THE DIGITAL INFORMATION AGE
An introduction to information transmission and storage, including technological issues. Binary numbers; elementary computer logic; digital speech and image coding; basics of compact disks, telephones, modems, faxes, UPC bar codes, and the World Wide Web. Projects include implementing simple digital logic systems and Web pages. Intended primarily for students outside the School of Engineering and Applied Science. The only prerequisite is a working knowledge of elementary algebra.
- TR 11:40 a.m.-12:55 p.m.
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Instructor:
David G Vallancourt
CULPA: 28
Info
- 3 points
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.
- TR 4:10 p.m.-5:25 p.m.
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Instructor:
David G Vallancourt
CULPA: 28
Info
- 3.5 points
SOLID ST,MICROWAVE,FBR OPT LAB
Optical electronics and communications. Microwave circuits. Physical electronics.
- W 4:10 p.m.-6:40 p.m.
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Instructor:
Wen I Wang
CULPA: 1 Info - 3 points
CIRCUIT ANALYSIS LABORATORY
Companion lab course for ELEN E3201. Experiments cover such topics as: use of measurement instruments; HSPICE simulation; basic network theorems; linearization of nonlinear circuits using negative feedback; op-amp circuits; integrators; second order RLC circuits. The lab generally meets on alternate weeks.
- M 2:40 p.m.-5:10 p.m.
- R 10:10 a.m.-12:40 p.m.
- F 10:10 a.m.-12:40 p.m.
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Instructor:
Charles A Zukowski
CULPA: 5
Wikipedia
Info
- 1 points
SIGNALS & SYSTEMS LABORATORY
Companion lab course for ELEN E3801. Experiments cover topics such as: introduction and use of MATLAB for numerical and symbolic calculations; linearity and time invariance; continuous-time convolution; Fourier-series expansion and signal reconstruction; impulse response and transfer function; forced response. The lab generally meets on alternate weeks.
- M 6:10 p.m.-8:40 p.m.
- R 4:10 p.m.-6:40 p.m.
- F 1:10 p.m.-3:40 p.m.
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Instructor:
Xiaodong Wang
CULPA: 15 Info - 1 points
SOLID STATE DEVICES-MATERIALS
Crystal structure and energy band theory of solids. Carrier concentration and transport in semiconductors. P-n junction and junction transistors. Semiconductor surface and MOS transistors. Optical effects and optoelectronic devices. Fabrication of devices and the effect of process variation and distribution statistics on device and circuit performance.
- TR 11:40 a.m.-12:55 p.m.
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Instructor:
Savannah Eisner
Info - 3.5 points
CIRCUIT ANALYSIS
A course on analysis of linear and nonlinear circuits and their applications. Formulation of circuit equations. Network theorems. Transient response of first and second order circuits. Sinusoidal steady state-analysis. Frequency response of linear circuits. Poles and zeros. Bode plots. Two-port networks.
- MW 11:40 a.m.-12:55 p.m.
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Instructor:
Charles A Zukowski
CULPA: 5
Wikipedia
Info
- 3.5 points
ELECTRICAL ENGINEERING PRACTICE
Design project planning, written and oral technical communication, the origin and role of standards, engineering ethics, and practical aspects of engineering as a profession, such as career development and societal and environmental impact. Generally taken fall of senior year just before ELEN E3390.
- M 11:40 a.m.-12:55 p.m.
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Instructor:
David G Vallancourt
CULPA: 28
Info
- 1 points
SIGNALS AND SYSTEMS
Modeling, description, and classification of signals and systems. Continuous-time systems. Time domain analysis, convolution. Frequency domain analysis, transfer functions. Fourier series. Fourier and Laplace transforms. Discrete-time systems and the Z transform.
- TR 7:10 p.m.-8:25 p.m.
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Instructor:
Xiaodong Wang
CULPA: 15 Info - 3.5 points
PROJECTS IN ELEC ENGINEERING
May be repeated for credit, but no more than 3 total points may be used for degree credit. Independent project involving laboratory work, computer programming, analytical investigation, or engineering design.
