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ELECTRICAL AND SYSTEMS ENGINEERING (E35)  (Dept. Info) Engineering and Applied Science  (Policies) FL2024 E35 ESE 105 Introduction to Electrical and Systems Engineering 4.0 Units Lab Required Details Save  Cancel   My Note:   Description: This course will offer students a rigorous introduction to fundamental mathematical underpinnings of ESE and their relationship to a number of contemporary application areas. Major emphasis will be placed on linear algebra and associated numerical methods, including the use of MATLAB. Topics covered will include vector spaces, linear transformations, matrix manipulations and eigenvalue decomposition. Students will learn how this mathematical theory is enacted in ESE through the completion of four case studies spanning application areas: (i) Dynamical Systems and Control, (ii) Imaging, (iii) Signal Processing, and (iv) Circuits. Attributes: EN: TU 4.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 4:00P-5:20P TBA Sinopoli, Patwari No final 70 15 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. A ----F-- 1:00P-1:50P TBA Sinopoli No final 20 10 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. B ----F-- 2:00P-2:50P TBA Patwari No final 20 2 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. C ----F-- 3:00P-3:50P TBA Sinopoli No final 20 2 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. D ----F-- 4:00P-4:50P Cupples II / L007 Patwari No final 20 1 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. E35 ESE 2180 Linear Algebra and Component Analysis 3.0 Units Details Save  Cancel   My Note:   Description: Linear algebra is the foundation of scientific computing across many disciplines of engineering. This course will introduce the numerical and computational issues that arise from solving large-scale problems, with motivation from data science, machine learning, and signal processing. Topics to be covered include least-squares problems, eigenvalue/eigenvector analysis, singular value decomposition, component analysis, rotation of bases, and concepts of computational complexity and numerical stability. A focus of the class will be studying concepts from signal processing and machine learning such as K-means, Fourier analysis, wavelet analysis, and sampling within the framework of linear algebra. The course will include case studies touching on a broad range of topics including systems science, signals and imaging, devices and circuits, and quantum science/applied physics. Prerequisites: Linear algebra at the level of ESE 105; familiarity with Matlab. Attributes: Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 10:00A-11:20A Simon / 017 Clark Dec 17 2024 6:00PM - 8:00PM 50 27 0 Actions: Books E35 ESE 230 Introduction to Electrical and Electronic Circuits 4.0 Units Lab Required Details Save  Cancel   My Note:   Description: Electrical energy, current, voltage, and circuit elements. Resistors, Ohm's Law, power and energy, magnetic fields and dc motors. Circuit analysis and Kirchhoff's voltage and current laws. Thevenin and Norton transformations and the superposition theorem. Measuring current, voltage, and power using ammeters and voltmeters. Energy and maximum electrical power transfer. Computer simulations of circuits. Reactive circuits, inductors, capacitors, mutual inductance, electrical transformers, energy storage, and energy conservation. RL, RC and RLC circuit transient responses, biological cell action potentials due to Na and K ions. AC circuits, complex impedance, RMS current and voltage. Electrical signal amplifiers and basic operational amplifier circuits. Inverting, non-inverting, and difference amplifiers. Voltage gain, current gain, input impedance, and output impedance. Weekly laboratory exercises related to the lectures are an essential part of the course. Prerequisite: L31 Phys192 and 192L Corequisite: L24 Math 217 Attributes: EN: TU 4.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Annually / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 1:00P-2:20P TBA Nussinov Exam last day of class 72 53 0 Desc: Discussion sections will be offered on Fridays with times to be determined. Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. A --W---- 1:00P-2:20P Urbauer / 208 Nussinov Default - none 0 0 31 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. Waits managed by dept. B --W---- 2:30P-3:50P Urbauer / 208 Nussinov Default - none 0 0 15 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. Waits managed by dept. C ---R--- 2:30P-3:50P Urbauer / 208 Nussinov Default - none 24 7 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. E35 ESE 260 Introduction to Digital Logic and Computer Design 3.0 Units Details Save  Cancel   My Note:   Description: Introduction to design methods for digital logic and fundamentals of computer architecture. Students learn to use hardware description languages and computer-aided design tools (simulation, circuit synthesis) and apply them to the design of a variety of digital circuits. Coverage includes both combinational and sequential circuits, ranging in complexity from basic arithmetic circuits to a simple processor. Students learn about the underlying causes of circuit delays and timing issues in sequential circuits (setup and hold times, minimum clock period analysis, metastability). They also study how logic minimization is done, learn to make basic design trade-offs (complexity vs. performance), and how look ahead techniques can be used to speed circuit operation. Coverage also includes the operation of a programmable processor, common methods for enhancing processor performance and the design of memory systems. Prerequisites: CSE 131 Attributes: EN: TU Instruction Type: Classroom instruction Grade Options: CP Fees: Course Type: Ident Same As: E81 260M  E81 505N Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 2:30P-3:50P TBA Siever No final 0 0 120 Desc: Learn about how this course manages its waitlist here: https://faq.cse.wustl.edu/#why-am-i-on-a-waitlist-how-are-waitlists-managed-what-are-my-chances-of-enrollment-what-is-managed-by-waitlist Actions: Books Waits managed by dept. E35 ESE 2971 Introduction to Research in ESE 2.0 Units Details Save  Cancel   My Note:   Description: This course provides students with an introductory experience with research in ESE. This is a mentored experience and requires the agreement of an ESE faculty member to serve in a mentorship role. Students must identify a mentor and obtain their agreement before registering for this course. Activities are to be designed by the student in conjunction with the faculty mentor, and will amount to 4-6 hours of commitment per week. The research activities will enable the student to gain a deeper understanding of ongoing research related to the mentor's field, or in an area mutually agreed upon by the mentor and the student. The student may also have an opportunity to actively participate in ongoing research activities, such as through assistance of graduate students or postdoctoral associates. Because activities may be unstructured, this course is will require strong time-management skills and self-discipline. The final grade will be determined on the basis of a set of deliverables that are agreed upon by the student and faculty member. Attributes: Instruction Type: Independent study, tutorial, or other Grade Options: CP Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 TBA TBA Lawrence Default - none 0 0 0 Actions: Books Waits managed by dept. E35 ESE 3050 Special Topics in Robotics: Practicum in Robotic Systems Design 3.0 Units Details Save  Cancel   My Note:   Description: This is an exciting hands-on course where teams of students (in groups of 4-6) will put a broad range of their engineering skills to use by designing, constructing, and debugging a complex electro-mechanical robotic system. The robotic system will be targeted at some proposed real-world application. Each team will engineer and implement their own solution to the problem. This course is designed to teach students how to apply their theory-based classroom engineering