INTRO-ELECTRICAL ENGINEERING

Basic concepts of electrical engineering. Exploration of selected topics and their application. Electrical variables, circuit laws, nonlinear and linear elements, ideal and real sources, transducers, operational amplifiers in simple circuits, external behavior of diodes and transistors, first order RC and RL circuits. Digital representation of a signal, digital logic gates, flipflops. A lab is an integral part of the course. Required of electrical engineering and computer engineering majors.

• MW 4:10 p.m.-5:25 p.m.
• Instructor: David G Vallancourt
  CULPA: 28 Info
• 3.5 points

DIGITAL SYSTEMS LABORATORY

Companion lab course for CSEE W3827. Experiments cover such topics as logic gates; flip-flops; shift registers; counters; combinational logic circuits; sequential logic circuits; programmable logic devices. The lab generally meets on alternate weeks.

• M 4:10 p.m.-6:40 p.m.
• T 4:10 p.m.-6:40 p.m.
• F 1:10 p.m.-3:40 p.m.
• Instructor: Kenneth Shepard
  CULPA: 2 Wikipedia h-index: 64 Info
• 1 points

ELECTRONIC CIRCUITS LABORATORY

Companion lab course for ELEN E3331. Experiments cover such topics as macromodeling of nonidealities of opamps using SPICE; Schmitt triggers and astable multivibrations using op-amps and diodes; logic inverters and amplifiers using bipolar junction transistors; logic inverters and ring oscillators using MOSFETs; filter design using opamps. The lab generally meets on alternate weeks.

• M 4:10 p.m.-6:40 p.m.
• T 4:10 p.m.-6:40 p.m.
• F 1:10 p.m.-3:40 p.m.
• Instructor: Charles A Zukowski
  CULPA: 5 Wikipedia Info
• 1 points

ELECTRONIC CIRCUITS

Operational amplifier circuits. Diodes and diode circuits. MOS and bipolar junction transistors. Biasing techniques. Small-signal models. Single-stage transistor amplifiers. Analysis and design of CMOS logic gates. A/D and D/A converters.

• MW 11:40 a.m.-12:55 p.m.
• Instructor: David G Vallancourt
  CULPA: 28 Info
• 3 points

EE SENIOR DESIGN PROJECT

Students work in teams to specify, design, implement and test an engineering prototype. Involves technical as well as non-technical considerations, such as manufacturability, impact on the environment, economics, adherence to engineering standards, and other real-world constraints. Projects are presented publicly by each design team in a school-wide expo.

• TR 11:40 a.m.-12:55 p.m.
• F 6 p.m.-7 p.m.
• Instructor: David G Vallancourt
  CULPA: 28 Info
• 3 points

ELECTROMAGNETICS

Basic field concepts. Interaction of time-varying electromagnetic fields. Field calculation of lumped circuit parameters. Transition from electrostatic to quasistatic and electromagnetic regimes. Transmission lines. Energy transfer, dissipation, and storage. Waveguides. Radiation.

• MW 2:40 p.m.-3:55 p.m.
• F 2:40 p.m.-3:55 p.m.
• Instructor: Keren Bergman
  CULPA: 1 Wikipedia h-index: 69 Info
• 4 points

INTRO TO COMMUNICATION SYSTEMS

A basic course in communication theory, stressing modern digital communication systems. Nyquist sampling, PAM and PCM/DPCM systems, time division multipliexing, high frequency digital (ASK, OOK, FSK, PSK) systems, and AM and FM systems. An introduction to noise processes, detecting signals in the presence of noise, Shannons theorem on channel capacity, and elements of coding theory.