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Instructor:
Dimitris Anastassiou
Wikipedia Info -
Instructor:
Keren Bergman
CULPA: 1 Wikipedia h-index: 69 Info -
Instructor:
Shih-Fu Chang
CULPA: 3
Wikipedia
h-index: 122
Info
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Instructor:
Javad Ghaderi
h-index: 17 Info -
Instructor:
Christine P Hendon
Wikipedia h-index: 21 Info -
Instructor:
Predrag R Jelenkovic
CULPA: 1 h-index: 35 Info -
Instructor:
Xiaofan Jiang
h-index: 24 Info -
Instructor:
Ethan Katz-Bassett
h-index: 31 Info -
Instructor:
Dion Khodagholy Araghy
Info -
Instructor:
Peter Kinget
CULPA: 1 h-index: 47 Info -
Instructor:
Zoran Kostic
CULPA: 1 h-index: 24 Info -
Instructor:
Harish Krishnaswamy
Info -
Instructor:
Ioannis Kymissis
CULPA: 4 h-index: 48 Info -
Instructor:
Aurel A Lazar
h-index: 53 Info -
Instructor:
Michal Lipson
CULPA: 1 Wikipedia h-index: 114 Info -
Instructor:
Nima Mesgarani
h-index: 35 Info -
Instructor:
Debasis Mitra
Wikipedia h-index: 61 Info -
Instructor:
John W Paisley
CULPA: 1 Info -
Instructor:
Matthias Preindl
h-index: 26 Info -
Instructor:
Mingoo Seok
h-index: 31 Info -
Instructor:
Kenneth Shepard
CULPA: 2 Wikipedia h-index: 64 Info -
Instructor:
Tanvir Ahmed Khan
Info -
Instructor:
Yannis P Tsividis
CULPA: 4
Wikipedia
Info
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Instructor:
David G Vallancourt
CULPA: 28
Info
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Instructor:
Wen I Wang
CULPA: 1 Info -
Instructor:
Xiaodong Wang
CULPA: 15 Info -
Instructor:
John Wright
CULPA: 1 h-index: 44 Info -
Instructor:
Charles A Zukowski
CULPA: 5
Wikipedia
Info
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Instructor:
Gil Zussman
CULPA: 3
h-index: 39
Info
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Instructor:
Savannah Eisner
Info -
Instructor:
James Anderson
h-index: 18 Info -
Instructor:
Xiang Meng
h-index: 8 Info - 0-3 points
COMP NEURO: CIRCUITS IN BRAIN
The biophysics of computation: modeling biological neurons, the Hodgkin-Huxley neuron, modeling channel conductances and synapses as memristive systems, bursting neurons and central pattern generators, I/O equivalence and spiking neuron models. Information representation and neural encoding: stimulus representation with time encoding machines, the geometry of time encoding, encoding with neural circuits with feedback, population time encoding machines. Dendritic computation: elements of spike processing and neural computation, synaptic plasticity and learning algorithms, unsupervised learning and spike time-dependent plasticity, basic dendritic integration. Projects in MATLAB.
- T 7 p.m.-9:30 p.m.
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Instructor:
Aurel A Lazar
h-index: 53 Info - 3 points
NEURAL NETWRKS & DEEP LEARNING
Developing features - internal representations of the world, artificial neural networks, classifying handwritten digits with logistics regression, feedforward deep networks, back propagation in multilayer perceptrons, regularization of deep or distributed models, optimization for training deep models, convolutional neural networks, recurrent and recursive neural networks, deep learning in speech and object recognition.
- F 10:10 a.m.-12:40 p.m.
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Instructor:
Zoran Kostic
CULPA: 1 h-index: 24 Info - 3 points
INTRO-GENOMIC INFO SCI & TECH
INTRO GENOMIC INFO SCI & TECH
Introduction to computational biology with emphasis on genomic data science tools and methodologies for analyzing data, such as genomic sequences, gene expression measurements and the presence of mutations. Applications of machine learning and exploratory data analysis for predicting drug response and disease progression. Latest technologies related to genomic information, such as single-cell sequencing and CRISPR, and the contributions of genomic data science to the drug development process.
- M 7 p.m.-9:30 p.m.
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Instructor:
Tai-Hsien Ou Yang
Info - 3 points
BRAIN COMPUTER INTERFACES LAB
Hands-on experience with basic neural interface technologies. Recording EEG (electroencephalogram) signals using data acquisition systems (non-invasive, scalp recordings). Real-time analysis and monitoring of brain responses. Analysis of intention and perception of external visual and audio signals.
- T 10:10 a.m.-12:40 p.m.
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Instructor:
Nima Mesgarani
h-index: 35 Info - 3 points
Advanced Solid State Devices and Materia
Adv Solid State Device &
Crystal structure and energy band theory of solids. Carrier concentration and transport in semiconductors. P-n junction and junction transistors. Semiconductor surface and MOS transistors. Optical effects and optoelectronic devices. Fabrication of devices and the effect of process variation and distribution statistics on device and circuit performance. Course shares lectures with ELEN E3106, but the work requirements differ. Undergraduate students are not eligible to register.
- TR 11:40 a.m.-12:55 p.m.
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Instructor:
Savannah Eisner
Info - 3 points
MOD DISPLAY SCI & TECHNOLOGY
Introduction to modern display systems in an engineering context. The basis for visual perception, image representation, color space, metrics of illumination. Physics of luminescence, propagation and manipulation of light in anisotropic media, emissive displays, and spatial light modulators. Fundamentals of display addressing, the Alt-Pleshko theorem, multiple line addressing. Large area electronics, fabrication, and device integration of commercially important display types. A series of short laboratories will reinforce material from the lectures. Enrollment may be limited.