knowledge by exposing students to the design/test/debug/iterate process needed to develop a working integrated system. Some of the topics/skills experienced in the class will include feedback control, real sensor/actuator implementation, circuit design/layout, soldering, asynchronous programming, project management, Design-For-Manufacturability, and more. Students will use the WUSTL Maker Space in this class to learn other valuable hands-on skills (e.g. CAD, CNC machining, 3D printing, laser cutting, etc.). This course will consist of one weekly lecture and a weekly lab component. Course Prerequisites: ESE205 or instructor permission Attributes: EN: TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 4:00P-5:50P Jubel / 138 Mell Default - none 24 24 2 Actions: Books E35 ESE 3090 Special Topics in Systems Engineering: Modeling and Design of Social Choice Systems 3.0 Units Details Save  Cancel   My Note:   Description: Social choice systems are all around us, from how we decide to split the check to who becomes president. This course introduces many conceptual and computational problems in the study of systems of social choice and offers a variety of tools to understand them. We will consider both micro and macro social choice systems; for the latter drawing on modern statistical techniques to understand (and reframe) questions like "what is a fair map of congressional districts?" In order to address modeling and design challenges in social choice systems we will explore mathematical and software tools such as game theory, linear optimization, Monte Carlo / MCMC methods, and geographical data representation in Python. Prerequisites: ESE 105, or Math 309, or working knowledge of linear algebra and scientific computing, or permission of instructor. Attributes: Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 2:30P-3:50P TBA Wormleighton No final 30 11 0 Actions: Books E35 ESE 318 Engineering Mathematics A 3.0 Units Details Save  Cancel   My Note:   Description: Laplace transforms; matrix algebra; vector spaces; eigenvalues and eigenvectors; vector differential calculus and vector integral calculus in three dimensions. Prerequisites: Math 233 and Math 217 or their equivalents. Attributes: Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 10:00A-11:20A TBA Brennan Dec 16 2024 10:30AM - 12:30PM 35 35 27 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. 02 -T-R--- 11:30A-12:50P TBA Zhu Dec 16 2024 1:00PM - 3:00PM 35 28 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. E35 ESE 319 Engineering Mathematics B 3.0 Units Details Save  Cancel   My Note:   Description: Power series and Frobenius series solutions of differential equations; Legendre's equation; Bessel's equation; Fourier series and Fourier transforms; Sturm-Liouville theory; solutions of partial differential equations; wave and heat equations. Prerequisites: Math 233 and Math 217 or their equivalents. Attributes: Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 10:00A-11:20A TBA Hasting Dec 17 2024 6:00PM - 8:00PM 30 23 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. 02 -T-R--- 2:30P-3:50P Lopata Hall / 101 Brennan Dec 18 2024 3:30PM - 5:30PM 30 30 21 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. E35 ESE 326 Probability and Statistics for Engineering 3.0 Units Details Save  Cancel   My Note:   Description: Study of probability and statistics together with engineering applications. Probability and statistics: random variables, distribution functions, density functions, expectations, means, variances, combinatorial probability, geometric probability, normal random variables, joint distribution, independence, correlation, conditional probability, Bayes theorem, the law of large numbers, the central limit theorem. Applications: reliability, quality control, acceptance sampling, linear regression, design and analysis of experiments, estimation, hypothesis testing. Examples are taken from engineering applications. Prerequisites: Math 233 or equivalent. Attributes: EN: TU 1.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Every Semester / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 10:00A-11:20A Whitaker / 100 Zhang Dec 16 2024 10:30AM - 12:30PM 115 58 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. E35 ESE 330 Engineering Electromagnetics Principles 3.0 Units Details Save  Cancel   My Note:   Description: Electromagnetic theory as applied to electrical engineering: vector calculus; electrostatics and magnetostatics; Maxwell's equations, including Poynting's theorem and boundary conditions; uniform plane-wave propagation; transmission lines, TEM modes, including treatment of general lossless lines, and pulse propagation; introduction to guided waves; introduction to radiation and scattering concepts. Prerequisites: Physics 118A and ESE 318 En Math A. Co-requisite: ESE 319 En Math B. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Annually / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 2:30P-3:50P TBA Lawrence Dec 16 2024 3:30PM - 5:30PM 35 27 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. E35 ESE 331 Electronics Laboratory 3.0 Units Lab Required Details Save  Cancel   My Note:   Description: Laboratory exercises provide students with a combination of hands-on experience involving electronic circuits. Students will use a variety of real instruments, analysis techniques and circuit simulation tools to summarize measurement results in written reports that clearly communicate laboratory results. A sequence of lab experiments provide hands-on experience in: properties of diodes and transistors, realistic operational amplifier characteristics, grounding and shielding techniques, signal analysis, and op amp based active filter design and characterization. Students will gain experience working with: sampling oscilloscopes to make measurements in the time and frequency domains, signal generators, digital multimeter and frequency measurements, and in creating circuits and making connections on contemporary circuit boards. The course concludes with a hands-on project to design, demonstrate and document the design of an electronic component. Prerequisite: ESE 232 Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Annually / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T----- 10:00A-11:20A Urbauer / 115 Wang Dec 17 2024 6:00PM - 8:00PM 24 19 0 Actions: Books A ---R--- 10:00A-12:50P Urbauer / 115 Wang No final 24 19 0 Actions: Books Waits Not Allowed E35 ESE 359 Signals, Data and Equity 3.0 Units Details Save  Cancel   My Note:   Description: This course introduces the design of classification and estimation systems for equity, that is, with the goal of reducing the inequities of racism, sexism, xenophobia, ableism, and other systems of oppression. Systems which change the allocation of resources among people can increase inequity due to their inputs, the systems themselves, or how the systems interact in the context in which they are deployed. This course presents background in power and oppression, to help predict how new technological and societal systems might interact, and when they might confront or reinforce existing power systems. Measurement theory, the study of the mismatch between a system's intended measure and the data it actually uses, is covered. Multiple example sensing and classification systems which operate on people (e.g., optical, audio, and text sensors) are covered by implementing algorithms and quantifying inequitable outputs. Prerequisite: ESE 105 or 217A or CSE 417T. Background readings will be available. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: E81 359A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 10:00A-11:20A McDonnell / 361 Wormleighton No final 25 33 12 Actions: Books E35 ESE 362 Computer Architecture 3.0 Units Details Save  Cancel   My Note:   Description: This course explores the interaction and design philosophy of hardware and software for digital computer systems. Topics include: Processor architecture, Instruction Set Architecture, Assembly Language, memory hierarchy design, I/O considerations, and a comparison of computer architectures. Prerequisite: CSE 260M. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CP Fees: Course Type: Ident Same As: E81 362M Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 2:30P-3:50P TBA Chamberlain Dec 18 2024 3:30PM - 5:30PM 0 0 24 Desc: Prerequisite of CSE 260M or instructor approval of equivalent experience is required. Learn more about waitlists here: https://faq.cse.wustl.edu/#why-am-i-on-a-waitlist-how-are-waitlists-managed-what-are-my-chances-of-enrollment-what-is-managed-by-waitlist Actions: Books Waits managed by dept. E35 ESE 400 Independent Study Var. Units (max = 3.0) Details Save  Cancel   My Note:   Description: Opportunities to acquire experience outside the classroom setting and to work closely with individual members of the faculty. A final report must be submitted to the department. Not open to first-year or graduate students. Consult adviser. Hours and credit to be arranged. --- In order to register for this course, please fill out the ESE Research/Independent Study Registration Form. Attributes: Instruction Type: Independent study, tutorial, or other Grade Options: CP Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 TBA TBA Feher Default - none 0 0 0 Actions: Books Waits managed by dept. 02 TBA TBA Richter Default - none 0 0 0 Actions: Books Waits managed by dept. 03 TBA TBA Ching Default - none 0 0 0 Actions: Books Waits managed by dept. 04 TBA TBA Zeng Default - none 0 0 0 Actions: Books Waits managed by dept. 07 TBA TBA Lew Default - none 0 0 0 Actions: Books Waits managed by dept. 08 TBA TBA Kamilov Default - none 0 0 0 Actions: Books Waits managed by dept. 10 TBA TBA Min Default - none 0 0 0 Actions: Books Waits managed by dept. 13 TBA TBA O'Sullivan Default - none 0 0 0 Actions: Books Waits managed by dept. 16 TBA TBA Trobaugh Default - none 0 0 0 Actions: Books Waits managed by dept. 28 TBA TBA Yang Default - none 0 0 0 Actions: Books Waits managed by dept. 29 TBA TBA Li Default - none 0 0 0 Actions: Books Waits managed by dept. 30 TBA TBA Shen Default - none 0 0 0 Actions: Books Waits managed by dept. 31 TBA TBA Wang Default - none 0 0 0 Actions: Books Waits managed by dept. 32 TBA TBA Kurenok Default - none 0 0 0 Actions: Books Waits managed by dept. 34 TBA TBA Mell Default - none 0 0 0 Actions: Books Waits managed by dept. 37 TBA TBA Chakrabartty Default - none 0 0 0 Actions: Books Waits managed by dept. 38 TBA TBA Bhan Default - none 0 0 0 Actions: Books Waits managed by dept. 39 TBA TBA La Rosa Default - none 0 0 0 Actions: Books Waits managed by dept. 40 TBA TBA Sinopoli Default - none 0 0 0 Actions: Books Waits managed by dept. 41 TBA TBA Wang, Dorothy Default - none 0 0 0 Actions: Books Waits managed by dept. E35 ESE 4031 Optimization for Engineered Planning, Decisions and Operations 3.0 Units Details Save  Cancel   My Note:   Description: The goal of the course is to introduce students to discrete optimization and decision-making methods as well as their application domains ranging from finance to robotics. This course will cover linear programming, integer programming, and dynamic programming from theoretical and application perspectives. Special emphasis will be given on modeling real-world problems as optimization problems as well as on designing techniques to address them. The use of methods will be demonstrated on numerous concrete examples (e.g., scheduling, operation management, robot planning and control) solved using MatLab or Python. Prerequisites: E35 ESE 105 (or both E81 CSE 131 and L24 Math 309), L24 Math 217; E35 ESE 326; or permission of the instructor. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 2:30P-3:50P Mallinckrodt / 302 Kantaros Dec 16 2024 3:30PM - 5:30PM 65 11 0 Actions: Books E35 ESE 415 Optimization 3.0 Units Details Save  Cancel   My Note:   Description: Optimization problems with and without constraints. The projection theorem. Notions of convexity. Lagrange multipliers and Kuhn-Tucker-type conditions. Duality. Computational methods. Applications of optimization in engineering. Prerequisites: Solid understanding of multivariable calculus notions, including gradients. Solid understanding of linear algebraic concepts, including eigen decomposition (eigenvalues & eigenvectors), matrix algebraic operations, and properties of symmetric matrices. Prerequisites: CSE 131, Math 309 and ESE 318 or permission of instructor. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 11:30A-12:50P Brauer Hall / 012 Zeng Dec 17 2024 10:30AM - 12:30PM 70 43 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. E35 ESE 417 Introduction to Machine Learning and Pattern Classification 3.0 Units Details Save  Cancel   My Note:   Description: This course provides a broad introduction to machine learning and statistical pattern classification. Students will study theoretical foundations of learning and several important supervised and unsupervised machine learning methods and algorithms including linear model of regression and classification, logistic regression, Bayesian learning methods, neural networks, nearest neighbor method, support vector machines methods, clustering methods and principal component analysis. Students will also learn to use Python programming language to implement learned models and methods to solve pattern classification problems. Pre-requisites: ESE326, Math 233, Python Programming Experience Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 11:30A-12:50P TBA Zhang Dec 16 2024 1:00PM - 3:00PM 100 56 0 Actions: Books E35 ESE 419 Special Topics in Optimization and Learning: Practicum in Deep Learning 3.0 Units Details Save  Cancel   My Note:   Description: Description: Deep learning has recently become the dominant paradigm in machine learning and artificial intelligence. It has wide-ranging applications in engineering and science, such as computer vision, natural language processing, sequence modeling and physical system simulation. This course is a practical introduction to deep neural networks (DNN) within the broader context of machine learning. Topics to be covered include: practical review of classical ML methods (PCA, logistic regression, naive Bayes, KNN, SVM); feedforward, convolutional and recurrent neural networks; optimization for training DNN; generalization, validation and hyperparameter tuning; overfitting, underfitting and bias-variance trade-off; classification, clustering and regression; representation learning; sequence models; generative models. Students will experiment with architectures and algorithms using Keras, TensorFlow and Wolfram Language. Class time will be allocated approximately equally between structured instruction and group discussions plus practical exercises. Students will collaborate in groups of 5 on a semester-long project. Students can propose their own projects or choose from a list provided by the instructor. Projects should be similar to real-world problems and include a value proposition. Progress will be evaluated throughout the semester. The course will include a final report, and a presentation open to the academic community. Prerequisites: ESE 326, ESE 415, ESE 417 (or CSE 417), experience in programming in Python or Wolfram Language. Second-year graduate or senior undergraduate standing. Enrollment for Fall 2024 is by permission of the instructor only subject to successful assessment of the prerequisites. Waits will be managed by department. Attributes: EN: TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 11:30A-12:50P TBA Tunay No final 0 0 6 Actions: Books Waits managed by dept. A ----F-- 4:00P-4:50P TBA Tunay No final 0 0 0 Actions: Books Waits managed by dept. E35 ESE 427 Financial Mathematics 3.0 Units Details Save  Cancel   My Note:   Description: This course is a self-contained introduction to financial mathematics at the undergraduate level. Topics to be covered include pricing of the financial instruments such as options, forwards, futures and their derivatives along with basic hedging techniques and portfolio optimization strategies. The emphasis is put on using of discrete, mostly binary models. The general, continuous case including the concepts of Brownian motion, stochastic integral, and stochastic differential equations, is explained from intuitive and practical point of view. Among major results discussed are the Arbitrage Theorem and Black-Scholes differential equations and their solutions. Prerequisites: ESE 326 or the consent of the instructor. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 1:00P-2:20P Lopata Hall / 101 Kurenok Dec 17 2024 1:00PM - 3:00PM 80 51 0 Actions: Books E35 ESE 4301 Quantum Mechanics for Engineers 3.0 Units Details Save  Cancel   My Note:   Description: This course provides an accessible introduction to quantum mechanics and quantum engineering for undergraduate students. Examples are drawn from practical areas of applications of quantum engineering. This course covers the following topics and examples: quantum mechanics and nano-technology, Schrodinger's equation, electrons transport in various potential profiles, quantum dots and defects, harmonic oscillator, nano-mechanical oscillator and quantum LC circuit, Stark effect in semiconductors, Bloch theorem, crystal and band structures, Kronig-Penney and tight-binding models, semiclassical and quantum descriptions of light-atom interactions, spontaneous and stimulated emissions, quantum flip-flops, approximate methods in quantum mechanics, spin, quantum gyroscope, spin transistor, and many-particle quantum mechanics for bosons and fermions. In addition, we will also discuss the physical foundations and applications in quantum information science (quantum computation, communication, and cryptography). Prerequisites: Simple differential equations and matrix algebra, at the level of ESE 318/319 Engineering Mathematics A/B or equivalent. Familiarity with a modern scientific computing software package (e.g., Matlab, Mathematica, or any of your favorites) Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 1:00P-2:20P TBA Lew Dec 18 2024 1:00PM - 3:00PM 25 9 0 Actions: Books E35 ESE 433 Radio Frequency and Microwave Technology for Wireless Systems 3.0 Units Details Save  Cancel   My Note:   Description: Focus is on the components and associated techniques employed to implement analog and digital radio frequency (RF) and microwave (MW) transceivers for wireless applications, including: cell phones; pagers; wireless local area networks; global positioning satellite based devices; and RF identification systems. A brief overview of system-level considerations is provided, including modulation and detection approaches for analog and digital systems; multiple-access techniques and wireless standards; and transceiver architectures. Focus is on RF and MW: transmission lines; filter design; active component modeling; matching and biasing networks; amplifier design; and mixer design. Prerequisite: ESE 330. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 4:00P-5:20P TBA Nagulu Dec 13 2024 6:00PM - 8:00PM 25 10 0 Actions: Books E35 ESE 434 Solid State Power Circuits and Applications 3.0 Units Details Save  Cancel   My Note:   Description: Study of the strategies and applications power control using solid-state semiconductor devices. Survey of generic power electronic converters. Applications to power supplies, motor drives, and consumer electronics. Introduction to power diodes, thyristors, and MOSFETs. Prerequisites: ESE 232, 351. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Annually / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 4:00P-5:20P TBA Davies No final 15 3 0 Desc: Same as T15-4340. Actions: Books Waits Not Allowed E35 ESE 435 Electrical Energy Laboratory 3.0 Units Lab Required Details Save  Cancel   My Note:   Description: Experimental studies of principles important in modern electrical energy systems. Topics include: AC power measurements, electric lighting, photovoltaic cells and arrays, batteries, DC-DC and DC-AC converters, brushed and brushless DC motors and three-phase circuits. Each experiment requires analysis, simulation with MultiSim, and measurement via LabVIEW and the Elvis II platform. Prerequisites: ESE 230 and 351 Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T----- 5:30P-7:00P Urbauer / 115 Abdelkamel Paper/Project/TakeHome 6 4 0 Actions: Books A -T----- 7:00P-10:00P Urbauer / 115 Abdelkamel Default - none 6 4 0 Actions: Books E35 ESE 436 Semiconductor Devices 3.0 Units Details Save  Cancel   My Note:   Description: This course covers the fundamentals of semiconductor physics and operation principles of modern solid-state devices such as homo- or hetero-junction diodes, solar cells, inorganic/organic light-emitting diodes, bipolar junction transistors, and metal-oxide-semiconductor field-effect transistors. These devices form the basis for today's semiconductor and integrated circuit industry. In additional to device physics, semiconductor device fabrication processes, new materials, and novel device structures will also be briefly introduced. At the end of this course, students will be able to understand the characteristics, operation, limitations and challenges faced by state-of-the-art semiconductor devices. This course will be particularly useful for students who wish to develop careers in the semiconductor industry. Prerequisite: ESE 232 Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 10:00A-11:20A TBA Wang Dec 16 2024 10:30AM - 12:30PM 30 22 0 Actions: Books E35 ESE 441 Control Systems 3.0 Units Details Save  Cancel   My Note:   Description: Introduction to the theory and practice of automatic control for dynamical systems. Dynamical systems as models for physical and observed phenomena. Mathematical representation of dynamical systems, such as state-space differential and difference equations, transfer functions, and block diagrams. Analysis of the time evolution of a system in response to control inputs, steady-state and transient responses, equilibrium points and their stability. Control via linear state feedback, and estimation using Luenberger observers. Relating the time response of a system to its frequency response, including Bode and Nyquist plots. Input-output stability and its relation to the stability of equilibrium points. Simple frequency-based controllers, such as PID and lead-lag compensators. Exercise involving the use of MATLAB/Simulink (or equivalent) to simulate and analyze systems. Prerequisites: CSE 131, and either ESE 351 or MEMS 4310. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Annually / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 4:00P-5:20P Lopata Hall / 101 Ching Dec 13 2024 6:00PM - 8:00PM 65 42 0 Actions: Books E35 ESE 444 Sensors and Actuators 3.0 Units Details Save  Cancel   My Note:   Description: The course provide engineering students with basic understanding of two of the main components of any modern electrical or electromechanical system; sensors as inputs and actuators as outputs. The covered topics include transfer functions, frequency responses and feedback control. Component matching and bandwidth issues. Performance specification and analysis, Sensors: analog and digital motion sensors, optical sensors, temperature sensors, magnetic and electromagnetic sensors, acoustic sensors, chemical sensors, radiation sensors, torque, force and tactile sensors. Actuators: stepper motors, DC and AC motors, hydraulic actuators, magnet and electromagnetic actuators, acoustic actuators. Introduction to interfacing methods: bridge circuits, A/D and D/A converters, microcontrollers. This course is useful for those students interested in control engineering, robotics and systems engineering. Prerequisites: one of the following 4 conditions:(1) ESE 230, ESE 351 (corequisite); (2) ESE 230, ESE 318 and MEMS 255; (3) ESE 351 or MEMS 4310; (4) permission of instructor. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Every 1 or 2 Years / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 5:30P-7:00P TBA Becnel Dec 17 2024 6:00PM - 8:00PM 36 14 0 Desc: Occasional labs on Thursdays in Urbauer 115. Actions: Books E35 ESE 4480 Control Systems Design Laboratory 3.0 Units Details Save  Cancel   My Note:   Description: Experimental study of real and simulated systems and their control. Modeling, identification, model validation and control of systems, including noise effects, using a two-link robotic manipulator as experimental testbed. Other topics include: mathematical modeling of robotic systems; nonlinear and linearized models; input-output and state-space techniques; model validation and simulation; stabilization using linear and nonlinear control techniques. Prerequisite: ESE 351 or MEMS 4310. Corequisite or Prerequisite: ESE 441 or MEMS 4301. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 11:00A-12:50P Green Hall / 1157 Mell No final 24 16 0 Actions: Books E35 ESE 4481 Autonomous Aerial Vehicle Control Laboratory 3.0 Units Details Save  Cancel   My Note:   Description: Integration of dynamical systems and control engineering principles toward the manipulation of a quadrotor unmanned aerial vehicle (UAV), sometimes referred to as a drone. Students will analytically transform a nonlinear description of the UAV system used for dynamic simulation into a conventional, linear state space system. Students will use key control engineering concepts, including system identification, state estimation and control synthesis, in order to command their UAV's to hover, climb and orbit. In addition to principles of estimation and identification, students will also learn about the theory of guidance and navigation, with projects such as flight planning and execution, collision avoidance, and competitive or cooperative tasks, e.g., formation flight. The overall objective is to expose students to the fusion of control, estimation, and identification techniques that are fundamental to systems theory. Prerequisite: ESE 441 and knowledge of a programming language, or permission of instructor. Attributes: EN: BME T2, TU 3.00 Instruction Type: Online Hybrid Course Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 6:00P-8:00P Green Hall / 1157 Bhan No final 24 2 0 Desc: Lectures will be held via zoom with breakout sessions to coordinate with lab groups. Assigned class space, Green 0161, will be available for students to test-fly drones. The space will be reserved individually on an as needed basis. Actions: Books E35 ESE 465 Digital Systems Laboratory 3.0 Units Lab Required Details Save  Cancel   My Note:   Description: Hardware/software co-design; processor interfacing; procedures for reliable digital design, both combinational and sequential; understanding manufacturers' specifications; use of test equipment. Several single-period laboratory exercises, several design projects, and application of microprocessors in digital design. One lecture and one laboratory period a week. Prerequisites: ESE 260 Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: E81 465M Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T----- 1:00P-2:20P Urbauer / 115 Richter Dec 17 2024 1:00PM - 3:00PM 24 10 0 Actions: Books A ---R--- 1:00P-3:50P Urbauer / 115 Richter Default - none 24 10 0 Actions: Books E35 ESE 467 Embedded Computing Systems 3.0 Units Details Save  Cancel   My Note:   Description: This course introduces the issues, challenges, and methods for designing embedded computing systems -- systems designed to serve a particular application and which incorporate the use of digital processing devices. Examples of embedded systems include cellular phones, appliances, game consoles, automobiles, and drones. Emphasis is given to aspects of design that are distinct to embedded systems. The course examines hardware, software, and system-level design. Hardware topics include microcontrollers, digital signal processors, memory hierarchy, and I/O. Software issues include languages, run-time environments, and program analysis. System-level topics include real-time operating systems, scheduling, power management, and wireless sensor networks. Students will perform a course project on a real embedded system testbed. Prerequisites: CSE 260M (and either CSE 132 or ESE 205). Attributes: EN: TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Ident Same As: E81 467S Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 5:30P-7:00P TBA Ivanovich Paper/Project/TakeHome 30 20 0 Actions: Books E35 ESE 482 Digital Signal Processing 3.0 Units Details Save  Cancel   My Note:   Description: Introduction to analysis and synthesis of discrete-time linear time-invariant (LTI) systems. Discrete-time convolution, discrete-time Fourier transform, z-transform, rational function descriptions of discrete-time LTI systems. Sampling, analog-to-digital conversion, and digital processing of analog signals. Techniques for the design of finite impulse response (FIR) and infinite impulse response (IIR) digital filters. Hardware implementation of digital filters and finite-register effects. The Discrete Fourier Transform and the Fast Fourier Transform (FFT) algorithm. Prerequisite: ESE 351. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Annually / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 5:30P-7:00P Jubel / 121 Sutton Dec 16 2024 6:00PM - 8:00PM 27 20 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. E35 ESE 488 Signals and Imaging Laboratory 3.0 Units Details Save  Cancel   My Note:   Description: Hands-on design and analysis that motivates ESE research and courses in signals, communications and imaging. Projects in digital audio signal processing, communication systems, and computational imaging and inverse problems in optics. Prerequisite: ESE 351. Attributes: EN: BME T2, TU Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Annually / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 1:00P-2:20P TBA Trobaugh, Lew Paper/Project/TakeHome 0 0 18 Desc: Department to manage waitlist, max of 10 students for pilot offering Actions: Books Waits managed by dept. E35 ESE 497 Undergraduate Research Var. Units (max = 3.0) Details Save  Cancel   My Note:   Description: Undergraduate research under the supervision of a faculty member. The scope and depth of the research must be approved by the faculty member prior to enrollment. Final deliverables include a poster presentation at a departmental event, submission of the poster in electronic form for archiving, and written documentation at the discretion of the instructor. Attributes: Instruction Type: Independent study, tutorial, or other Grade Options: CP Fees: Course Type: Home Same As: N/A Frequency: Every Semester / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 03 TBA TBA Ching Default - none 0 0 1 Actions: Books Waits managed by dept. 04 TBA TBA Richter Default - none 0 0 0 Actions: Books Waits managed by dept. 07 TBA TBA Lew Default - none 0 0 0 Actions: Books Waits managed by dept. 08 TBA TBA Kamilov Default - none 0 0 0 Actions: Books Waits managed by dept. 13 TBA TBA O'Sullivan Default - none 0 0 0 Actions: Books Waits managed by dept. 14 TBA TBA Zhou Default - none 0 0 0 Actions: Books Waits managed by dept. 21 TBA TBA Kantaros Default - none 0 0 0 Actions: Books Waits managed by dept. 28 TBA TBA Yang Default - none 0 0 0 Actions: Books Waits managed by dept. 29 TBA TBA Li Default - none 0 0 0 Actions: Books Waits managed by dept. 30 TBA TBA Shen Default - none 0 0 0 Actions: Books Waits managed by dept. 31 TBA TBA Wang Default - none 0 0 0 Actions: Books Waits managed by dept. 32 TBA TBA Kurenok Default - none 0 0 0 Actions: Books Waits managed by dept. 34 TBA TBA Mell Default - none 0 0 0 Actions: Books Waits managed by dept. 36 TBA TBA Murch Default - none 0 0 0 Actions: Books Waits managed by dept. 37 TBA TBA Chakrabartty Default - none 0 0 0 Actions: Books Waits managed by dept. 38 TBA TBA Patwari Default - none 0 0 0 Actions: Books Waits managed by dept. 39 TBA TBA Wang Default - none 0 0 0 Actions: Books Waits managed by dept. 40 TBA TBA Lawrence Default - none 0 0 0 Actions: Books Waits managed by dept. 41 TBA TBA Bae Default - none 0 0 0 Actions: Books Waits managed by dept. 42 TBA TBA Nagulu Default - none 0 0 0 Actions: Books Waits managed by dept. 43 TBA TBA Trobaugh Default - none 0 0 1 Actions: Books Waits managed by dept. 44 TBA TBA Sinopoli Default - none 0 0 0 Actions: Books Waits managed by