• TR 2:40 p.m.-3:55 p.m.
• Instructor: Irving Kalet
  CULPA: 3 h-index: 12 Info
• 3 points

Computing with Brain Circuits of Model O

Building the functional map of the fruit fly brain. Molecular transduction and spatio-temporal encoding in the early visual system. Predictive coding in the Drosophila retina. Canonical circuits in motion detection. Canonical navigation circuits in the central complex. Molecular transduction and combinatorial encoding in the early olfactory system. Predictive coding in the antennal lobe. The functional role of the mushroom body and the lateral horn. Canonical circuits for associative learning and innate memory. Projects in Python.

• M 7 p.m.-9:30 p.m.
• Instructor: Aurel A Lazar
  h-index: 53 Info
• 3 points

COMMUNICATION CIRCUITS

Principles of electronic circuits used in the generation, transmission, and reception of signal waveforms, as used in analog and digital communication systems. Nonlinearity and distortion; power amplifiers; tuned amplifiers; oscillators; multipliers and mixers; modulators and demodulators; phase-locked loops. An extensive design project is an integral part of the course.

• T 4:10 p.m.-6:40 p.m.
• Instructor: Emily Naviasky
  Info
• 3 points

WAVE TRANSMISSION-FIBER OPTICS

Waves and Maxwell’s equations. Field energetics, dispersion, complex power. Waves in dielectrics and in conductors. Reflection and refraction. Oblique incidence and total internal reflection. Transmission lines and conducting waveguides. Planar and circular dielectric waveguides; integrated optics and optical fibers. Hybrid and LP modes. Graded-index fibers. Mode coupling; wave launching.

• MW 2:40 p.m.-3:55 p.m.
• Instructor: Xiang Meng
  h-index: 8 Info
• 3 points

SOL ENERGY/SMART GRID POWR SYS

• R 7 p.m.-9:30 p.m.
• Instructor: Mohamed Kamaludeen
  Info
• 3 points

DIGITAL COMMUNICATIONS

Digital communications for both point-to-point and switched applications is further developed. Optimum receiver structures and transmitter signal shaping for both binary and M-ary signal transmission. An introduction to block codes and convolutional codes, with application to space communications.

• W 7 p.m.-9:30 p.m.
• Instructor: Alexei Ashikhmin
  Info
• 3 points

Machine Learning for Signals, Informatio

ML FOR SIG, INF

• W 4:10 p.m.-6:40 p.m.
• Instructor: John W Paisley
  CULPA: 1 Info
• 3 points

Quantum Optimization and Machine Learnin

QUANTUM OPT & ML

An introduction to the recent development in quantum optimization and quantum machine learning using gate-based Noisy Intermediate Scale Quantum (NISQ) computers. IBM’s quantum programming framework Qiskit is utilized. Qbits, quantum gates and quantum measurements, quantum algorithms (Grover’s search, Simon’s algorithm, quantum Fourier transform, quantum phase estimation) quantum optimization (quantum annealing, QAOA, variational quantum eigensolver), quantum machine learning (quantum support vector machine, quantum neural networks).

• F 1:10 p.m.-3:40 p.m.
• Instructor: Xiaodong Wang
  CULPA: 15 Info
• 3 points

RANDOM SIGNALS & NOISE

Characterization of stochastic processes as models of signals and noise; stationarity, ergodicity, correlation functions, and power spectra. Gaussian processes as models of noise in linear and nonlinear systems; linear and nonlinear transformations of random processes; orthogonal series representations. Applications to circuits and devices, to communication, control, filtering, and prediction.

• TR 11:40 a.m.-12:55 p.m.
• Instructor: Irving Kalet
  CULPA: 3 h-index: 12 Info
• 3 points

COMPUTER ARCHITECTURE

Focuses on advanced topics in computer architecture, illustrated by case studies from classic and modern processors. Fundamentals of quantitative analysis. Pipelining. Memory hierarchy design. Instruction-level and thread-level parallelism. Data-level parallelism and graphics processing units. Multiprocessors. Cache coherence. Interconnection networks. Multi-core processors and systems-on-chip. Platform architectures for embedded, mobile, and cloud computing.