- MW 10:10 a.m.-11:25 a.m.
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Instructor:
Ioannis Kymissis
CULPA: 4 h-index: 48 Info - 3 points
ANALOG ELECTRONIC CIRCUITS
Differential and multistage amplifiers; small-signal analysis; biasing techniques; frequency response; negative feedback; stability criteria; frequency compensation techniques. Analog layout techniques. An extensive design project is an integral part of the course.
- R 4:10 p.m.-6:40 p.m.
- 3 points
DIGITAL VLSI CIRCUITS
Design and analysis of high speed logic and memory. Digital CMOS and BiCMOS device modeling. Integrated circuit fabrication and layout. Interconnect and parasitic elements. Static and dynamic techniques. Worst-case design. Heat removal and I/O. Yield and circuit reliability. Logic gates, pass logic, latches, PLAs, ROMs, RAMs, receivers, drivers, repeaters, sense amplifiers.
- TR 1:10 p.m.-2:25 p.m.
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Instructor:
Kenneth Shepard
CULPA: 2 Wikipedia h-index: 64 Info - 3 points
FUNDAMENTALS OF PHOTONICS
Planar resonators. Photons and photon streams. Photons and atoms: energy levels and band structure; interactions of photons with matter; absorption, stimulated and spontaneous emission; thermal light, luminescence light. Laser amplifiers: gain, saturation, and phase shift; rate equations; pumping. Lasers: theory of oscillation; laser output characteristics. Photons in semiconductors: generation, recombination, and injection; heterostructures; absorption and gain coefficients. Semiconductor photon sources: LEDs; semiconductor optical amplifiers; homojunction and heterojunction laser diodes. Semiconductor photon detectors: p-n, p-i-n, and heterostructure photo diodes; avalanche photodiodes.
- W 4:10 p.m.-6:40 p.m.
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Instructor:
Michal Lipson
CULPA: 1 Wikipedia h-index: 114 Info - 3 points
OPTICAL SYSTEMS
OPTICAL SYSTEMS & NETWORKS
Introduction to optical systems based on physical design and engineering principles. Fundamental geometrical and wave optics with specific emphasis on developing analytical and numerical tools used in optical engineering design. Focus on applications that employ optical systems and networks, including examples in holographic imaging, tomography, Fourier imaging, confocal microscopy, optical signal processing, fiber optic communication systems, optical interconnects and networks.
- R 10:10 a.m.-12:40 p.m.
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Instructor:
Christine P Hendon
Wikipedia h-index: 21 Info - 3 points
POWER SYSTEMS ANALYSIS
Modeling of power networks, steady-state and transient behaviors, control and optimization, electricity market, and smart grid.
- W 7 p.m.-9:30 p.m.
- 3 points
Electric Machines
Introduction to principles, analysis, and applications of electric machines; transformers, DC machines, induction motors, and synchronous machines. Fundamentals of electromagnetic energy conversion, steady-state and dynamic machine models.
- R 7 p.m.-9:30 p.m.
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Instructor:
Sindhu Suresh
Info - 3 points
Numerical Methods for Data Analysis
Num Methods for Data Anal
An introduction to the mathematical and computational foundations of data analysis with linear models. Develops theoretical and computational understanding of numerical linear algebra algorithms for problems including data fitting, data classification, clustering, and data reduction. Focus includes vector spaces, matrix factorization, least squares methods, and singular value decompositions. Illustrations on a variety of engineering applications, including power networks, autonomous and electric vehicles, quantum computing, medical imaging, and systems biology.
- MW 1:10 p.m.-2:25 p.m.
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Instructor:
James Anderson
h-index: 18 Info - 3 points
CONVEX OPTIMIZATION FOR ENG
CONVEX OPTIMIZATION ELCT ENG
Theory of convex optimization; numerical algorithms; applications in circuits, communications, control, signal processing and power systems.
- MW 10:10 a.m.-11:25 a.m.
- 3 points
Machine Learning for Signals, Informatio
ML FOR SIG, INF
- T 1:10 p.m.-3:40 p.m.
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Instructor:
John W Paisley
CULPA: 1 Info - 3 points
Heterogeneous Computing for Signal and D
HETEROGENEOUS COMPUTING
Methods for deploying signal and data processing algorithms on contemporary general purpose graphics processing units (GPGPUs) and heterogeneous computing infrastructures. Using programming languages such as OpenCL and CUDA for computational speedup in audio, image and video processing and computational data analysis. Significant design project.
- R 1:10 p.m.-3:40 p.m.
