M.Eng Coursework and Focus Areas

Focus Areas

Focus areas and courses within each area are listed below. These courses have been historically offered but are not available every term. Please check the campus Course Catalog for a list of courses offered in the current term.

• Microelectronics, Photonics, and Nanotechnology
• Integrated Circuits and Systems
• Power and Energy Systems
• Biomedical Imaging, Bioengineering and Acoustics
• Electromagnetics, Optics, Remote Sensing
• Signal Processing, Communications, Control Systems
• Computing Systems, Networks, Software, and Algorithms
• Computational Science

• ECE 441, Physics and Modeling of Semiconductor Devices
  Advanced concepts including generation-recombination, hot electron effects, and breakdown mechanisms; essential features of small ac characteristics, switching and transient behavior of p-n junctions, and bipolar and MOS transistors; fundamental issues for device modeling; perspective and limitations of Si-devices.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 340.
• ECE 442, Silicon Photonics
  Overview of silicon integrated photonics in three sections: (1) fundamentals of waveguide optics and passive silicon photonic devices including wavelength filters, mode converters, polarization and dispersion management. (2) active silicon photonic devices based on carrier injection/depletion pn junction, photonic modulators, optical switches, photodetectors. (3) application of integrated silicon photonics in optical communications systems in short and long haul optical links and datacenters. Emerging applications in quantum computing, neuromorphic computing and biosensing.
  • 3 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 350.
• ECE 444, IC Device Theory & Fabrication
  Fabrication lab emphasizing physical theory and design of devices suitable for integrated circuitry; electrical properties of semiconductors and techniques (epitaxial growth, oxidation, photolithography diffusion, ion implantation, metallization, and characterization) for fabricating integrated circuit devices such as p-n junction diodes, bipolar transistors, and field effect transistors.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 340.
• ECE 455 Optical Electronics
  Optical beams and cavities; semiclassical theory of gain; characteristics of typical lasers (gas, solid state, and semiconductor); application of optical devices.
  • 3 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 350 or PHYS 436.
• ECE 481, Nanotechnology
  Fundamental physical properties of nanoscale systems. Nanofabrication techniques, semiconductor nanotechnology, molecular and biomolecular nanotechnology, carbon nanotechnology (nanotubes and graphene), nanowires, and nanoscale architectures and systems.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: One of CHEM 442, CHBE 457, ME 485, MSE 401, PHYS 460.
• ECE 485, MEMS Devices and Systems
  Introduction to principles, fabrication techniques, and applications of microelectromechanical systems (MEMS). In-depth analysis of sensors, actuator principles, and integrated microfabrication techniques for MEMS. Comprehensive investigation of state-of-the-art MEMS devices and systems.
  • Same as ME 485.
  • 3 undergraduate hours. 3 graduate hours.
• ECE 487, Introduction to Quantum Electronics
  Application of quantum mechanical concepts to electronics problems; detailed analysis of a calculable two-state laser system; incidental quantum ideas bearing on electronics.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: PHYS 485.
• ECE 488, Compound Semiconductors and Devices
  Advanced semiconductor materials and devices; elementary band theory; heterostructures; transport issues; three-terminal devices; two-terminal devices; including lasers and light modulators.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 340 and ECE 350.
• ECE 495, Photonic Device Laboratory
  Active photonic devices and lightwave technology. Hands-on experience with several classes of lasers (HeNe laser, semiconductor edge emitting lasers, vertical cavity surface emitting lasers), photodetectors, and photonic systems. Familiarization with experimental optical characterization techniques and equipment.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 487 recommended.
• ECE 518, Advanced Semiconductor Nanotechnology
  Semiconductor nanotechnology from the formation and characterization of low-dimensional structures to device applications. Compound semiconductors, epitaxial growth, quantum dots, nanowires, membranes, strain effect, quantum confinement, surface states, 3D transistors, nanolasers, multijunction tandem solar cells, and nanowire thermoelectrics. Handouts are supplemented with papers from the research literature. Critical literature review assignments, research proposals in National Science Foundation format, and oral presentations are required.
  • 4 graduate hours.
  • Prerequisites: ECE 340, ECE 444, and ECE 481.
• ECE 523, Gaseous Electronics and Plasmas
  This course will help students to develop an advanced theoretical understanding of Low-Temperature Plasma (LTP) processing systems, with an emphasis on system design. Whereas prerequisite coursework focused on developing a framework for the analysis of LTP systems, in this course students will build upon that foundation to develop more advanced theoretical models for LTP dynamics, including electron collisions, plasma transport, sheath dynamics, and plasma and surface chemistry. Students will be able to apply this advanced LTP theory for the design of systems for etching, advanced deposition, and others important in modern materials processing applications.
  • 4 graduate hours.
  • No professional credit.
  • Prerequisite: ECE 452 or PHYS 485 or NPRE 429.
• ECE 529, Light-Matter Interactions
  Light-matter interaction is explored using a primarily classical approach. This course examines optical properties, including refraction, dispersion, and absorption, in gases, liquids, and solids, emphasizing metals and dielectrics. Topics include dispersion relations, optical activity, Faraday rotation, and the influence of quantum mechanics on optical properties. Nonlinear contributions to polarization, which result in new frequencies and irradiance-dependent properties, are discussed. The course also addresses light's interactions with artificial photonic materials, specifically metamaterials and metasurfaces. 
  
  • 4 graduate hours.
  • No professional credit.
  • Prerequisite: ECE 350, one of ECE 460 or PHYS 402
• ECE 532, Compound Semiconductors and Diode Lasers
  Compound semiconductor materials and their optical properties. Diode lasers including quantum well heterostructure lasers, strained layer lasers, and quantum wire and quantum dot lasers. Current topics in diode laser development.
  • 4 graduate hours.
  • Prerequisite: ECE 340 and PHYS 486.
  • Recommended: ECE 455; credit or concurrent registration in ECE 536.
• ECE 535, Theory of Semiconductors and Semiconductor Devices
  Introductory quantum mechanics of semiconductors; energy bands; dynamics of Block electrons in static and high-frequency electric and magnetic fields; equilibrium statistics; transport theory, diffusion, drift, and thermoelectric effects; characteristics of p-n junctions, heterojunctions, and transistor devices.
  • 4 graduate hours.
  • Same as PHYS 565.
  • Prerequisite: Senior-level course in quantum mechanics or atomic physics.
• ECE 536, Integrated Optics and Optoelectronics
  Integrated optical and optoelectronic devices; theory of optical devices including laser sources, waveguides, photodetectors, and modulations of these devices.
  • 4 graduate hours.
  • Prerequisite: One of ECE 455, ECE 487, PHYS 486.
  • Recommended: ECE 488.
• ECE 538, 2D Material Electronics and Photonics
  Explores the electronic and photonic devices based on two-dimensional (2D) materials. More specifically, this course will discuss the synthesis and characterization of a variety of 2D materials. This course will also introduce the design, fabrication and physics of various nanoscale devices, including logic transistors, radio frequency devices, tunneling devices, photodetectors, plasmonic devices, lasers and valleytronic devices. The lab sessions will provide the students hands-on experience on the fabrication and characterization of 2D electronic/photonic devices. The lab sessions will be carried out in the nanofabrication laboratory in ECEB.
  • 4 graduate hours.
  • No professional credit.
  • Prerequisite: ECE 340 or equivalent
• ECE 539, Advanced Theory of Semiconductors & Devices
  Advanced topics of current interest in the physics of semiconductors and solid-state devices.
  • 4 graduate hours.
  • Prerequisite: ECE 535.
• ECE 572, Quantum Optoelectronics
  Theoretical approach to quantum mechanics and atomic physics, with many applications in spin resonance and modern maser theory.
  • 4 graduate hours.
  • Recommended: PHYS 485
• ECE 574, Nanophotonics
  Nanoscale interaction between light and semiconductors, metals, or composites; plasmonics, cavity electrodynamics, polarition cavity condensation, sub-wavelength structures, metamaterials, and applications.
  • 4 graduate hours.
  • Prerequisite: ECE 455 or ECE 572; ECE 487 or PHYS 486.