• TR 1:10 p.m.-2:25 p.m.
• Instructor: Tanvir Ahmed Khan
  Info
• 3 points

DIGITAL IMAGE PROCESSING

Introduction to the mathematical tools and algorithmic implementation for representation and processing of digital pictures, videos, and visual sensory data. Image representation, filtering, transform, quality enhancement, restoration, feature extraction, object segmentation, motion analysis, classification, and coding for data compression. A series of programming assignments reinforces material from the lectures.

• W 10:10 a.m.-12:40 p.m.
• Instructor: Christine P Hendon
  Wikipedia h-index: 21 Info
• 3 points

TOPICS IN EE & CE

ELEC VEHICLE DRIVETRAIN LAB

Selected topics in electrical and computer engineering. Content varies from year to year, and different topics rotate through the course numbers 4900 to 4909.

• F 10:10 a.m.-12:40 p.m.
• Instructor: Matthias Preindl
  h-index: 26 Info
• 3 points

TPC NEUROSCI & DEEP LEARN

Comp. w. Brain Cir of MO

Selected advanced topics in neuroscience and deep learning. Content varies from year to year, and different topics rotate through the course numbers 6070 to 6079.

• M 7 p.m.-9:30 p.m.
• Instructor: Aurel A Lazar
  h-index: 53 Info
• 3 points

ADV ANALOG INTEGRATED CIRCUITS

Integrated circuit device characteristics and models; temperature- and supply-independent biasing; IC operational amplifier analysis and design and their applications; feedback amplifiers, stability and frequency compensation techniques; noise in circuits and low-noise design; mismatch in circuits and low-offset design. Computer-aided analysis techniques are used in homework(s) or a design project.

• R 4:10 p.m.-6:40 p.m.
• Instructor: Harish Krishnaswamy
  Info
• 3 points

Analog-Digital Interfaces in VLSI

Analog-to-digital and digital-to-analog conversion techniques for very large scale integrated circuits and systems. Precision sampling; quantization; A/D and D/A converter architectures and metrics; Nyquist architectures; oversampling architectures; correction techniques; system considerations. A design project is an integral part of this course.

• T 7 p.m.-9:30 p.m.
• Instructor: Timothy Dickson
  Info
• 3 points

MICROWAVE CIRCUIT DESIGN

Introduction to microwave engineering and microwave circuit design. Review of transmission lines. Smith chart, S-parameters, microwave impedance matching, transformation and power combining networks, active and passive microwave devices, S-parameter-based design of RF and microwave amplifiers. A microwave circuit design project (using microwave CAD) is an integral part of the course.

• M 4:10 p.m.-6:40 p.m.
• Instructor: Yves Baeyens
  h-index: 31 Info
• 3 points

ADV DIGITAL ELECTRONIC CIRCUIT

Advanced topics in the design of digital integrated circuits. Clocked and non-clocked combinational logic styles. Timing circuits: latches and flip-flops, phase-locked loops, delay-locked loops. SRAM and DRAM memory circuits. Modeling and analysis of on-chip interconnect. Power distribution and power-supply noise. Clocking, timing, and synchronization issues. Circuits for chip-to-chip electrical communication. Advanced technology issues that affect circuit design. The class may include a team circuit design project.

• TR 2:40 p.m.-3:55 p.m.
• Instructor: Mingoo Seok
  h-index: 31 Info
• 3 points

VLSI DESIGN LABORATORY

Design of a CMOS mixed-signal integrated circuit. The class divides up into teams to work on mixed-signal integrated circuit designs. The chips are fabricated to be tested the following term. Lectures cover use of computer-aided design tools, design issues specific to the projects, and chip integration issues. This course shares lectures with E4350, but the complexity requirements of integrated circuits are higher.

