| | 02 | TBA | | TBA | Arthur | See Department | 0 | 0 | 0 | | | |
| 03 | TBA | | TBA | Ching | See Department | 0 | 1 | 0 | | | |
| 04 | TBA | | TBA | [TBA] | See Department | 0 | 0 | 0 | | | |
| 05 | TBA | | TBA | Brown | See Department | 0 | 0 | 0 | | | |
| 06 | TBA | | TBA | Zhang | See Department | 0 | 0 | 0 | | | |
| 07 | TBA | | TBA | Lew | See Department | 0 | 0 | 0 | | | |
| 09 | TBA | | TBA | [TBA] | See Department | 0 | 0 | 0 | | | |
| 10 | TBA | | TBA | Min | See Department | 0 | 0 | 0 | | | |
| 11 | TBA | | TBA | [TBA] | See Department | 0 | 0 | 0 | | | |
| 12 | TBA | | TBA | Mukai | See Department | 0 | 0 | 0 | | | |
| 13 | TBA | | TBA | O'Sullivan | See Department | 0 | 0 | 0 | | | |
| 14 | TBA | | TBA | Pickard | See Department | 0 | 0 | 0 | | | |
| 15 | TBA | | TBA | Rode | See Department | 0 | 0 | 0 | | | |
| 16 | TBA | | TBA | Rodin | See Department | 0 | 0 | 0 | | | |
| 17 | TBA | | TBA | Schaettler | See Department | 0 | 0 | 0 | | | |
| 18 | TBA | | TBA | Shrauner | See Department | 0 | 0 | 0 | | | |
| 19 | TBA | | TBA | Snyder | See Department | 0 | 0 | 0 | | | |
| 20 | TBA | | TBA | Spielman | See Department | 0 | 0 | 0 | | | |
| 21 | TBA | | TBA | Tarn | See Department | 0 | 0 | 0 | | | |
| 27 | TBA | | TBA | Nehorai | See Department | 0 | 0 | 0 | | | |
| 28 | TBA | | TBA | Yang | See Department | 0 | 0 | 0 | | | |
| 29 | TBA | | TBA | Li | See Department | 0 | 0 | 0 | | | |
| 30 | TBA | | TBA | Shen | See Department | 0 | 0 | 0 | | | |
| 31 | TBA | | TBA | Wang | See Department | 0 | 0 | 0 | | | |
| 32 | TBA | | TBA | Kurenok | See Department | 0 | 0 | 0 | | | |
| 34 | TBA | | TBA | Mell | See Department | 0 | 0 | 0 | | | |
| 36 | TBA | | TBA | Kamilov | See Department | 0 | 0 | 0 | | | |
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| | 01 | M------ | 2:30P-3:50P | Wilson / 214 | Feher | No Final | 48 | 27 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| A | ----F-- | 8:30A-10:30A | Urbauer / 214 | Feher | Default - none | 15 | 0 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| B | ----F-- | 10:30A-12:30P | Urbauer / 214 | Feher | Default - none | 15 | 15 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| C | ----F-- | 1:30P-3:30P | Urbauer / 214 | Feher | Default - none | 15 | 12 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 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. 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. Prerequisites: Phys 198/118A. Corequisite: Math 217. |
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| | 01 | -T-R--- | 1:00P-2:20P | Remote / EN | Nussinov | Exam Last Day of Class | 90 | 34 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| A | --W---- | 11:00A-12:20P | Remote / EN | Nussinov | Default - none | 20 | 10 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| B | --W---- | 1:00P-2:20P | Remote / EN | Nussinov | Default - none | 15 | 8 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| C | ---R--- | 2:30P-3:50P | Remote / EN | Nussinov | Default - none | 16 | 16 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | M-W---- | 4:00P-5:20P | Remote / EN | Wang | May 10 2021 6:00PM - 8:00PM | 75 | 51 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | M-W---- | 1:00P-2:20P | Remote / EN | Richard | May 13 2021 1:00PM - 3:00PM | 50 | 43 | 0 | | | |
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| | 01 | M-W---- | 11:30A-12:50P | Remote / EN | Khanmohammadi | May 12 2021 10:30AM - 12:30PM | 40 | 22 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 02 | -T-R--- | 10:00A-11:20A | Louderman / 458 | Hasting | May 12 2021 6:00PM - 8:00PM | 40 | 21 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | M-W-F-- | 9:00A-9:50A | Hillman / 70 | Hasting | May 10 2021 8:00AM - 10:00AM | 70 | 55 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 02 | -T-R--- | 11:30A-12:50P | Louderman / 458 | Seidel | May 11 2021 1:00PM - 3:00PM | 70 | 70 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 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. |
