and discrete linear systems; standard canonical representations, the concept of state, and the representation of interconnected systems, linear spaces, the state equations, and their solution; stability; and introduction to the general control problem in terms of controllability and observability.
Covers the fundamental elements of solid-state device physics and the application of these principles. Seeks to provide students with the opportunity to develop an understanding of pn junctions, bipolar junction transistors, and MOSFETs.
Examines the fundamental equations, their physical meaning, principal mathematical techniques, and important engineering applications. Topics include sources of the electromagnetic field, Lorentz force equation, integral form of Maxwell’s equations and point relations (differential equations and boundary conditions), electromagnetic energy and power, propagation of uniform and nonuniform plane waves in homogeneous media, reflection and refraction, scalar and vector potentials, solutions in the absence of boundaries for static and dynamic problems, solutions to boundary value problems, duality, uniqueness, images, physical theory of diffraction, and general theory of metal and dielectric wave-guides and resonators for Cartesian and cylindrical systems.
Comprises the theory of functions of a complex variable. Covers Cauchy’s integral and related theorems, Taylor and Laurent series, analytic continuation, and multivalued functions. Considers special functions of mathematical physics using generating functions, Taylor and Laurent expansions, and various integral representations. Reviews applications of complex variable theory drawn from optics and electromagnetic theory and from digital signal processing and digital communications. Focuses on the theory of ordinary and partial differential equations of mathematical physics. Develops series solutions of ordinary differential equations of second order using the tools of complex variable theory. Covers Sturm-Liouville theory and uses it to develop eigen function and Green function solutions of homogeneous and inhomogeneous partial differential equations. Requires knowledge of undergraduate advanced calculus.
Covers the fundamentals of probabilistic treatment and the concept of random processes, which are essential for many engineering disciplines and data analysis in general. Includes the basic laws of probability, random variables and their functions, probability density and cumulative distributions, statistical averages, bounds on probability, and the central limit theorem. Outlines basic principles of statistics, including estimation of probability, confidence intervals, and order statistics. Provides an overview of detection and estimation problems, including maximum likelihood and Bayesian principles, Cramer-Rao bound, linear estimators, and hypothesis testing. Studies random sequences, with notions of convergence, laws of large numbers, and examples of Markov chains. Defines random processes, along with the concepts of stationarity, ergodicity, autocorrelation and power spectral density, and filtering operations.
Introduces fundamental techniques in computer engineering used throughout the graduate curriculum. Covers basic programming and analysis methods and the formulation and solution of a wide range of computer engineering problems. Also discusses the applications of algorithm analysis and complexity theory to analyzing and solving problems. Emphasizes those fundamental computational problems and related algorithms whose solution can be obtained in polynomial time. For basic computational problems such as sorting, searching, elementary graph algorithms, shortest-paths problems, as well as flow problems in networks, many different algorithms and data structures are described and analyzed, implemented, and compared both from a theoretical and from an experimental point of view.
Prerequisite(s): EECE 7200 with a minimum grade of C-
Prerequisite(s): EECE 7200 with a minimum grade of C-
Prerequisite(s): EECE 7200 with a minimum grade of C-
Prerequisite(s): EECE 5580 with a minimum grade of C- or EECE 7346 with a minimum grade of C-
Offers a self-contained introduction to optimization on smooth manifolds. Covers both theoretical foundations and practical computational methods that students can apply to their own work. Introduces the theory of Riemannian geometry. Emphasizes those elements that are relevant for the construction of optimization algorithms (tensor fields, metrics, connections, geodesics, retractions, and transporters). Applies this geometric machinery to devise first- and second-order smooth optimization methods on generic Riemannian manifolds. Focuses on the development of practical computational techniques, with applications to robotics, computer vision, and machine learning.
Offers an up-to-date account of the strategies utilized in state estimation of electric power systems. Provides a broad overview of power system operation and the role of state estimation in overall energy management. Presents an abundance of examples, models, tables, and guidelines to clearly examine new aspects of state estimation, the testing of network observability, and methods to assure computational efficiency.
Presents computer modeling of linear and nonlinear power system components to be used in transient studies. Covers methods of digital simulation of power systems operating in the steady-state and transient conditions. Discusses use of transient simulation programs for design and analysis of power systems. Students are asked to carry out a term project and deliver a presentation about its outcome.
Corequisite(s): EECE 7248
Prerequisite(s): EECE 5649 with a minimum grade of C- or EECE 7240 with a minimum grade of C-
Introduces microelectromechanical systems, including principles of sensing and actuation, microfabrication technology for MEMS, noise concepts, and packaging techniques. Covers a wide range of disciplines, from electronics to mechanics, material properties, microfabrication technology, electromagnetics, and optics. Studies several classes of devices including inertial measurement devices, pressure sensors, rf components, and optical MEMS. Devotes the last third of the semester largely to projects involving design of MEMS devices to specifications in a realistic fabrication process.