• W 1:10 p.m.-3:40 p.m.
• Instructor: Peter Kinget
  CULPA: 1 h-index: 47 Info
• 3 points

LIGHTWAVE DEVICES

Electro-optics: principles; electro-optics of liquid crystals and photo-refractive materials. Nonlinear optics: second-order nonlinear optics; third-order nonlinear optics; pulse propagation and solitons. Acousto-optics: interaction of light and sound; acousto-optic devices. Photonic switching and computing: photonic switches; all-optical switches; bistable optical devices. Introduction to fiber-optic communications: components of the fiber-optic link; modulation, multiplexing and coupling; system performance; receiver sensitivity; coherent optical communications.

• T 4:10 p.m.-6:40 p.m.
• Instructor: Xiang Meng
  h-index: 8 Info
• 3 points

PHOTONIC INTEGRATED CIRCUITS

Photonic integrated circuits are important subsystem components for telecommunications, optically controlled radar, optical signal processing, and photonic local area networks. An introduction to the devices and the design of these circuits. Principle and modeling of dielectric waveguides (including silica on silicon and InP based materials), waveguide devices (simple and star couplers), and surface diffractive elements. Discussion of numerical techniques for modeling circuits, including beam propagation and finite difference codes, and design of other devices: optical isolators, demultiplexers.

• W 4:10 p.m.-6:40 p.m.
• Instructor: Michal Lipson
  CULPA: 1 Wikipedia h-index: 114 Info
• 3 points

TOPICS DATA-DRIVEN ANAL & COMP

Advanced Deep Learning

Selected advanced topics in data-driven analysis and computation. Content varies from year to year, and different topics rotate through the course numbers 6690 to 6699.

• W 10:10 a.m.-12:40 p.m.
• Instructor: Zoran Kostic
  CULPA: 1 h-index: 24 Info
• 3 points

TOPICS DATA-DRIVEN ANAL & COMP

Deep Learning on the Edge

Selected advanced topics in data-driven analysis and computation. Content varies from year to year, and different topics rotate through the course numbers 6690 to 6699.

• W 1:10 p.m.-3:40 p.m.
• Instructor: Zoran Kostic
  CULPA: 1 h-index: 24 Info
• 3 points

TOPICS DATA-DRIVEN ANAL & COMP

TPC: MATHEMATICS OF DEEP LEARN

Selected advanced topics in data-driven analysis and computation. Content varies from year to year, and different topics rotate through the course numbers 6690 to 6699.

• T 4:10 p.m.-6:40 p.m.
• Instructor: Predrag R Jelenkovic
  CULPA: 1 h-index: 35 Info
• 3 points

TOPICS IN NETWORKING

5G&NxtG Programmable Ntwr

Further study of areas such as communication protocols and architectures, flow and congestion control in data networks, performance evaluation in integrated networks. Content varies from year to year, and different topics rotate through the course numbers 6770 to 6779.

• F 1:10 p.m.-3:40 p.m.
• Instructor: Doru Calin
  h-index: 26 Info
• 3 points

TOPICS IN NETWORKING

MachineLearn for Networks

Further study of areas such as communication protocols and architectures, flow and congestion control in data networks, performance evaluation in integrated networks. Content varies from year to year, and different topics rotate through the course numbers 6770 to 6779.

• W 7 p.m.-9:30 p.m.
• Instructor: Anwar I Walid
  CULPA: 1 Info
• 3 points

TOPICS IN NETWORKING

Stat Sgnl Process & Learn

Further study of areas such as communication protocols and architectures, flow and congestion control in data networks, performance evaluation in integrated networks. Content varies from year to year, and different topics rotate through the course numbers 6770 to 6779.

• M 7 p.m.-9:30 p.m.
• Instructor: Guido H Jajamovich
  Info
• 3 points

TOPICS IN SIGNAL PROCESSING

INTRO TO BLOCKCHAIN TECH

Advanced topics in signal processing, such as multidimensional signal processing, image feature extraction, image/video editing and indexing, advanced digital filter design, multirate signal processing, adaptive signal processing, and wave-form coding of signals. Content varies from year to year, and different topics rotate through the course numbers 6880 to 6889. 