Integrated Circuits and Systems

• ECE 425, Introduction to VLSI System Design
  Complementary Metal-Oxide Semiconductor (CMOS) technology and theory; CMOS circuit and logic design; layout rules and techniques; circuit characterization and performance estimation; CMOS subsystem design; Very-Large-Scale Integrated (VLSI) systems design methods; VLSI Computer Aided Design (CAD) tools; workstation-based custom VLSI chip design using concepts of cell hierarchy; final project involving specification, design, and evaluation of a VLSI chip or VLSI CAD program; written report and oral presentation on the final project.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 385 or CS 233.
• ECE 482, Digital IC Design (3 hours)
  Bipolar and MOS field effect transistor characteristics; VLSI fabrication techniques for MOS and bipolar circuits; calculation of circuit parameters from the process parameters; design of VLSI circuits such as logic, memories, charge-coupled devices, and A/D and D/A converters.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 342.
• ECE 483, Analog IC Design
  Basic linear integrated circuit design techniques using bi-polar, JFET, and MOS technologies; operational amplifiers; wide-band feedback amplifiers; sinusoidal and relaxation oscillators; electric circuit noise; application of linear integrated circuits.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite:& ECE 342.
• ECE 527, System-On-Chip Design
  System-on-chip (SOC) design methodology and IP (intellectual property) reuse, system modeling and analysis, hardware/software co-design, behavioral synthesis, embedded software, reconfigurable computing, design verification and test, and design space exploration. Class projects focusing on current SOC design and research. Platform FPGA boards and digital cameras are provided to prototype, test, and evaluate SOC designs.
  • 4 graduate hours.
  • Prerequisite: ECE 391 and ECE 425.
• ECE 552, Numerical Circuit Analysis
  Formulation of circuit equations; sparse matrix algorithms for the solution of large systems, AC, DC, and transient analysis of electrical circuits; sensitivity analysis; decomposition methods.
  • 4 graduate hours.
  • Same as CSE 532.
  • Prerequisite: MATH 415 and ECE 210.
• ECE 560, VLSI in Signal Processing and Communications
  Basic concepts in digital signal processing, VLSI design methodologies, VLSI DSP building blocks; algorithm transformation and mapping techniques, high-speed, low-power transforms, applications to digital filtering; basics of finite-field arithmetic, forward-error correction algorithms, and architectures; DSP implementation platforms, programmable DSPs, media processors, FPGAs, ASICs, case studies of multimedia communications systems, video codecs, xDSL, and cable modems. Homework and a term project apply these concepts in the design of VLSI architectures for digital signal processing and communication systems.
  • 4 graduate hours.
  • Prerequisite: ECE 310.
• ECE 581, Advanced Analog IC Design
  Advanced topics in modern analog IC design. Emphasis on CMOS building blocks and circuit techniques as a result of fabrication technology advancement. Noise in linear analog circuits; linear feedback theory and stability; harmonic distortion in weakly nonlinear circuits; switched-capacitor circuit technique and realization; Nyquist-rate and oversampled data converters. Extensive computer simulations required in both homework and final project.
  • 4 graduate hours.
  • Prerequisite: ECE 310 and ECE 483.
• ECE 582, Physical VLSI Design
  Basic physical design requirements for VLSI; performance-oriented formulation and optimization of chip partitioning, module placement and interconnection; optimized design and layout of on-chip modules; circuit extraction; high-speed VLSI circuits; yield and reliability analysis; advanced VLSI packaging and parametric testing.
  • 4 graduate hours.
  • Prerequisite: ECE 425 or ECE 482.
• ECE 585, MOS Device Modeling & Design
  Techniques for characterizing gate oxide and interface properties and reliability, I-V models for circuit simulation, design for control of short channel effects, silicon-on-insulator, and new device structures.
  • 4 graduate hours.
  • Prerequisite: ECE 441.

Power and Energy Systems

• ECE 431, Electric Machinery
  Theory and laboratory experimentation with three-phase power, power-factor correction, single- and three-phase transformers, induction machines, DC machines, and synchronous machines; project work on energy control systems; digital simulation of machine dynamics.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 330.
• ECE 464, Power Electronics
  Switching functions and methods of control such as pulse-width modulation, phase control, and phase modulation; dc-dc, ac-dc, dc-ac, and ac-ac power converters; power components, including magnetic components and power semiconductor switching devices.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 342.
• ECE 469, Power Electronics Laboratory
  Circuits and devices used for switching power converters, solid-state motor drives, and power controllers; dc-dc, ac-dc, and dc-ac converters and applications; high-power transistors and magnetic components; design considerations including heat transfer.
  • 2 undergraduate hours.
  • 2 graduate hours.
  • Prerequisite: ECE 343; credit or concurrent registration in ECE 464.
• ECE 476, Power System Analysis
  Development of power system equivalents by phase network analysis, load flow, symmetrical components, sequence networks, fault analysis, and digital simulation.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 330.
• ECE 530, Analysis Techniques for Large-Scale Electrical Systems
  Fundamental techniques for the analysis of large-scale electrical systems, including methods for nonlinear and switched systems. Emphasis on the importance of the structural characteristics of such systems. Key aspects of static and dynamic analysis methods.
  • 4 graduate hours.
  • Prerequisite: ECE 464 and ECE 476.
• ECE 568, Modeling and Control of Electromechanical Systems
  Fundamental electrical and mechanical laws for derivation of machine models; simplifying transformations of variables in electrical machines; power electronics for motor control; time-scale separation; feedback linearization and nonlinear control as applied to electrical machines. Typical electromechanical applications in actuators, robotics, and variable speed drives.
  • Prerequisite: ECE 431 and ECE 515.
• ECE 573, Power Systems Operations and Control
  Energy control center functions, state estimation and steady state security assessment techniques, economic dispatch, optimal power flow, automatic generation control, and dynamic equivalents.
  • 4 graduate hours.
  • Prerequisite: ECE 476; credit or concurrent registration in ECE 530.
• ECE 576, Power System Dynamics and Stability
  Detailed modeling of the synchronous machine and its controls, such as excitation system and turbine-governor dynamics; time-scales and reduced order models; non-linear and linear multi-machine models; stability analysis using energy functions; power system stabilizers.
  • 4 graduate hours.
  • Prerequisite: ECE 476; credit or concurrent registration in ECE 530.
• ECE 588, Electricity Resource Planning
  Techniques in electricity resource planning including methodologies for reliability evaluation and assessment, production costing, marginal costing, supply-side and demand-side planning, integrated planning, and planning under competition.
  • 4 graduate hours.
  • Prerequisite: MATH 415, ECE 313, and ECE 476.