dept. 45 TBA TBA Hu Default - none 0 0 0 Actions: Books Waits managed by dept. E35 ESE 4971 Honors Thesis Research 4.0 Units Details Save  Cancel   My Note:   Description: This is the premier research experience for students in ESE, offering a challenging but rewarding opportunity for committed students to work at the cutting edge of engineering research. This is a mentored experience and requires the agreement of an ESE faculty member to serve in a mentorship role. To register for this course, students must obtain the nomination of two faculty members, including their proposed mentor. Nomination must reflect strong academic preparation, interest in research and ability to manage time and work independently. During this course, students will work within their mentor's research group or laboratory to pursue one or more specific research aims. Research is expected to result in a podium presentation and a thesis document that will be archived. Students completing honors thesis will participate in a departmental recognition event. Attributes: Instruction Type: Independent study, tutorial, or other Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Every Semester / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 TBA TBA Lew No final 0 0 0 Actions: Books Waits managed by dept. E35 ESE 498 Electrical Engineering Capstone Design Projects 3.0 Units Details Save  Cancel   My Note:   Description: Capstone design project supervised by the course instructor. The project must use the theory, techniques, and concepts of the student's major: electrical engineering or systems science & engineering. The solution of a real technological or societal problem is carried through completely, starting from the stage of initial specification, proceeding with the application of engineering methods, and terminating with an actual solution. Collaboration with a client, typically either an engineer or supervisor from local industry or a professor or researcher in university laboratories, is encouraged. A proposal, an interim progress update, and a final report are required, each in the forms of a written document and oral presentation, as well as a Web page on the project. Weekly progress reports and meetings with the instructor are also required. Prerequisite: ESE senior standing and instructor's consent. Note: this course will meet at the scheduled time only during select weeks. If you cannot attend at that time, you may still register for the course. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 ----F-- 2:00P-3:50P TBA Wang No final 0 0 14 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. Waits managed by dept. E35 ESE 499 Systems Science and Engineering Capstone Design Project 3.0 Units Details Save  Cancel   My Note:   Description: Capstone design project supervised by the course instructor. The project must use the theory, techniques, and concepts of the student's major: electrical engineering or systems science & engineering. The solution of a real technological or societal problem is carried through completely, starting from the stage of initial specification, proceeding with the application of engineering methods, and terminating with an actual solution. Collaboration with a client, typically either an engineer or supervisor from local industry or a professor or researcher in university laboratories, is encouraged. A proposal, an interim progress update, and a final report are required, each in the forms of a written document and oral presentation, as well as a Web page on the project. Weekly progress reports and meetings with the instructor are also required. Prerequisite: ESE senior standing and instructor's consent. Note: this course will meet at the scheduled time only during select weeks. If you cannot attend at that time, you may still register for the course. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Every Semester / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 ----F-- 2:00P-3:50P TBA Wang No final 0 0 4 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. Waits managed by dept. E35 ESE 500 Independent Study Var. Units (max = 3.0) Details Save  Cancel   My Note:   Description: Opportunities to acquire experience outside the classroom setting and to work closely with individual members of the faculty. A final report must be submitted to the department. Prerequisite: Students must have the ESE Research/Independent Study Registration Form approved by the department. Attributes: Instruction Type: Independent study, tutorial, or other Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 03 TBA TBA Ching No final 0 0 0 Actions: Books Waits managed by dept. 04 TBA TBA Patwari No final 0 0 0 Actions: Books Waits managed by dept. 05 TBA TBA Feher No final 0 0 0 Actions: Books Waits managed by dept. 07 TBA TBA Lew No final 0 0 0 Actions: Books Waits managed by dept. 08 TBA TBA Kamilov No final 0 0 0 Actions: Books Waits managed by dept. 13 TBA TBA O'Sullivan No final 0 0 0 Actions: Books Waits managed by dept. 14 TBA TBA Wang No final 0 0 0 Actions: Books Waits managed by dept. 27 TBA TBA Nehorai No final 0 0 0 Actions: Books Waits managed by dept. 28 TBA TBA Yang No final 0 0 0 Actions: Books Waits managed by dept. 29 TBA TBA Li No final 0 0 0 Actions: Books Waits managed by dept. 30 TBA TBA Shen No final 0 0 0 Actions: Books Waits managed by dept. 31 TBA TBA Wang No final 0 0 0 Actions: Books Waits managed by dept. 32 TBA TBA Kurenok No final 0 0 0 Actions: Books Waits managed by dept. 34 TBA TBA Mell No final 0 0 0 Actions: Books Waits managed by dept. 36 TBA TBA Culver No final 0 0 0 Actions: Books Waits managed by dept. 37 TBA TBA Chakrabartty No final 0 0 0 Actions: Books Waits managed by dept. 38 TBA TBA Murch No final 0 0 0 Actions: Books Waits managed by dept. 39 TBA TBA Nagulu No final 0 0 0 Actions: Books Waits managed by dept. 40 TBA TBA Sinopoli No final 0 0 0 Actions: Books Waits managed by dept. 41 TBA TBA Hu No final 0 0 0 Actions: Books Waits managed by dept. 42 TBA TBA Lu No final 0 0 0 Actions: Books Waits managed by dept. 43 TBA TBA Jacobs No final 0 0 0 Actions: Books Waits managed by dept. E35 ESE 5001 Research Rotation for ESE Masters Students 3.0 Units Details Save  Cancel   My Note:   Description: Masters students in Electrical and Systems Engineering may complete a rotation their first semester with research mentors acceptable to the Department. The rotations must be mutually agreeable to both the student and faculty member. The grade will be assigned based on a written report from the rotation. The rotation allows students to sample different research projects and laboratory working environments, to enable matching masters students and research mentors with whom they will carry out thesis research. Attributes: Instruction Type: Dissertation/Research Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 TBA TBA Feher Default - none 0 0 1 Actions: Books Waits managed by dept. E35 ESE 501 Mathematics of Modern Engineering I 3.0 Units Details Save  Cancel   My Note:   Description: Matrix algebra: systems of linear equations, vector spaces, linear independence and orthogonality in vector spaces, eigenvectors and eigenvalues; Vector calculus: gradient, divergence, curl, line and surface integrals, theorems of Green, Stokes, and Gauss; Elements of Fourier analysis and its applications to solving some classical partial differential equations, heat, wave, and Laplace equation. Prerequisite: ESE 318 and ESE 319 or equivalent or consent of instructor. This course will not count toward the ESE doctoral program. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Annually / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 4:00P-5:20P TBA Kurenok Dec 13 2024 6:00PM - 8:00PM 65 9 0 Actions: Books E35 ESE 513 Large-Scale Optimization for Data Science 3.0 Units Details Save  Cancel   My Note:   Description: Large-scale optimization is an essential component of modern data science, artificial intelligence, and machine learning. This graduate-level course rigorously introduces optimization methods that are suitable for large-scale problems arising in these areas. We will learn several algorithms suitable for both smooth and nonsmooth optimization, including gradient methods, proximal methods, mirror descent, Nesterov's acceleration, ADMM, quasi-Newton methods, stochastic optimization, variance reduction, as well as distributed optimization. Throughout the class, we will discuss the efficacy of these methods in concrete data science problems, under appropriate statistical models. Students will be required to program in python or MATLAB. Prerequisites: CSE 247, Math 309, (Math 3200 or ESE 326), ESE 415. Attributes: EN: TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: E81 534A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 1:00P-2:20P TBA Kamilov Dec 18 2024 1:00PM - 3:00PM 0 0 70 Actions: Books Waits managed by dept. E35 ESE 520 Probability and Stochastic Processes 3.0 Units Details Save  Cancel   My Note:   Description: Review of probability theory, models for random signals and noise, calculus of random processes, noise in linear and nonlinear systems, representation of random signals by sampling and orthonormal expansions. Poisson, Gaussian, and Markov processes as models for engineering problems. Prereq: ESE 326. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Annually / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 4:00P-5:20P TBA Kurenok Dec 18 2024 6:00PM - 8:00PM 90 34 0 Actions: Books E35 ESE 527 Practicum in Data Analytics & Statistics 3.0 Units Details Save  Cancel   My Note:   Description: In this course, students will learn through hands-on experience the application of analytics to support data-driven decisions. Through lectures and the execution of a project (to be defined at the beginning of the semester), students will learn to use descriptive, predictive, and prescriptive analytics. Lectures will focus on presenting analytic topics relevant to the execution of the project, including analytic model development, data quality and data models, review of machine learning algorithms (unsupervised, supervised, and semi-supervised approaches), model validation, insights generation and results communication, and code review and code repository. Students are expected to demonstrate the application of these concepts through the execution of a one-semester project. Students can propose their own projects or choose from a list of projects made available by the lecturer. Projects should reflect real-world problems with a clear value proposition. Progress will be evaluated and graded periodically during the semester, and the course will include a final presentation open to the academic community. Prerequisites: ESE 520 (or Math 493 and 494), ESE 417 or CSE 417T, ESE 415 and declaration of the MS in DAS. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 5:30P-7:00P Lopata Hall / 101 La Rosa Default - none 0 0 26 Actions: Books Waits managed by dept. E35 ESE 536 Introduction to Quantum Optics 3.0 Units Details Save  Cancel   My Note:   Description: This course covers the following topics: quantum mechanics for quantum optics, radiative transitions in atoms, lasers, photon statistics (photon counting, Sub-/Super-Poissionian photon statistics, bunching, anti-bunching, theory of photodetection, shot noise), entanglement, squeezed light, atom-photon interactions, cold atoms, atoms in cavities. If time permits, the following topics will be selectively covered: quantum computing, quantum cryptography, and teleportation. Prerequisites: ESE 330 and Physics 217 or Physics 421 Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 1:00P-2:20P Green Hall / L0120 Shen No final 30 28 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. E35 ESE 543 Control Systems Design by State Space Methods 3.0 Units Details Save  Cancel   My Note:   Description: Advanced design and analysis of control systems by state-space methods: classical control review, Laplace transforms, review of linear algebra (vector space, change of basis, diagonal and Jordan forms), linear dynamic systems (modes, stability, controllability, state feedback, observability, observers, canonical forms, output feedback, separation principle and decoupling), nonlinear dynamic systems (stability, Lyapunov methods). Frequency domain analysis of multivariable control systems. State space control system design methods: state feedback, observer feedback, pole placement, linear optimal control. Design exercises with CAD (computer-aided design) packages for engineering problems. Prerequisite: ESE 351 and ESE 441, or permission of instructor. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Annually / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 ----F-- 1:00P-3:50P TBA Wise Exam last day of class 40 19 0 Actions: Books E35 ESE 545 Stochastic Control 3.0 Units Details Save  Cancel   My Note:   Description: Introduction to the theory of stochastic differential equations based on Wiener processes and Poisson counters, and an introduction to random fields. The formulation and solution of problems in nonlinear estimation theory. The Kalman-Bucy filter and nonlinear analogues. Identification theory. Adaptive systems. Applications. Prerequisites: ESE 520 and ESE 551 Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 1:00P-2:20P TBA Chen Dec 17 2024 1:00PM - 3:00PM 20 7 0 Actions: Books E35 ESE 551 Linear Dynamic Systems I 3.0 Units Details Save  Cancel   My Note:   Description: Input-output and state-space description of linear dynamic systems. Solution of the state equations and the transition matrix. Controllability, observability, realizations, pole-assignment, observers and decoupling of linear dynamic systems. Prereq: ESE 351. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: Fall / Summer / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 4:00P-5:20P Lopata Hall / 229 Li Dec 13 2024 6:00PM - 8:00PM 56 12 0 Actions: Books Syllabus Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. E35 ESE 560 Computer Systems Architecture I 3.0 Units Details Save  Cancel   My Note:   Description: An exploration of the central issues in computer architecture: instruction set design, addressing and register set design, control unit design, memory hierarchies (cache and main memories, virtual memory), pipelining, instruction scheduling, and parallel systems. The course emphasizes understanding the performance implications of design choices, using architecture modeling and evaluation using simulation techniques. Prerequisites: CSE 361S and CSE 260M. Attributes: EN: BME T2, TU 3.00 Instruction Type: Classroom instruction Grade Options: CP Fees: Course Type: Ident Same As: E81 560M Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 5:30P-7:00P TBA Hall No final 75 21 0 Actions: Books E35 ESE 562 Analog Integrated Circuits 3.0 Units Details Save  Cancel   My Note:   Description: This course focuses on fundamental and advanced topics in analog and mixed-signal VLSI techniques. The first part of the course covers graduate level materials in the area of analog circuit synthesis and analysis. The second part of the course covers applications of the fundamental techniques for designing analog signal processors and data converters. Several practical aspects of mixed-signal design, simulation and testing are covered in this course. This is a project-oriented course and it is expected that the students apply the concepts learned in the course to design, simulate and explore different circuit topologies. Prerequisite: E35 ESE 232 Attributes: EN: TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 11:30A-12:50P TBA Chakrabartty Dec 17 2024 10:30AM - 12:30PM 22 22 9 Actions: Books E35 ESE 565 Acceleration of Algorithms in Reconfigurable Logic 3.0 Units Details Save  Cancel   My Note:   Description: Reconfigurable logic, in the form of Field-Programmable Gate Arrays (FPGAs), enables the deployment of custom hardware for individual applications. To exploit this capability, the application developer is required to specify the design at the register-transfer level. This course explores techniques for designing algorithms that are amenable to hardware acceleration as well as provides experience in actual