• F 8:10 a.m.-10 a.m.
• 3 points

TOPICS IN SIGNAL PROCESSING

LARGE-SCALE STREAM PROCESSING

Advanced topics in signal processing, such as multidimensional signal processing, image feature extraction, image/video editing and indexing, advanced digital filter design, multirate signal processing, adaptive signal processing, and wave-form coding of signals. Content varies from year to year, and different topics rotate through the course numbers 6880 to 6889.  Topic: Large Data Stream Processing.

• R 7 p.m.-9:30 p.m.
• Instructor: Deepak S Turaga
  Info
• 3 points

TOPICS-INFORMATION PROCESSING

eBPF Research Seminar

Advanced topics spanning electrical engineering and computer science such as speech processing and recognition, image and multimedia content analysis, and other areas drawing on signal processing, information theory, machine learning, pattern recognition, and related topics. Content varies from year to year, and different topics rotate through the course numbers 6890 to 6899.

• R 10:10 a.m.-12:40 p.m.
• Instructor: Asaf Cidon
  h-index: 20 Info
• 3 points

TOPICS-INFORMATION PROCESSING

Reinforcement Learning

Advanced topics spanning electrical engineering and computer science such as speech processing and recognition, image and multimedia content analysis, and other areas drawing on signal processing, information theory, machine learning, pattern recognition, and related topics. Content varies from year to year, and different topics rotate through the course numbers 6890 to 6899.

• T 1:10 p.m.-3:40 p.m.
• Instructor: Javad Ghaderi
  h-index: 17 Info
• 3 points

TOPICS-INFORMATION PROCESSING

TPC: Adv Big Data & AI

Advanced topics spanning Electrical Engineering and Computer Science such as speech processing and recognition, image and multimedia content analysis, and other areas drawing on signal processing, information theory, machine learning, pattern recognition, and related topics. Content varies from year to year, and different topics rotate through the course numbers 6890 to 6899.  Topic: Advanced Big Data Analytics.

• F 7 p.m.-9:30 p.m.
• Instructor: Ching-Yung Lin
  h-index: None Info
• 3 points

TOPICS-INFORMATION PROCESSING

Data Science Fundamentals

Advanced topics spanning electrical engineering and computer science such as speech processing and recognition, image and multimedia content analysis, and other areas drawing on signal processing, information theory, machine learning, pattern recognition, and related topics. Content varies from year to year, and different topics rotate through the course numbers 6890 to 6899.

• TR 10:10 a.m.-11:25 a.m.
• Instructor: James Anderson
  h-index: 18 Info
• 3 points

TPCS-ELEC & COMPUT ENGINEERING

Smart Grid-Holist. Approa

Selected topics in electrical and computer engineering. Content varies from year to year, and different topics rotate through the course numbers 6900 to 6909.

• W 7 p.m.-9:30 p.m.
• Instructor: Sindhu Suresh
  Info
• 3 points

TPCS-ELEC & COMPUT ENGINEERING

Future Energy: Econ-Syst

Selected topics in electrical and computer engineering. Content varies from year to year, and different topics rotate through the course numbers 6900 to 6909.

• MW 11:40 a.m.-12:55 p.m.
• Instructor: Debasis Mitra
  Wikipedia h-index: 61 Info
• 3 points

SEM IN LIGHTWAVE COMMUNICATNS

Recent theoretical and experimental developments in light wave communications research. Examples of topics that may be treated include information capacity of light wave channels, photonic switching, novel light wave network architectures, and optical neural networks.

• F 9 a.m.-11:30 a.m.
• Instructor: Keren Bergman
  CULPA: 1 Wikipedia h-index: 69 Info
• 3 points

INFO & COMMUNICATION THEORIES

Wireless & Mobile Ntwking

• W 1:10 p.m.-3:40 p.m.
• Instructor: Gil Zussman
  CULPA: 3 h-index: 39 Info
• 3 points