Covers planar microwave circuits and integrated circuits (MMICs) for wireless communication systems. Employs microwave CAD tools in design projects as well as in-class case-study examples. Reviews communication system basics, modulation and demodulation, architectures of receivers and transmitters, and system performance. Covers planar transmission lines and coupled lines and their application to important devices and microwave circuit functions and multiport networks using S-parameters, flow graphs, and Smith charts. Studies microwave filters, narrowband and broadband amplifiers, their gain and stability, impedance matching, and noise performance, as well as mixers and frequency-conversion techniques. Finishes with design and performance of microwave oscillators. Covers wireless standards, multiple-access techniques, and recent advances if time permits.
Prerequisite(s): EECE 7240 with a minimum grade of C- or EECE 5649 with a minimum grade of C- or EECE 5649 with a minimum grade of D-
Corequisite(s): EECE 7240
Prerequisite(s): EECE 5649 with a minimum grade of D- or EECE 5649 with a minimum grade of C- (Graduate) or EECE 7240 with a minimum grade of C-
Introduces verifiable machine learning, focusing on the limitations of current learning-based methods regarding safety and robustness. Explores adversarial robustness, uncertainty quantification, safety verification, reachability analysis, and safe/robust reinforcement learning. Examines neural network relaxations and their applications in robotics, control, image classification, medical diagnosis, and language modeling.
Prerequisite(s): EECE 7202 with a minimum grade of C-
Prerequisite(s): EECE 7202 with a minimum grade of C-
Prerequisite(s): EECE 7202 with a minimum grade of C-
Presents the formal mathematical treatment of classical crystal optics including dispersion, polarization, birefringence, metal optics, and the optics of thin films. Emphasis is on the interaction of electromagnetic waves and the crystal lattice. Classical crystal optics are extended to nonlinear effects observed with very intense electric and magnetic fields. Presents applications of nonlinear optics, such as second- and third-harmonic generation, optical mixing, optical parametric oscillation, multiple photon interaction, and linear and nonlinear scattering. Various topics in linear and nonlinear optics are applied in such areas as birefringent filters, second-harmonic generators, optical parametric oscillators, and acousto-optical beam deflectors.
Prerequisite(s): EECE 7202 with a minimum grade of C-
Offers a basic treatment of electronic materials from atomic, molecular, and application viewpoints. Topics include atomic structure and bonding in materials, structure of materials, and crystal defects. These topics lay a foundation for thermal and electronic conduction, which is the underlying physics of electronic devices. Examines the electronic properties of semiconductors, dielectric, magnetic, superconducting, and optical materials. The latter half of the course deals with an introduction to state-of-the-art electronic materials, including semiconductor nanoelectronics, magnetic semiconductors and Spintronics, molecular electronics, carbon nanotubes, conducting polymers, graphene and graphane, and other topics representing recent technological breakthroughs in the area of electronic materials.
Prerequisite(s): (EECE 5666 with a minimum grade of C- or EECE 5666 with a minimum grade of C- ); EECE 7204 with a minimum grade of C-
Focuses on generation of digital image from the source; image digitizers and display devices; image transforms; enhancement techniques, such as histogram, equalization, and edge sharpening; restoration by Wiener and Kalman filters; image coding using run-length coding; DPCM; transform coding; and feature analysis. Undergraduate course in digital signal processing highly recommended but not required.
Introduces fundamental theoretical and algorithmic concepts behind numerical optimization theory for objective functions with finite numbers of parameters. Optimization problems arise ubiquitously in all areas of engineering and science. Presents established numerical methods for iterative unconstrained and constrained optimization. Topics covered include line-search and trust-region strategies, gradient descent and Newton methods and their variations, linear and quadratic programming, penalty-augmented Lagrangian methods, sequential quadratic programming, and interior point methods. The course relies on the use of Matlab in projects. Requires a basic knowledge of calculus and linear algebra.
Prerequisite(s): EECE 5576 (may be taken concurrently) with a minimum grade of C-
Prerequisite(s): EECE 7204 (may be taken concurrently) with a minimum grade of C- or EECE 3468 with a minimum grade of C-
Prerequisite(s): EECE 7204 with a minimum grade of C-
Prerequisite(s): EECE 5644 with a minimum grade of C- or EECE 7323 with a minimum grade of C-
Prerequisite(s): EECE 7204 with a minimum grade of C-
Presents many of the issues involved in the design and analysis of new and evolving computer architectures. Topics include all aspects of the system including the microprocessor, memory, I/O, and networking. Emphasizes the connection between architecture and the underlying software that drives it. Topics include pipelining, superscalar, out-of-order execution and completion, data flow, caching, prefetching, virtual memory, RAID, and ATM switching. Performance analysis is another fundamental theme of this course. A project is assigned that involves the creation of a trace-driven simulation model to study the performance of various hardware or software architectural features. Also provides a survey of the current state of the art in processor architectures and provides additional readings from recent research in the field. Requires a working knowledge of C programming language.