Biomedical Imaging, Bioengineering and Acoustics

• ECE 402, Electronic Music Synthesis
  Historical survey of electronic and computer music technology; parameters of musical expression and their codification; analysis and synthesis of fixed sound spectra; time-variant spectrum analysis/synthesis of musical sounds; algorithms for dynamic sound synthesis.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 310.
• ECE 403, Audio Engineering
  Resonance and wave phenomena; Acoustics of rooms and transmission lines (e.g., horns); How loudspeakers work: A lab component has been added to measure and model real loudspeakers and enclosures; Topics in digital audio, including AD and DA (Sigma-Delta) audio converters.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 210 and ECE 310.
• ECE 410, Neural Circuits and Systems
  Basic computer organization and design: integer and floating-point computer arithmetic; control unit design; pipelining; system interconnect; memory organization; I/O design; reliability and performance evaluation. Laboratory for computer design implementation, simulation, and layout.
  • Same as NE 410.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 391, CS 241 or CS 341.
• ECE 414, Biomedical Instrumentation
  Engineering aspects of the detection, acquisition, processing, and display of signals from living systems; biomedical sensors for measurements of biopotentials, ions and gases in aqueous solution, force, displacement, blood pressure, blood flow, heart sounds, respiration, and temperature; therapeutic and prosthetic devices; medical imaging instrumentation.
  • Same as ECE 414.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: BIOE 205, ECE 205 or ECE 210.
• ECE 416, Biosensors
  Underlying engineering principles used to detect small molecules, DNA, proteins, and cells in the context of applications in diagnostic testing, pharmaceutical research, and environmental monitoring. Biosensor approaches including electrochemistry, fluorescence, acoustics, and optics; aspects of selective surface chemistry including methods for biomolecule attachment to transducer surfaces; characterization of bisensor performance; blood glucose detection; fluorescent DNA microarrays; label-free biochips; bead-based assay methods. Case studies and analysis of commercial biosensor.
  • Same as BIOE 416
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 329.
• ECE 421, Neural Interface Engineering
  This course will focus on hardware and software technologies that enable control and readout of neural activity in the brain. Engineering grounded innovation will accelerate our understanding of the brain, impact new therapies for restoring lost neural functions, and lead to neural interfaces to augment our interaction with the world and machines. Focuses on using physical, chemical and biological principles to understand technology design criteria governing ability to observe and alter brain structure and function. Topics include noninvasive and invasive brain mapping and stimulation, neural interfaces and neural prosthetics, data processing problems, decoding/encoding techniques based on machine learning, future brain interfaces based on nanotechnology, optogenetics.
  • Same as NE 420.
  • 3 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 210 or BIOE 205 and NE 330, or instructor approval.
• ECE 437, Sensors and Instrumentation
  Hands-on exposure to fundamental technology and practical application of sensors. Capacitive, inductive, optical, electromagnetic, and other sensing methods are examined. Instrumentation techniques incorporating computer control, sampling, and data collection and analysis are reviewed in the context of real-world scenarios.
  • 3 undergraduate hours.
  • 3 graduate hours. Prerequisite: ECE 329.
• ECE 467, Biophotonics
  Overview of the field of biophotonics, in three segments: (1) fundamental principles of light, optics, lasers, biology, and medicine; (2) diagnostic biophotonics including imaging, spectroscopy, and optical biosensors; (3) therapeutic applications of biophotonics including laser ablation and photodynamic therapies. Reviews and presentations of current scientific literature by students. Tours of microscopy facilities.
  • Same as BIOE 467.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: One of ECE 455, ECE 460, PHYS 402.
• ECE 472, Biomedical Ultrasound Imaging
  Theoretical and engineering foundations of ultrasonic imaging for medical diagnostics. Conventional, Doppler, and advanced ultrasonic imaging techniques; medical applications of different ultrasonic imaging techniques; engineering problems related to characterization of ultrasonic sources and arrays, image production, image quality, the role of contrast agents in ultrasonic imaging, and system design.
  • Same as BIOE 427.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 329.
• ECE 473, Fundamentals of Engineering Acoustics
  Development of the basic theoretical concepts of acoustical systems; mechanical vibration, plane and spherical wave phenomena in fluid media, lumped and distributed resonant systems, and absorption phenomena and hearing.
  • Same as TAM 413.
  • 3 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: MATH 285 or MATH 286.
• ECE 480, Magnetic Resonance Imaging
  Fundamental physical, mathematical, and computational principles governing the data acquisition and image reconstruction of magnetic resonance imaging.
  • Same as BIOE 480.
  • 3 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: Recommended: ECE 310.
• ECE 537, Speech Processing Fundamentals
  Development of an intuitive understanding of speech processing by the auditory system, in three parts. I): The theory of acoustics of speech production, introductory acoustic phonetics, inhomogeneous transmission line theory (and reflectance), room acoustics, the short-time Fourier Transform (and its inverse), and signal processing of speech (LPC, CELP, VQ). II): Psychoacoustics of speech perception, critical bands, masking (JNDs), and the physiology of the auditory pathway (cochlear modeling). III): Information theory entropy, channel capacity, the confusion matrix, state models, EM algorithms, and Bayesian networks. Presentation of classic papers on speech processing and speech perception by student groups. MATLAB (or equivalent) programming in majority of assignments.
  • 4 graduate hours.
  • Prerequisite: ECE 310.
• ECE 545, Advanced Physical Acoustics
  Advanced topics in acoustics including physical properties of a fluid; linear propagation phenomena; nonlinear phenomena such as radiation force, streaming, and harmonic generation; cavitation; absorption and dispersion.
  • 4 graduate hours.
  • Prerequisite: One of ECE 473, ECE 520, TAM 518.
• ECE 564, Modern Light Microscopy
  Current research topics in modern light microscopy: optics principles (statistical optics, Gaussian optics, elastic light scattering, dynamic light scattering); traditional microscopy (bright field, dark field, DIC, phase contract, confocal, epi-fluorescence, confocal fluorescence); current research topics (multiphoton, CARS, STED, FRET, FIONA, STORM, PALM, quantitative phase).
  • 4 graduate hours.
  • Prerequisite: One of ECE 460, MSE 405, PHYS 402.
• ECE 594, Mathematical Models of Language
  Mathematical models of linguistic structure and their implementation in computational algorithms used in automatic speech understanding and speech synthesis. Statistical and automata-theoretic techniques are studied allowing a quantitative description of acoustic-phonetics, phonology, phonotactics, lexicons, syntax, and semantics. The methods are used to build components of a speech understanding system.
  • For 4 graduate hours credit, an extended project is required.
  • Prerequisite: ECE 537.