implementation. Example applications are drawn from a variety of fields, such as networking, computational biology, etc. Prerequisites: Basic digital logic (CSE 260M) and some experience with a hardware description language (e.g., VHDL or Verilog). Attributes: EN: TU Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Ident Same As: E81 565M Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 4:00P-5:20P TBA [TBA] Paper/Project/TakeHome 30 15 0 Actions: Books E35 ESE 5830 Nonlinear Optical Microscopy 3.0 Units Details Save  Cancel   My Note:   Description: This course will cover the theoretical and practical knowledge needed to design, construct, and use a nonlinear optical microscope. The course will focus on the relevant optical physics and instrumentation for different types of nonlinear optical microscopy, and additionally provide some information on applications and image processing. Topics include: ultrafast lasers, detectors, nonlinear susceptibility, nonlinear wave equation, quantum theory of nonlinear optics, harmonic generation, multiphoton fluorescence, fluorescence lifetime, optical metabolic imaging, coherent Raman scattering, and multimodal nonlinear optical microscopy. Prerequisites: Electromagnetism, at the level of ESE 330, and familiarity with Python or Matlab Attributes: Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 10:00A-11:20A TBA [TBA] See instructor 25 4 0 Actions: Books E35 ESE 590 Electrical & Systems Engineering Graduate Seminar 0.0 Unit Details Save  Cancel   My Note:   Description: This satisfactory/unsatisfactory course is required for the Masters, DSc and PhD degrees in Electrical and Systems Engineering. A satisfactory grade is required for each semester of enrollment and is received by attendance at regularly scheduled ESE seminars. Masters students must attend at least 3 seminars per semester, except for first year Master's students who must attend 4. DSc and PhD students must attend at least 5 seminars per semester, except for first year PhD students who must attend 6. Part-time students are exempt except during their year of residency. Any student under continuing status is also exempt. Attributes: Instruction Type: Classroom instruction Grade Options: U Fees: Course Type: Home Same As: N/A Frequency: Every Semester / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 ----F-- 10:00A-10:50A Green Hall / L0120 Feher No final 225 33 0 Actions: Books Waits Not Allowed E35 ESE 5931 Mathematics of Imaging Science 3.0 Units Details Save  Cancel   My Note:   Description: This course will expose students to a unified treatment of the mathematical properties of images and imaging. This will include an introduction to linear vector space theory, operator theory on Hilbert spaces, and concepts from applied functional analysis. Further, concepts from generalized functions, Fourier analysis, and Radon transform will be discussed. These tools will be applied to conduct deterministic analyses of imaging systems that are described as continuous-to-continuous, continuous-to-discrete, and discrete-to-discrete mappings from object properties to image data. In addition, imaging systems will be analyzed in a statistical framework where stochastic models for objects and images will be introduced. Prerequisite: Graduate standing or consent of instructor. Attributes: Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Ident Same As: E62 570  E62 470 Frequency: Fall / Summer / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 M-W---- 2:30P-3:50P Whitaker / 218 Jha, A Dec 16 2024 3:30PM - 5:30PM 35 25 0 Actions: Books E35 ESE 5933 Theoretical Imaging Science 3.0 Units Details Save  Cancel   My Note:   Description: Imaging science encompasses the design and optimization of imaging systems to quantitatively measure information of interest. Imaging systems are important in many scientific and medical applications and may be designed for one specific application or for a range of applications. Performance is quantified for any given task through an understanding of the statistical model for the imaging data, the data processing algorithm used, and a measure of accuracy or error. Optimal processing is based on statistical decision theory and estimation theory; performance bounds include the receiver operating characteristic and Cramer-Rao bounds. Bayesian methods often lead to ideal observers. Extensions of methods from finite-dimensional spaces to function space are fundamental for many imaging applications. A variety of methods to assess image quality and resulting imaging system optimization are covered. Prerequisite: Permission of instructor Attributes: EN: TU 3.00 Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 -T-R--- 4:00P-5:20P TBA O'Sullivan Dec 18 2024 6:00PM - 8:00PM 15 12 0 Actions: Books E35 ESE 596 Seminar in Imaging Science and Engineering 1.0 Unit Details Save  Cancel   My Note:   Description: This seminar course consists of a series of tutorial lectures on Imaging Science and Engineering with emphasis on applications of imaging technology. Students are exposed to a variety of imaging applications that vary depending on the semester, but may include multispectral remote sensing, astronomical imaging, microscopic imaging, ultrasound imaging, and tomographic imaging. Guest lecturers come from several parts of the university. This course is required of all students in the Imaging Science and Engineering program; the only requirement is attendance. This course is graded Pass/Fail. Prerequisite: Admission to Imaging Science and Engineering Program. Attributes: Instruction Type: Classroom instruction Grade Options: CPA Fees: Course Type: Home Same As: E62 506 Frequency: Every Semester / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 ----F-- 8:30A-9:50A Green Hall / L0120 O'Sullivan No final 40 9 0 Actions: Books E35 ESE 599 Masters Research Var. Units (max = 3.0) Details Save  Cancel   My Note:   Description: Prerequisite: Students must have the ESE Research Registration Form. approved by the department. The form must contain a brief description of the work that is expected to be completed during the course. Attributes: Instruction Type: Dissertation/Research Grade Options: C Fees: Course Type: Home Same As: N/A Frequency: None / History Sec Days       Time Building / Room Instructor Final Exam Seats Enroll Waits 01 TBA TBA Clark No final 0 0 1 Actions: Books Waits managed by dept. 02 TBA TBA Zhu No final 0 0 0 Actions: Books Waits managed by dept. 03 TBA TBA Ching No final 0 0 1 Actions: Books Waits managed by dept. 04 TBA TBA Zhou No final 0 0 0 Actions: Books Waits managed by dept. 05 TBA TBA Wormleighton No final 0 0 1 Actions: Books Waits managed by dept. 07 TBA TBA Lew No final 0 0 0 Actions: Books Waits managed by dept. 08 TBA TBA Kamilov No final 0 0 1 Actions: Books Waits managed by dept. 13 TBA TBA O'Sullivan No final 0 0 0 Actions: Books Waits managed by dept. 14 TBA TBA Patwari No final 0 0 1 Actions: Books Waits managed by dept. 28 TBA TBA Yang No final 0 0 0 Actions: Books Waits managed by dept. 29 TBA TBA Li No final 0 0 1 Actions: Books Waits managed by dept. 30 TBA TBA Shen No final 0 0 0 Actions: Books Waits managed by dept. 31 TBA TBA Wang No final 0 0 1 Actions: Books Waits managed by dept. 32 TBA TBA Kurenok No final 0 0 0 Actions: Books Waits managed by dept. 34 TBA TBA Mell No final 0 0 0 Actions: Books Waits managed by dept. 36 TBA TBA Nagulu No final 0 0 0 Actions: Books Waits managed by dept. 37 TBA TBA Chakrabartty No final 0 0 0 Actions: Books Waits managed by dept. 38 TBA TBA Zeng No final 0 0 0 Actions: Books Waits managed by dept. 39 TBA TBA Villa No final 0 0 0 Actions: Books Waits managed by dept. 40 TBA TBA Murch No final 0 0 0 Actions: Books Waits managed by dept. 41 TBA TBA Chamberlain No final 0 0 1 Actions: Books Waits managed by dept. 42 TBA TBA Kantaros No final 0 0 1 Actions: Books Waits managed by dept. 43 TBA TBA Culver No final 0 0 0 Actions: Books Waits managed by dept. 44 TBA TBA Sotiras No final 0 0 0 Actions: Books Waits managed by dept. 45 TBA TBA Wang No final 0 0 0 Actions: Books Waits managed by dept.