Covers all aspects of VLSI design and engineering including VLSI design methodology; MOS transistors and circuits; CAD tools to create, extract, simulate, and evaluate physical layouts; CMOS fabrication process; evaluation and optimization of circuit area, power consumption, and propagation delay; CAD tools to design CMOS systems with standard cells; system clocking design and evaluation; the characteristics and limitations of CAD tools, such as simulation, placement, and routing; VLSI testing, fault models, test vector generation, and design for testability; design projects going through a complete VLSI design cycle; and a research project targeting a specific area of VLSI engineering. Requires a knowledge of electronics and digital systems design.
Analyzes the working principles and practice of current and future mobile and wireless networks. Topics include overviews of different wireless and mobile systems and applications, 5G and beyond cellular networks, current and upcoming Wi-Fi standards, and emerging networking architectures. Covers theoretical foundations to computer simulation-based exercises. Designed with a research component involving a project that allows students to match classroom concepts to real-world problems. The overall objective is to enable the student to critically evaluate current and future wireless and mobile systems through an awareness of communication and networking theory, software protocols, and architectural know-how.
Prerequisite(s): EECE 7205 with a minimum grade of C-
Offers students an opportunity to obtain practical knowledge in computer vision and to develop skills for being a successful researcher in this field. The goal of the field of computer vision is to make useful decisions about real physical objects and scenes based on sensed images. Achieving this goal requires obtaining and using descriptions (models) of the sensors and the world. Computer vision is an exciting field that builds on very diverse disciplines such as image processing, statistics, pattern recognition, control theory and system identification, physics, geometry, computer graphics, and machine learning. Course material includes state-of-the-art in the field, current research trends, and algorithms and their applications, with an emphasis on the mathematical methods used.
Corequisite(s): EECE 7364
Prerequisite(s): EECE 5644 with a minimum grade of C-
Presents an overview of modern communication networks using the internet as a primary case study. Uses the concept of layered network architecture as a framework for understanding the principal functions and services required for achieving reliable end-to-end communications. Topics include networking application design and network programming (socket programming), service interfaces and peer-to-peer protocols, the reference model for TCP/IP (internet), transport layer and network layer issues, data link layer and LANs (local area networks) architectures, and important emerging technologies, including software-defined networking (SDN). Covers the basics of wireless and mobile networking (principles and practice) and standardization and policy issues concerning communications and networks.
Prerequisite(s): CS 3000 with a minimum grade of C- or EECE 2560 with a minimum grade of C- or EECE 7205 with a minimum grade of C-
Covers computer hardware and embedded system security and trust, a major concern for national security. Topics include crypto engineering, side-channel attacks, hardware security primitives, counterfeit electronics detection and prevention, logic locking and obfuscation, hardware Trojan detection and isolation, passive and active metering for the prevention of piracy, FPGA security, and artificial intelligence security from a hardware perspective. Reviews the foundations of the new and evolving area of hardware security and trust, as well as the state-of-the-art on trusted and assured microelectronics and system-on-chip design. Discusses current frontier papers to motivate research interests and ideas in building secure and trustworthy computer hardware systems.
Prerequisite(s): CS 6140 with a minimum grade of C- or EECE 7204 with a minimum grade of C- or EECE 7313 with a minimum grade of C- or EECE 5644 with a minimum grade of C-
Covers topics of interest to the faculty member conducting this class for advanced study. May be repeated up to four times.
Provides instruction and experience in effective communication of technical material to broad audiences. Centers on the fundamental question of "So What-Who Cares?" (SWWC), which guides all choices about what to present and how to present it. The SWWC approach uses a 3-level method applied through a learn-by-doing format, covering presentations in multiple formats, responses to critique, seminar analysis, and professional development including CV preparation and interview practice.
Offers advanced theoretical or experimental work under individual faculty supervision.
Offers students an opportunity to develop and present a plan for the demonstration of a marketable technology product or prototype with an electrical engineering focus. Constitutes the first half of a thesis-scale project in technology commercialization. Requires work/training with a sponsoring organization or employer to improve a process or develop a project that is of significant value to the organization and demonstrates a quantifiable market impact, while enhancing the student’s technological and engineering depth and fostering the student’s leadership development.
Prerequisite(s): EECE 7440 with a minimum grade of C-
Offers analytical and/or experimental work leading to a written report and a final short presentation by the end of the semester.
Offers elective credit for courses taken at other academic institutions. May be repeated without limit.
Prerequisite(s): EECE 7945 with a minimum grade of C-
Offers analytical and/or experimental work conducted under the auspices of the department.
Indicates successful completion of program requirements for PhD candidacy.
Offers students an opportunity to conduct full-time research under faculty supervision. May be repeated up to 4 times.
Prerequisite(s): EECE 9000 with a minimum grade of S
Prerequisite(s): EECE 9990 with a minimum grade of S
Prerequisite(s): EECE 9991 with a minimum grade of S or Dissertation Check with a score of REQ
Source: Northeastern University's catalog, linked per course · table learning_unit · CourseShelf publish 61