Electromagnetics, Optics, Remote Sensing

• ECE 443, LEDs and Solar Cells
  This course explores the energy conversion devices from fundamentals to system-levels including electronic structure of semiconductors; quantum physics; compound semiconductors; semiconductor heterostructures and low dimensional quantum structures; energy transfer between photons and electron-hole pairs; photon emission and capture processes; radiative and non-radiative processes; light extraction and trapping; emission and absorption engineering; electrical and optical modelling via numerical and TCAD simulation tools; hands-on characterization of modern light emitting diodes and solar cells.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 340.
• ECE 447, Active Microwave Circuit Design
  Microwave circuit design of amplifiers, oscillators, and mixers.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 350 and ECE 453.
• ECE 451, Advanced Microwave Measurements
  Manual- and computer-controlled laboratory analysis of circuits at microwave frequencies.
  • 3 undergraduate hours.
  • 3 graduate hours. Prerequisite: ECE 350.
• ECE 452, Electromagnetic Fields
  Plane waves at oblique incidence; wave polarization; anisotropic media; radiation; space communications; waveguides.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 350.
• ECE 453, Wireless Communication Systems
  Design of a radio system for transmission of information; modulation, receivers, impedance matching, oscillators, two-port network analysis, receiver and antenna noise, nonlinear effects, mixers, phase-locked loops.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 329, credit or concurrent registration in ECE 342.
• ECE 454, Antennas
  Antenna parameters; polarization of electromagnetic waves; basic antenna types; antenna arrays; broadband antenna design; antenna measurements.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 350.
• ECE 456, Global Nav Satellite Systems
  Engineering aspects of space-based navigation systems, such as the Global Positioning System (GPS). Engineering and physical principles on which GPS operates, including orbital dynamics, electromagnetic wave propagation in a plasma, signal encoding, receiver design, error analysis, and numerical methods for obtaining a navigation solution. GPS as a case study for performing an end-to-end analysis of a complex engineering system. Laboratory exercises focus on understanding receiver design and developing a MATLAB-based GPS receiver.
  • Same as AE 456.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 329 and ECE 310 or AE 352 and AE 353.
• ECE 457, Microwave Devices & Circuits
  Electromagnetic wave propagation, microwave transmission systems, passive components, microwave tubes, solid state microwave devices, microwave integrated circuits, S-parameter analysis, and microstrip transmission lines.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 340 and ECE 350.
• ECE 458, Applications of Radio Wave Propagation
  Terrestrial atmosphere, radio wave propagation, and applications to radio sensing and radio communication.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 350.
• ECE 459, Communication Systems
  Analog underpinning of analog and digital communication systems: representation of signals and systems in the time and frequency domains; analog modulation schemes; random processes; prediction and noise analysis using random processes; noise sensitivity and bandwidth requirements of modulation schemes. Brief introduction to digital communications.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 313.
• ECE 460, Optical Imaging
  Scalar fields, geometrical optics, wave optics, Gaussian beams, Fourier optics, spatial and temporal coherence, microscopy, interference chromatic and geometric aberrations, Jones matrices, waveplates, electromagnetic fields, and electro-optic and acousto-optic effects. Laboratory covers numerical signal processing, spectroscopy, ray optics, diffraction, Fourier optics, microscopy, spatial coherence, temporal coherence, polarimetry, fiber optics, electro-optic modulation and acousto-optic modulation.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 329; credit or concurrent registration in ECE 313.
• ECE 465, Optical Communication Systems
  Fundamentals of lightwave systems: characterization of lightwave channels, optical transmitters, receivers, and amplifiers; quantum and thermal noise processes; design of optical receivers; multimode and single-mode link analysis.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 313 and ECE 350.
  • Recommended: credit or concurrent registration in ECE 459 nd ECE& 466.
• ECE 466, Optical Communications Lab
  Fiber components and measurements, transmitters and detectors, fiber amplifiers, multimode fiber links, and wavelength division multiplexing.
  • 1 undergraduate hour. 1 graduate hour.
  • Prerequisite: Credit or concurrent registration in ECE 465.
• ECE 468, Optical Remote Sensing
  Optical sensors including single element and area arrays (CCDs); optical systems including imagers, spectrometers, interferometers, and lidar; optical principles and light gathering power; electromagnetics of atomic and molecular emission and scattering with applications to the atmosphere the prime example; applications to ground and spacecraft platforms. Four laboratory sessions (4.5 hours each) arranged during term in lieu of four lectures.
  • Same as AE 468.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 329, ECE 313.
• ECE 520, Electromagnetic Waves and Radiating Systems
  Fundamental electromagnetic theory with applications to plane waves, waveguides, cavities, antennas, and scattering; electromagnetic principles and theorems; and solution of electromagnetic boundary-value problems.
  
  • 4 graduate hours.
• ECE 531, Theory of Guided Waves
  Propagation of electromagnetic waves in general cylindrical waveguides; stationary principles; non-uniform inhomogeneously filled waveguides; mode and power orthogonality; losses in waveguides; analytical and numerical techniques; microwave integrated circuits waveguides; optical waveguides.
  • 4 graduate hours.
  • Prerequisite: ECE 520.
  • Recommended: MATH 556.
• ECE 540, Computational Electromagnetics
  Basic computational techniques for numerical analysis of electromagnetics problems, including the finite difference, finite element, and moment methods. Emphasis on the formulation of physical problems into mathematical boundary-value problems, numerical discretization of continuous problems into discrete problems, and development of rudimentary computer codes for simulation of electromagnetic fields in engineering problems using each of these techniques.
  • Same as CSE 530.
  • 4 graduate hours.
  • Prerequisite: CS 357; credit or concurrent registration in ECE 520.
• ECE 546, Advanced Signal Integrity
  Signal integrity aspects involved in the design of high-speed computers and high-frequency circuits; addressing the functions of limitations of interconnects for system-level integration. Topics explored include packaging structures, power and signal distribution, power level fluctuations, skin effect, parasitics, noise, packaging hierarch, multilayer wiring structures as well as the modeling and simulation of interconnects through the use of computer-aided design (CAD) and computational electromagnetics.
  • 4 graduate hours.
  • Prerequisite: ECE 520.
• ECE 569, Inverse Problems in Optics
  Physical optics, solution of linear inverse problems, and computed imaging. Forward problems in diffraction, asymptotics, ray propagation, x-ray projections, scattering, sources, optical coherence tomography, and near-field optics. Solution of associated inverse problems including back-propagation, back-projection, Radon transforms (x-ray CT), inverse scattering, source localization, interferometric synthetic aperture microscopy, and near-field tomography. Special topics as time permits.
  • 4 graduate hours.
  • Prerequisite: ECE 460.
• ECE 570, Nonlinear Optics
  Light propagation in anisotropic crystals; second- and third-order nonlinear susceptibility and electro-optic effect; discussion of the relationship of these effects along with such applications as light modulation, harmonic generation, and optical parametric amplification and oscillation.
  • 4 graduate hours.
  • Prerequisite: ECE 520.
• ECE 571, Electromagnetic Waves in Inhomogeneous Media
  Electromagnetic waves in layered media; plane wave expansion of electromagnetic point source field; Sommerfeld integrals; transient response; WKB method with asymptotic matching; scattering by junction discontinuity; surface integral equation; volume integral equation; inverse problems.
  • 4 graduate hours.
  • Prerequisite: MATH 446; ECE 520 or PHYS 505.
• ECE 577, Advanced Antenna Theory
  Selected topics from recent engineering literature on antennas supplemented by advanced topics in electromagnetic theory needed for comprehension; current techniques for analysis of wire, slot, horn, frequency independent, quasi-optical, and array antennas.
  • 4 graduate hours.
  • Prerequisite: ECE 520.
• ECE 579, Computational Complexity
  Turing machines; determinism and non-determinism; time and space hierarchy theorems; speed-up and tape compression; Blum axioms; structure of complexity classes NP, P, NL, L, and PSPACE; complete problems; randomness and complexity classes RP, RL, and BPP; alternation, polynomial-time hierarchy; circuit complexity, parallel complexity, NC, and RNC; relativized computational complexity; time-space trade-offs.
  • Same as CS 579.
  • 4 graduate hours. No professional credit.
  • Prerequisite: One of CS 473, CSE 414, MATH 473, CS 475 or MATH 475.

