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:
David G Vallancourt
CULPA: 28
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.
- T 4:10 p.m.-6:40 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
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
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
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.
- T 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.
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Instructor:
Ahmed Mousa
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.
- T 10:10 a.m.-12:40 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.
- R 10:10 a.m.-12:40 p.m.
- 3 points
Machine Learning for Signals, Informatio
ML FOR SIG, INF
- W 10:10 a.m.-12:40 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
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
Power Management Integrated Circuits
Power Mgmt Integrated Cir
Modern power management integrated circuits (PMIC) design introduced comperhensively. Advanced topics in power management introduced, including linear regulators, digital linear regulators, switch-mode power converters, control schemes for DC-DC converters, compensation methods of DC-DC converters, power losses in DC-DC converters, switched capacitor converters, power converter modeling and simulation, design examples.
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 1:10 p.m.-3:40 p.m.
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Instructor:
Xiang Meng
h-index: 8 Info - 3 points
APPLIED QUANTUM OPTICS
An introduction to fundamental concepts of quantum optics and quantum electrodynamics with an emphasis on applications in nanophotonic devices. The quantization of the electromagnetic field; coherent and squeezed states of light; interaction between light and electrons in the language of quantum electrodynamics (QED); optical resonators and cavity QED; low-threshold lasers; and entangled states of light.
- R 4:10 p.m.-6:40 p.m.
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Instructor:
Xiang Meng
h-index: 8 Info - 3 points
OPTICAL INTERCONNECTS
Introduction to optical interconnects and interconnection networks for digital systems. Fundamental optical interconnects technologies, optical interconnection network design, characterization, and performance evaluation. Enabling photonic technologies including free-space structures, hybrid and monolithic integration platforms for photonic on-chip, chip-to-chip, backplane, and node-to-node interconnects, as well as photonic networks on-chip.
- M 4:10 p.m.-6:40 p.m.
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Instructor:
Keren Bergman
CULPA: 1 Wikipedia h-index: 69 Info - 3 points
Topics in Smart Electric Energy
Battery Systems
Selected advanced topics in smart electric energy. Content varies from year to year.
Topics in Smart Electric Energy
Selected advanced topics in smart electric energy. Content varies from year to year.
- R 4:10 p.m.-6:40 p.m.
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Instructor:
Mohamed Kamaludeen
Info - 3 points
TOPICS DATA-DRIVEN ANAL & COMP
Adv VLSI DA & Methodology
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.
- M 4:10 p.m.-6:40 p.m.
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Instructor:
Matthew M Ziegler
Info - 3 points
TOPICS DATA-DRIVEN ANAL & COMP
GenAI & Modern 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.
- MW 10:10 a.m.-11:25 a.m.
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Instructor:
Micah Goldblum
Info - 3 points
COMPUTER COMMUNICATNS NETWORKS
COMPUTER COMMUNCATION NETWORKS
Analytical approach to the design of (data) communication networks. Necessary tools for performance analysis and design of network protocols and algorithms. Practical engineering applications in layered Internet protocols in Data link layer, Network layer, and Transport layer. Review of relevant aspects of stochastic processes, control, and optimization.
- TR 10:10 a.m.-11:25 a.m.
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Instructor:
Javad Ghaderi
h-index: 17 Info - 3 points
INTERNET ECON, ENG & SOCIETY
Mathematical models, analyses of economics and networking interdependencies in the internet. Topics include microeconomics of pricing and regulations in communications industry, game theory in revenue allocations, ISP settlements, network externalities, two-sided markets. Economic principles in networking and network design, decentralized vs. centralized resource allocation, “price of anarchy,” congestion control. Case studies of topical internet issues. Societal and industry implications of internet evolution.
- MW 11:40 a.m.-12:55 p.m.
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Instructor:
Debasis Mitra
Wikipedia h-index: 61 Info - 3 points
TOPICS IN NETWORKING
TPC:NET VIRTUAL & CLOUD COMPUT
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 4:10 p.m.-6:40 p.m.
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Instructor:
Thomas Woo
Info - 3 points
TOPICS IN NETWORKING
Massive Content Mining&Di
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.
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Instructor:
Anwar I Walid
CULPA: 1 Info - 3 points
TOPICS IN SIGNAL PROCESSING
BIOMEDICAL SIGNAL&IMAGE
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.
- M 10:10 a.m.-12:40 p.m.
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Instructor:
Guido H Jajamovich
Info - 3 points
TOPICS IN SIGNAL PROCESSING
TPC:REINFORCEMENT LEARNING
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-INFORMATION PROCESSING
TPC:BIG DATA ANALYTICS
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: Big Data Analytics.
- F 7 p.m.-9:30 p.m.
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Instructor:
Ching-Yung Lin
h-index: None Info - 3 points
TOPICS-INFORMATION PROCESSING
DATA CENTER PROCESSING
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.
- MW 8:40 a.m.-9:55 a.m.
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Instructor:
Tanvir Ahmed Khan
Info - 3 points
TOPICS-INFORMATION PROCESSING
Learning and Storage
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: Quantum Computing and Communication.
- M 4:10 p.m.-6:40 p.m.
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Instructor:
Alexei Ashikhmin
Info - 3 points
TPCS-ELEC & COMPUT ENGINEERING
Selected topics in electrical and computer engineering. Content varies from year to year, and different topics rotate through the course numbers 6900 to 6909.
- TR 2:40 p.m.-3:55 p.m.
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Instructor:
Savannah Eisner
Info - 3 points