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Instructor:
Zoran Kostic
CULPA: 1 h-index: 24 Info - 3 points
Artificial Intelligence of Things (AIoT)
IoT - INTELLIG & CONNECTED SYS
Artificial Intelligence of Things (AIoT), Internet of Things (IoT), and Cyber-Physical Systems (CPS). Embedded and mobile platforms. Embedded programming. Sensors, actuators, and interfaces. Wireless networking, web services, and databases. Edge and cloud computing. Large language models (LLMs) for AIoT. Time-series data visualization and analytics. Group projects to build end-to-end AIoT systems and applications.
- MW 2:40 p.m.-3:55 p.m.
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Instructor:
Xiaofan Jiang
h-index: 24 Info - 3 points
DIGITAL SIGNAL PROCESSING
Digital filtering in time and frequency domain, including properties of discrete-time signals and systems, sampling theory, transform analysis, system structures, IIR and FIR filter design techniques, the discrete Fourier transform, fast Fourier transforms.
- M 4:10 p.m.-6:40 p.m.
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Instructor:
John Wright
CULPA: 1 h-index: 44 Info - 3 points
ADVANCED LOGIC DESIGN
An introduction to modern digital system design. Advanced topics in digital logic: controller synthesis (Mealy and Moore machines); adders and multipliers; structured logic blocks (PLDs, PALs, ROMs); iterative circuits. Modern design methodology: register transfer level modelling (RTL); algorithmic state machines (ASMs); introduction to hardware description languages (VHDL or Verilog); system-level modelling and simulation; design examples.
- TR 2:40 p.m.-3:55 p.m.
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Instructor:
Mingoo Seok
h-index: 31 Info - 3 points
INTERMEDIATE PROJECTS
May be repeated for credit, but no more than 3 total points may be used for degree credit. Substantial independent project involving laboratory work, computer programming, analytical investigation, or engineering design.
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Instructor:
Dimitris Anastassiou
Wikipedia Info -
Instructor:
Keren Bergman
CULPA: 1 Wikipedia h-index: 69 Info -
Instructor:
Shih-Fu Chang
CULPA: 3
Wikipedia
h-index: 122
Info
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Instructor:
Javad Ghaderi
h-index: 17 Info -
Instructor:
Christine P Hendon
Wikipedia h-index: 21 Info -
Instructor:
Predrag R Jelenkovic
CULPA: 1 h-index: 35 Info -
Instructor:
Xiaofan Jiang
h-index: 24 Info -
Instructor:
Ethan Katz-Bassett
h-index: 31 Info -
Instructor:
Dion Khodagholy Araghy
Info -
Instructor:
Peter Kinget
CULPA: 1 h-index: 47 Info -
Instructor:
Zoran Kostic
CULPA: 1 h-index: 24 Info -
Instructor:
Harish Krishnaswamy
Info -
Instructor:
Ioannis Kymissis
CULPA: 4 h-index: 48 Info -
Instructor:
Aurel A Lazar
h-index: 53 Info -
Instructor:
Michal Lipson
CULPA: 1 Wikipedia h-index: 114 Info -
Instructor:
Nima Mesgarani
h-index: 35 Info -
Instructor:
Debasis Mitra
Wikipedia h-index: 61 Info -
Instructor:
John W Paisley
CULPA: 1 Info -
Instructor:
Matthias Preindl
h-index: 26 Info -
Instructor:
Mingoo Seok
h-index: 31 Info -
Instructor:
Kenneth Shepard
CULPA: 2 Wikipedia h-index: 64 Info -
Instructor:
Tanvir Ahmed Khan
Info -
Instructor:
Yannis P Tsividis
CULPA: 4
Wikipedia
Info
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Instructor:
David G Vallancourt
CULPA: 28
Info
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Instructor:
Wen I Wang
CULPA: 1 Info -
Instructor:
Xiaodong Wang
CULPA: 15 Info -
Instructor:
John Wright
CULPA: 1 h-index: 44 Info -
Instructor:
Charles A Zukowski
CULPA: 5
Wikipedia
Info
-
Instructor:
Gil Zussman
CULPA: 3
h-index: 39
Info
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Instructor:
Savannah Eisner
Info -
Instructor:
James Anderson
h-index: 18 Info -
Instructor:
Xiang Meng
h-index: 8 Info - 0-3 points
ADVANCED PROJECTS
May be repeated for up to 6 points of credit. Graduate-level projects in various areas of electrical engineering and computer science. In consultation with an instructor, each student designs his or her project depending on the students previous training and experience. Students should consult with a professor in their area for detailed arrangements no later than the last day of registration.
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Instructor:
Dimitris Anastassiou
Wikipedia Info -
Instructor:
Keren Bergman
CULPA: 1 Wikipedia h-index: 69 Info -
Instructor:
Shih-Fu Chang
CULPA: 3
Wikipedia
h-index: 122
Info
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Instructor:
Javad Ghaderi
h-index: 17 Info - 1-4 points