Signal Processing, Communications, Control Systems

• ECE 401, Signal and Image Analysis
  Introduction to signal processing for advanced undergraduates or graduate students in the biological, physical, social, engineering and computer sciences. Representation and processing of continuous-time and discrete-time signals and images using phasors, Fourier series, sampling, FIR filters, discrete-time Fourier transform, Z transform, and IIR filters. Machine problems include processing of music, speech, photographic image, bioelectric, and biomedical image data.
  • 4 undergraduate hours. 4 graduate hours.
  • Credit is not given towards graduation for both ECE 310 and ECE 401.
  • Prerequisite: MATH 220.
• ECE 417, Multimedia Signal Processing
  Characteristics of speech and image signals; important analysis and synthesis tools for multimedia signal processing including subspace methods, Bayesian networks, hidden Markov models, and factor graphs; applications to biometrics (person identification), human-computer interaction (face and gesture recognition and synthesis), and audio-visual databases (indexing and retrieval). Emphasis on a set of MATLAB machine problems providing hands-on experience.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 310 or ECE 401; one of ECE 313, CS361, or STAT 400.
• ECE 418, Introduction to Image and Video Signal Processing
  Concepts and applications in image and video processing; introduction to multidimensional signal processing: sampling, Fourier transform, filtering, interpolation, and decimation; human visual perception; scanning and display of images and video; image enhancement, restoration and segmentation; digital image and video compression; image analysis. Laboratory exercises promote experience with topics and development of C and MATLAB programs.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 310; credit or concurrent registration in one of ECE 313, STAT 400, IE 300, MATH 461; MATH 415; experience with C programming language.
• ECE 420, Embedded DSP Laboratory
  Development of real-time digital signal processing (DSP) systems using a DSP microprocessor; several structured laboratory exercises, such as sampling and digital filtering; followed by an extensive DSP project of the student's choice.
  • 2 undergraduate hours.
  • 2 graduate hours. Prerequisite: ECE 310.
• ECE 459, Communications Systems
  Analog underpinning of analog and digital communication systems: representation of signals and systems in the time and frequency domains; analog modulation schemes; random processes; prediction and noise analysis using random processes; noise sensitivity and bandwidth requirements of modulation schemes. Brief introduction to digital communications.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 313.
• ECE 461, Digital Communications
  Reliable communication of one bit of information over three types of channels: additive Gaussian noise, wireline, and wireless. Emphasis on the impact of bandwidth and power on the data rate and reliability, using discrete-time models. Technological examples used as case studies.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 210 and ECE 313.
• ECE 463, Digital Communications Laboratory
  Hands-on experience in the configuration and performance evaluation of digital communication systems employing both radio and optical signals.
  • 2 undergraduate hours. 2 graduate hours.
  • Prerequisite: ECE 361 or ECE 459.
• ECE 486, Control Systems
  Analysis and design of control systems with emphasis on modeling, state variable representation, computer solutions, modern design principles, and laboratory techniques.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 210.
• ECE 490, Introduction to Optimization
  Basic theory and methods for the solution of optimization problems; iterative techniques for unconstrained minimization; linear and nonlinear programming with engineering applications.
  • Same as CSE 441.
  • 3 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 220 and MATH 415.
• ECE 513, Vector Space Signal Processing
  Mathematical tools in a vector space framework, including: finite and infinite dimensional vector spaces, Hilbert spaces, orthogonal projections, subspace techniques, least-squares methods, matrix decomposition, conditioning and regularizations, bases and frames, the Hilbert space of random variables, random processes, iterative methods; applications in signal processing, including inverse problems, filter design, sampling, interpolation, sensor array processing, and signal and spectral estimation.
  • 4 graduate hours.
  • Prerequisite: ECE 310, ECE 313, and MATH 415.
• ECE 515, Control System Theory & Design
  Feedback control systems emphasizing state space techniques. Basic principles, modeling, analysis, stability, structural properties, optimization, and design to meet specifications.
  • Same as ME 540.
  • 4 graduate hours.
  • Prerequisite: ECE 486.
• ECE 517, Nonlinear & Adaptive Control
  Design of nonlinear control systems based on stability considerations; Lyapunov and hyperstability approaches to analysis and design of model reference adaptive systems; identifiers, observers, and controllers for unknown plants.
  • 4 graduate hours.
  • Prerequisite: ECE 515.
• ECE 528, Analysis of Nonlinear Systems
  Nonlinear dynamics, vector fields and flows, Lyapunov stability theory, regular and singular perturbations, averaging, integral manifolds, input-output and input-to-state stability, and various design applications in control systems and robotics.
  • Same as ME 546 and SE 520.
  • 4 graduate hours. No professional credit.
  • Prerequisite: ECE 515 and MATH 444 or MATH 447.
• ECE 534, Random Processes
  Basic concepts of random processes; linear systems with random inputs; Markov processes; spectral analysis; Wiener and Kalman filtering; applications to systems engineering.
  • 4 graduate hours.
  • Prerequisite: One of ECE 313, MATH 461, STAT 400.
• ECE 544, Topics in Signal Processing
  Pattern Recognition.
  • 4 graduate hours.
  • Prerequisite: Math 415 or equivalent; ECE 413, Math 461 or Stat 400 or equivalent; and CS 225, ECE 390 or equivalent programming experience.
• ECE 547, Topics in Image Processing
  Fundamental concepts, techniques, and directions of research in image processing: two-dimensional Fourier transform and filtering, image digitization, coding, restoration, reconstruction, analysis, and recognition.
  • Same as CSE 543.
  • 4 graduate hours.
  • Prerequisite: ECE 310 and ECE 313.
• ECE 551, Digital Signal Processing, II
  Basic concept review of digital signals and systems; computer-aided digital filter design, quantization effects, decimation and interpolation, and fast algorithms for convolution and the DFT; introduction to adaptive signal processing.
  • 4 graduate hours.
  • Prerequisite: ECE 310 and ECE 313.
• ECE 553, Optimum Control Systems
  Theoretical and algorithmic foundations of deterministic optimal control theory, including calculus of variations, maximum principle, and principle of optimality; the Linear-Quadratic-Gaussian design; differential games and H-infinity optimal control design.
  • 4 graduate hours.
  • Prerequisite: ECE 313 and ECE 515.
• ECE 554, Dynamic System Reliability
  Reliability and dynamic performance evaluation for large-scale and complex systems; building on system-theoretic modeling, analysis, and design techniques. Design methods for reliability including architecture design and filter-based fault detection and isolation. Analytical methods for optimal redundancy allocation, sensitivity analysis methods for iterative system design, and other techniques for design optimization. Mechatronic systems used in aircraft and automotive, power electronic systems, and electrical power systems are examples of applications discussed.
  • Same as ME 544.
  • 4 graduate hours.
  • Prerequisite: ECE 313 and ECE 515, or permission of instructor.
• ECE 555, Control of Stochastic Systems
  Stochastic control models; development of control laws by dynamic programming; separation of estimation and control; Kalman filtering; self-tuning regulators; dual controllers; decentralized control.
  • 4 graduate hours.
  • Prerequisite: ECE 515 and ECE 534.
• ECE 556, Coding Theory
  Coding theory with emphasis on the algebraic theory of cyclic codes using finite field arithmetic, decoding of BCH and RS codes, finite field Fourier transform and algebraic geometry codes, convolutional codes, and trellis decoding algorithms.
  • 4 graduate hours.
  • Prerequisite: MATH 417.
• ECE 557, Geometric Control Theory
  Graduate course on mathematical theory of control and optimization, with a focus on geometric and topological methods. The following topics will be covered: introduction to the basics of differential geometric, Riemannian geometry, algebraic topology and Lie group theory. Control systems on manifolds. Controllability and observability of nonlinear systems. Optimization on manifolds and Lie groups and their applications in signal processing and learning. Control of non-holonomic systems and mechanical systems, rigid body dynamics. Optimal control on manifolds and Lie groups. Feedback linearization and feedback invariants. Introduction to quantum control.
  • 4 graduate hours. No professional credit.
  • Prerequisite: ECE 515 or equivalent is required. A course on state-space control theory, multivariable calculus, linear algebra and overall mathematical maturity are recommended.
• ECE 558, Digital Imaging
  Multidimensional signals, convolution, transforms, sampling, and interpolation; design of two-dimensional digital filters; sensor array processing and range-doppler imaging; applications to synthetic aperture radar, optics, tomography, radio astronomy, and beam-forming sonar; image estimation from partial data.
  • 4 graduate hours.
  • Prerequisite: ECE 310 and ECE 313.
• ECE 559, Topics in Communications
  Lectures and discussion related to advanced topics and new areas of interest in the theory of communication systems: information theory, coding theory, and communication network theory. May be repeated in the same term, if topics vary, to a maximum of 12 graduate hours; may be repeated in separate terms, if topics vary, to a maximum of 16 graduate hours. Credit toward a degree from multiple offerings of this course is not given if those offerings have significant overlap, as determined by the ECE department.
  • 4 graduate hours.
  • Prerequisite: As specified each term. (It is expected that each offering will have a 500-level course as a prerequisite or co-requisite.).
• ECE 561, Statistical Inference for Engineers and Data Scientists
  Fundamental principles of statistical decision theory and their application to hypothesis testing and estimation; classical optimality criteria for decision rules; computationally efficient implementations; sequential decision-making; performance analysis; asymptotic properties and performance of decision rules.
  • 4 graduate hours. No professional credit.
  • Prerequisite: ECE 534.
• ECE 562 Advanced Digital Communications
  Digital communication systems modulation, demodulation, signal space methods, channel models, bit error rate, spectral occupancy, synchronization, equalization, trellis-coded modulation, wireless channels, multiantenna systems, spread spectrum, and orthogonal frequency modulation.
  • 4 graduate hours. No professional credit.
  • Prerequisite: ECE 461 or ECE 459.
• ECE 563, Information Theory
  Mathematical models for channels and sources; entropy, information, data compression, channel capacity, Shannon's theorems, and rate-distortion theory.
  • 4 graduate hours.
  • Prerequisite: One of ECE 534, MATH 464, MATH 564.
• ECE 580, Optimization by Vector Space Methods
  Normed, Banach, and Hilbert spaces; applications of the projection theorem and the Hahn-Banach Theorem to problems of minimum norm, least squares estimation, mathematical programming, and optimal control; the Kuhn-Tucker Theorem and Pontryagin's maximum principle; iterative methods.
  • 4 graduate hours.
  • Prerequisite: MATH 415 or MATH 482; MATH 447.
• ECE 586, Topics in Decision and Control
  Lectures and discussions related to advanced topics and new areas of interest in decision and control theory: hybrid, sampled-data, and fault tolerant systems; control over networks; vision-based control; system estimation and identification; dynamic games. May be repeated up to 12 hours within a term, and up to 20 hours total for the course. Credit towards a degree from multiple offerings of this course is not given if those offerings have significant overlap, as determined by the ECE department.
  • 4 graduate hours.
  • Prerequisite: As specified each term. It is expected that each offering will have a 500-level course as prerequisite or co-requisite.

Computing Systems, Networks, Software, and Algorithms

• ECE 407, Cryptography
  Cryptography is a powerful toolbox for building secure systems --- not just for private communication, but also for building fault tolerant protocols, for securely outsourcing computation to untrusted services, and more. The goal of this course is to introduce the concepts of modern cryptography, including a combination of theoretical foundations (how do we precisely state security guarantees and assumptions, and prove that a protocol is designed correctly?) and practical techniques (how do we combine secure primitives to make effective systems?). This course is intended for senior undergraduate students with an interest in applying cryptographic techniques to building secure systems, and for graduate students with an interest in cryptography or systems security.
  • Same as CS 407.
  • 3 or 4 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: CS 225.
• ECE 408, Applied Parallel Programming
  Parallel programming with emphasis on developing applications for processors with many computation cores. Computational thinking, forms of parallelism, programming models, mapping computations to parallel hardware, efficient data structures, paradigms for efficient parallel algorithms, and application case studies.
  • Same as CS 483 and CSE 408.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 220.
• ECE 411, Computer Organization and Design
  Basic computer organization and design: integer and floating-point computer arithmetic; control unit design; pipelining; system interconnect; memory organization; I/O design; reliability and performance evaluation. Laboratory for computer design implementation, simulation, and layout.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 391, CS 241 or CS 341.
• ECE 419, Security Lab
  Operating systems security: access control, least privilege mechanism and malware techniques. Network security: firewalls, sniffing, tunnels, intrusion detection, AAA and worm structure. System security: forensics security architectures, and attack/defend exercises. Complements CS 461 via hands-on project.
  • Same as ECE 419.
  • 3 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: CS 461 or ECE 422.
• ECE 422, Computer Security I
  Fundamental principles of computer and communications security and information assurance: ethics, privacy, notions of threat, vulnerabilities, and risk in systems, information warfare, malicious software, data secrecy and integrity issues, network security, trusted computing, mandatory and discretionary access controls, certification and accreditation of systems against security standards. Security mechanisms: authentication, auditing, intrusion detection, access control, cryptography, security protocols, key distribution.
  • Same as ECE 422.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: One of CS 241, CS 341, or ECE 391.
• ECE 424, Computer Security II
  Program security, trusted base, privacy, anonymity, non-interference, information flow, confinement, advanced auditing, forensics, intrusion detection, key management and distribution, policy composition and analysis, formal approaches to specification and verification of secure systems and protocols, and topics in applied cryptography.
  • Same as ECE 424.
  • 3 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: CS 461. Recommended: CS 475.
• ECE 425, Introduction to VLSI System Design
  Complementary Metal-Oxide Semiconductor (CMOS) technology and theory; CMOS circuit and logic design; layout rules and techniques; circuit characterization and performance estimation; CMOS subsystem design; Very-Large-Scale Integrated (VLSI) systems design methods; VLSI Computer Aided Design (CAD) tools; workstation-based custom VLSI chip design using concepts of cell hierarchy; final project involving specification, design, and evaluation of a VLSI chip or VLSI CAD program; written report and oral presentation on the final project.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 385 or CS 233.
• ECE 426, Principles of Mobile Robotics
  Prepares students in design, navigation, control, and autonomy of aerial and ground robots that operate in harsh, uncertain, and changing field environments. Covers three primary aspects of field robotics: perception (sensing), motion control, and data analytics, and bring everything together through labs involving ground robots and flying unmanned aircraft (drones).
  • Same as ABE 426.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: MATH 221, MATH 225, and MATH 285, or ABE 415, or ABE 440, IE 300, or STAT 400 or equiv, CS 125 or equiv., or graduate standing.
• ECE 428, Distributed Systems
  Protocols, specification techniques, global states and their determination, reliable broadcast, transactions and commitment, security, and real-time systems.
  • Same as CS 425.
  • 3 or 4 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: Credit or concurrent enrollment in one of CS 240, CS 241, CS 340, CS 341 or ECE 391.
• ECE 434, Mobile Computing & Application
  Introduction to cross-disciplinary ideas and techniques in mobile computing, with an emphasis on how they can be composed to build systems and applications on smartphones, tablets, and wearable devices. Topics of interest include smartphone sensing, energy efficiency, indoor localization, augmented reality, context-awareness, gesture recognition, and data analytics. Various techniques and methods utilized to combine them into functional systems, propose a new system, define the underlying problems, and solve them end to end.
  • Same as CS 434.
  • 3 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 391, CS 241, CS 341 or ECE 310.
• ECE 435, Computer Networking Laboratory
  Design, application, analysis, and deployment of communication protocols and system software behind modern cloud/compute/network infrastructures. Students learn the internals of modern system infrastructures, including operating system networking kernels, cloud application service code, and firewall and router configuration. Students will gain experience with widely-used and production-grade code and systems, such as Cisco IOS, the Linux networking stack, and Amazon Web Services. This class links theory with practice to prepare students to confidently carry out tasks they will commonly encounter in industry, such as building an enterprise network, deploying a large-scale cloud service, or implementing a new network protocol.
  • Same as ECE 435.
  • 3 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: One of CS 240, CS 241, CS 340, CS 341 or ECE 391.
• ECE 438, Communication Networks
  Layered architectures and the OSI Reference Model; design issues and protocols in the transport, network, and data link layers; architectures and control algorithms of local-area, point-to-point, and satellite networks; standards in networks access protocols; models of network interconnection; overview of networking and communication software.
  • Same as ECE 438.
  • 3 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: One of CS 241, CS 341 or ECE 391; strongly recommend one of CS 361, STAT 361, ECE 313, MATH 362, MATH 461, MATH 463 or STAT 400.
• ECE 439, Wireless Networks
  Overview of wireless network architectures including cellular networks, local area networks, multi-hop wireless networks such as ad hoc networks, mesh networks, and sensor networks; capacity of wireless networks; medium access control, routing protocols, and transport protocols for wireless networks; mechanisms to improve performance and security in wireless networks; energy-efficient protocols for sensor networks.
  • Same as CS 439.
  • 3 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: ECE 391; CS 241 or CS 341; one of MATH 461, MATH 463, ECE 313.
• ECE 448, Introduction to Artificial Intelligence
  Major topics in and directions of research in artificial intelligence: basic problem solving techniques, knowledge representation and computer inference, machine learning, natural language understanding, computer vision, robotics, and societal impacts.
  • Same as CS 440.
  • 3 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: CS 225; one of CS 361, STAT 361, ECE 313, MATH 362, MATH 461, MATH 463, ;STAT 400 or BIOE 310.
• ECE 449, Machine Learning
  Principles and applications of machine learning. Main paradigms and techniques, including discriminative and generative methods, reinforcement learning: linear regression, logistic regression, support vector machines, deep nets, structured methods, dimensionality reduction, k-means, Gaussian mixtures, expectation maximization, Markov decision processes, and Q-learning. Application areas such as natural language and text understanding, speech recognition, computer vision, data mining, and adaptive computer systems, among others.
  • Same as CS 446.
  • 3 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: CS 225; One of MATH 225, MATH 257, MATH 415, MATH 416, ASRM 406 or BIOE 210; One of CS 361, ECE 313, MATH 461or STAT 400.
• ECE 462, Logic Synthesis
  Unate function theory, unate recursive paradigm, synthesis of two-level logic, synthesis of incompletely specified combinational logic, multi-level logic synthesis, binary decision diagrams, finite state machine synthesis, automatic test pattern generation and design for test, equivalence checking and reachability analysis of finite machines, and technology mapping.
  • 3 undergraduate hours. 3 graduate hours.
  • Prerequisite: ECE 220 or CS 233.
• ECE 470, Introduction to Robotics
  Fundamentals of robotics including rigid motions; homogeneous transformations; forward and inverse kinematics; velocity kinematics; motion planning; trajectory generation; sensing, vision; control.
  • Same as AE 482 and ME 445.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: One of MATH 225, MATH 286, MATH 415, MATH 418.
• ECE 471, Data Science Analytics Using Probablistic Graph Models
  Extracting insights from heterogeneous datasets to support decision-making is fundamental to modern applications. This course teaches students to engineer analysis workflows that use feature engineering, longitudinal machine learning methods, and validation to derive real‐world insights from data. Students gain hands‐on experience through lectures and labs and via three projects involving large-scale real‐world data from domains such as autonomous-vehicles, healthcare and trust. While each workflow is end‐to‐end, students will delve deeper into methods as the course progresses.
  • 3 undergraduate hours. 4 graduate hours.
  • Prerequisite: Basic probability and basic computer programming skills are essential. ECE 313 or CS 361. Prior exposure to basics of scripting languages (such as Python), knowledge of operating systems (e.g., ECE 391, or an equivalent course) is beneficial.
• ECE 478, Formal Software Development Methods
  Mathematical models, languages, and methods for software specification, development, and verification.
  • Same as CS 477.
  • 3 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: CS 225; one of CS 374, ECE 374 or MATH 414.
• ECE 479, IoT and Cognitive Computing
  Offers in-depth coverage on existing and emerging IoT and cognitive computing topics. Detailed topics include definition and characteristics of IoT; IoT enabling technologies; smart domains and applications; IoT systems; IoT design methodology; machine learning and deep learning; embedded GPU and FPGA for IoT; IoT servers and cloud; data analytics for IoT; cognitive computing; cognitive systems design; cognitive application workloads; IoT security; hands-on learning experience to build IoT systems; and various case studies such as smart city, smart home, and IoT for healthcare. Three lab-based machine problems working with actual IoT computing devices together with homework assignments will be given to reinforce students' understanding and learning of the techniques and topics.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: ECE 220 or CS 225.
• ECE 484, Principles of Safe Autonomy
  Introduces techniques for building autonomous systems such as autonomous cars, delivery drones, and manufacturing robots, and techniques for performing their safety analysis. Covers key algorithms and approaches in perception, modeling, motion planning, control, and safety analysis, with a view towards understanding their basic assumptions and performance guarantees. Also provides exposure to some of the state-of-the-art software tools for control, simulation, and analysis. Students will get experience through labs, programming assignments, and they will perform hands-on laboratory work on the Polaris GEM autonomous vehicle platform. Course material is distilled from recent research papers; thus, there is no required textbook.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: CS 124, ECE 220 or equivalent; ECE313, IE300, or STAT400. A course on data structures, algorithms, differential equations, and linear algebra is recommended.
• ECE 489, Robot Dynamics and Control
  Fundamental concepts and analytical methods for analysis and design of robot systems. Laboratory experiments complement theoretical development.
  • Same as SE 422 and ME 446.
  • 4 undergraduate hours. 4 graduate hours.
  • Prerequisite: SE 320.
  • Recommended: ECE 470.
• ECE 492, Introduction to Parallel Programming
  Fundamental issues in design and development of parallel programs for various types of parallel computers. Various programming models according to both machine type and application area. Cost models, debugging, and performance evaluation of parallel programs with actual application examples.
  • Same as CSE 420.
  • 3 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: CS 225.
• ECE 508, Manycore Parallel Algorithms
  Algorithm techniques for enhancing the scalability of parallel software: scatter vs. gather, problem decomposition, spatial sorting and binning, privatization for reduced conflicts, tiling for data locality, regularization for improved load balance, compaction to conserve memory bandwidth, double-buffering to overlap latencies, and data layout for improved efficiency of DRAM accesses.
  • Same as CS 508.
  • 4 graduate hours. No professional credit.
  • Prerequisite: ECE 408 or CS 420.
• ECE 511, Computer Architecture
  Advanced concepts in computer architecture: design, management, and modeling of memory hierarchies; stack-oriented processors; associative processors; pipelined computers; and multiple processor systems. Emphasis on hardware alternatives in detail and their relation to system performance and cost.
  • Same as CSE 521.
  • 4 graduate hours.
  • Prerequisite: ECE 411 or CS 433.
• ECE 512, Computer Microarchitecture
  Design of high performance computer systems; instruction level concurrency; memory system implementation; pipelining, superscalar, and vector processing; compiler back-end code optimization; profile assisted code transformations; code generation and machine dependent code optimization; cache memory design for multiprocessors; synchronization implementation in multiprocessors; compatibility issues; technology factors; state-of-the-art commercial systems.
  • 4 graduate hours.
  • Prerequisite: ECE 511 and CS 426.
• ECE 519, Hardware Verification
  This course teaches algorithms for verification that are applied to very large scale hardware in the chip design industry. The course teaches symbolic model checking, Binary decision diagrams (BDDs), satisfiability (SAT) based algorithms, symbolic simulation, coverage metrics for simulation, automatic assertion generation, analog circuit verification and post Silicon validation algorithms. The course teaches scalable search algorithms that can be applied to discrete and continuous space models.
  • Same as CS 585.
  • 4 graduate hours.
  • No professional credit.
• ECE 522, Emerging Memory and Storage Systems
  We will discuss advanced techniques for building memory and storage systems. It will cover a variety of recent research topics centered around memory and storage systems, including the new and emerging hardware architecture, systems software, memory-centric applications, near-data computing, rack-scale storage, storage security and reliability, mobile/wearable/IoT storage, and storage at rack scale. Through this course, students will learn not only the fundamental concepts of memory and storage systems via the lecture materials, but also the hands-on experience of building and evaluating a memory/storage-centric system via projects.
  • 4 graduate hours. No professional credit.
  • Prerequisite: ECE 391, ECE 411/CS 433 or equivalent courses.
• ECE 524, Advanced Computer Security
  Current research trends in computer and network security. Privacy, tamper-resistance, unwanted traffic, monitoring and surveillance, and critical infrastructure protection. Subtopics will vary depending upon current research trends. Students work in teams in close coordination with the course instructor to develop one of the topics in depth by carrying out background research and an exploratory project.
  • Same as CS 563.
  • 4 graduate hours. No professional credit.
  • Prerequisite: One of CS 461, CS 463, ECE 422 or ECE 424.
• ECE 526, Distributed Algorithms
  Theoretical aspects of distributed algorithms, with an emphasis on formal proofs of correctness and theoretical performance analysis. Algorithms for consensus, clock synchronization, mutual exclusion, debugging of parallel programs, peer-to-peer networks, and distributed function computation; fault-tolerant distributed algorithms; distributed algorithms for wireless networks.
  • Same as CS 539.
  • 4 graduate hours. No professional credit.
  • Prerequisite: One of CS 473, ECE 428, ECE 438.
• ECE 533, Parallel Computer Architecture
  Fundamental concepts in parallel computer architecture, including scalable cache coherence, memory consistency models, hardware and software prefetching, synchronization support, multithreading, multiple processors on a chip, speculative parallelization and execution, transactional memory, processor and memory integration, hardware and software reliability, interaction of memory hierarchies with operating systems and databases, networks, and dataflow, systolic, and data-parallel architectures.
  • Same as CSE 522.
  • 4 graduate hours.
  • Prerequisite: CS 433.
• ECE 541, Computer Systems Analysis
  Development of analytical models of computer systems and application of such models to performance evaluation: scheduling policies, paging algorithms, multiprogrammed resource management, and queuing theory.
  • Same as CS 541.
  • 4 graduate hours.
  • Prerequisite: One of ECE 313, MATH 461, MATH 463.
• ECE 542, Design of Fault-Tolerant Digital Systems
  Advanced concepts in hardware and software fault tolerance: fault models, coding in computer systems, module and system level fault detection mechanism, reconfiguration techniques in multiprocessor systems and VLSI processor arrays, and software fault tolerance techniques such as recovery blocks, N-version programming, checkpointing, and recovery; survey of practical fault-tolerant systems.
  • Same as CS 536.
  • 4 graduate hours.
  • Prerequisite: ECE 411.
• ECE 548, Computer Models of Cognitive Processes
  Formal models and concepts in automated cognition; integrating machine learning and prior knowledge; current approaches and detailed analyses of the role of reasoning in the learning process; computational complexity and fundamental tradeoffs between expressiveness and tractability; implications for state-of-the-art artificial intelligence areas such as automated planning, the semantic web, relational learning, structured prediction, latent models, structure learning, theory formation, etc.; philosophical and psychological aspects of integrating analytic and empirical evidence.
  • Same as ECE 548.
  • 4 graduate hours. No professional credit.
  • Prerequisite: One of CS 440, CS 446, ECE 448 or ECE 449.
• ECE 549, Computer Vision
  Formal models and concepts in automated cognition; integrating machine learning and prior knowledge; current approaches and detailed analyses of the role of reasoning in the learning process; computational complexity and fundamental tradeoffs between expressiveness and tractability; implications for state-of-the-art artificial intelligence areas such as automated planning, the semantic web, relational learning, structured prediction, latent models, structure learning, theory formation, etc.; philosophical and psychological aspects of integrating analytic and empirical evidence.
  • Same as ECE 548.
  • 4 graduate hours. No professional credit.
  • Prerequisite: One of CS 440, CS 446, ECE 448 or ECE 449.
• ECE 550, Advanced Robotic Planning
  Computational approaches to robot motion planning, configuration space, algebraic decompositions, artificial potential fields, retraction, approximate decompositions, planning under uncertainty, grasp planning, and task-level planning.
  • Same as AE 583.
  • Prerequisite: ECE 470.
• ECE 567, Communication Network Analysis
  Performance analysis and design of multiple-user communication systems; emphasis on rigorous formulation and analytical and computational methods; includes queuing networks, decentralized minimum delay routing, and dynamic network flow control.
  • Prerequisite: CS 438; one of ECE 534, MATH 464, MATH 564.
• ECE 584, Embedded System Verification
  Examines formal analysis an synthesis approaches for discrete, continuous, and hybrid models of computing systems and their physical environment. Introduces timed and hybrid automata models. Analysis techniques including model checking, Hoare-style deduction, and abstractions for safety and stability, and controller synthesis strategies with applications in distributed robotics, automobile system, traffic control, and real-time systems.
  • Same as CS 584.
  • 4 graduate hours. No professional credit.
  • Prerequisite: MATH 257 or equivalent.

Computational Science

• ECE 491, Numerical Analysis
  Linear system solvers, optimization techniques, interpolation and approximation of functions, solving systems of nonlinear equations, eigenvalue problems, least squares, and quadrature; numerical handling of ordinary and partial differential equations. 
  
  • Same as CS 450, CSE 401 and MATH 350.
  • 3 undergraduate hours. 3 or 4 graduate hours. Credit is not given toward graduation for both CS 450 and CS 457.
  • Prerequisite: One of CS 101, CS 124 or CS 125; one of CS 357, MATH 257, MATH 357, MATH 415, or MATH 416; MATH 285.
• ECE 493, Advanced Engineering Math 
  Complex linear algebra, inner product spaces, Fourier transforms and analysis of boundary value problems, Sturm-Liouville theory.
  • Same as MATH 487.
  • 3 undergraduate hours. 3 or 4 graduate hours.
  • Prerequisite: One of MATH 284, MATH 285, MATH 286, MATH 441.
• ECE 543, Statistical Learning Theory
  Advanced graduate course on modern probabilistic theory of adaptive and learning systems. The following topics will be covered; basics of statistical decision theory; concentration inequalities; supervised and unsupervised learning; empirical risk minimization; complexity-regularized estimation; generalization bounds for learning algorithms; VC dimension and Rademacher complexities; minimax lower bounds; online learning and optimization. Along with the general theory, the course will discuss applications of statistical learning theory to signal processing, information theory, and adaptive control. Basic prerequisites include probability and random processes, calculus, and linear algebra. Other necessary material and background will be introduced as needed.
  • 4 graduate hours. No professional credit.
    Prerequisite: ECE 534 or equivalent.
• ECE 566, Computation Inference and Learning
  Computational inference and machine learning have seen a surge of interest in the last 15 years, motivated by applications as diverse as computer vision, speech recognition, analysis of networks and distributed systems, big-data analytics, large-scale computer simulations, and indexing and searching of very large databases. This course introduces the mathematical and computational methods that enable such applications. Topics include computational methods for statistical inference, sparsity analysis, approximate inference and search, and fast optimization.
  • 4 graduate hours. No professional credit.
    Prerequisite: ECE 490, ECE 534.