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| | 01 | M-W---- | 10:00A-11:20A | Brown / 100 | Kurenok | May 11 2021 10:30AM - 12:30PM | 85 | 38 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 02 | -T-R--- | 1:00P-2:20P | Remote / EN | Krone | May 12 2021 1:00PM - 3:00PM | 110 | 99 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| A | ----F-- | 2:30P-3:20P | Remote / EN | Krone | Default - none | 110 | 96 | 0 | Desc: | This optional discussion section is only for students enrolled in section 02 with Prof. Krone. |
| | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | -T----- | 10:00A-11:20A | Remote / EN | Wang, Dorothy | May 12 2021 6:00PM - 8:00PM | 24 | 11 | 0 | | | |
| A | ---R--- | 10:00A-12:50P | Remote / EN | Wang, Dorothy | Default - none | 24 | 11 | 0 | | | |
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| | 01 | -T-R--- | 4:00P-5:20P | Remote / EN | Collins | Paper/Project/Take Home | 15 | 6 | 0 | Desc: | Same room as T15 3320. |
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| Description: | Introduction to concepts and methodology of discrete- and continuous-time signals in relation to linear dynamic systems. Representation of signals and systems. Fourier, Laplace, and Z-transforms. Input-output description of linear systems: impulse response, convolution, transfer function. Time-domain and frequency-domain system analysis: transient and steady-state responses, stability, frequency spectra and frequency responses. Matlab-based case studies highlight the role of this material in key ESE areas of signal processing, control systems, and communication. Prerequisites: Physics 117A-118A, Math 217, CSE 131, Matlab, matrix addition and multiplication, and ESE 105 or ESE 230; Corequisite: ESE 318. |
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| | 01 | -T-R--- | 2:30P-3:50P | Rebstock / 215 | Trobaugh | May 13 2021 3:30PM - 5:30PM | 70 | 36 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| A | ----F-- | 11:00A-11:50A | Remote / EN | Trobaugh | Default - none | 50 | 2 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | TBA | | TBA | Feher | Default - none | 0 | 1 | 0 | | | |
| 02 | TBA | | TBA | Arthur | Default - none | 0 | 0 | 0 | | | |
| 03 | TBA | | TBA | Ching | Default - none | 0 | 1 | 0 | | | |
| 04 | TBA | | TBA | Zeng | Default - none | 0 | 0 | 0 | | | |
| 05 | TBA | | TBA | Brown | Default - none | 0 | 0 | 0 | | | |
| 06 | TBA | | TBA | Zhang, Silvia | Default - none | 0 | 1 | 0 | | | |
| 07 | TBA | | TBA | Lew | Default - none | 0 | 0 | 0 | | | |
| 08 | TBA | | TBA | Chakrabartty | Default - none | 0 | 1 | 0 | | | |
| 09 | TBA | | TBA | [TBA] | Default - none | 0 | 0 | 0 | | | |
| 10 | TBA | | TBA | Min | Default - none | 0 | 0 | 0 | | | |
| 11 | TBA | | TBA | Nussinov | Default - none | 0 | 0 | 0 | | | |
| 12 | TBA | | TBA | Mukai | Default - none | 0 | 0 | 0 | | | |
| 13 | TBA | | TBA | O'Sullivan | Default - none | 0 | 0 | 0 | | | |
| 14 | TBA | | TBA | Pickard | Default - none | 0 | 0 | 0 | | | |
| 15 | TBA | | TBA | Rode | Default - none | 0 | 0 | 0 | | | |
| 16 | TBA | | TBA | Rodin | Default - none | 0 | 0 | 0 | | | |
| 17 | TBA | | TBA | Schaettler | Default - none | 0 | 0 | 0 | | | |
| 18 | TBA | | TBA | Shrauner | Default - none | 0 | 0 | 0 | | | |
| 19 | TBA | | TBA | Snyder | Default - none | 0 | 0 | 0 | | | |
| 20 | TBA | | TBA | Spielman | Default - none | 0 | 0 | 0 | | | |
| 21 | TBA | | TBA | Tarn | Default - none | 0 | 0 | 0 | | | |
| 22 | TBA | | TBA | Trobaugh | Default - none | 0 | 0 | 0 | | | |
| 27 | TBA | | TBA | Nehorai | Default - none | 0 | 0 | 0 | | | |
| 28 | TBA | | TBA | Yang | Default - none | 0 | 0 | 0 | | | |
| 29 | TBA | | TBA | Li | Default - none | 0 | 0 | 0 | | | |
| 30 | TBA | | TBA | Shen | Default - none | 0 | 0 | 0 | | | |
| 31 | TBA | | TBA | Wang | Default - none | 0 | 0 | 0 | | | |
| 32 | TBA | | TBA | Kurenok | Default - none | 0 | 0 | 0 | | | |
| 34 | TBA | | TBA | Mell | Default - none | 0 | 0 | 0 | | | |
| 36 | TBA | | TBA | Kamilov | Default - none | 0 | 0 | 0 | | | |
| 37 | TBA | | TBA | Bhan | Default - none | 0 | 0 | 0 | | | |
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| | 01 | --W---- | 8:00P-10:00P | Remote / EN | Becnel | Exam Last Day of Class | 30 | 7 | 0 | | | |
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| | 01 | -T-R--- | 5:30P-7:00P | Remote / EN | Bassham | May 11 2021 6:00PM - 8:00PM | 25 | 18 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| Description: | This course gives a rigorous and comprehensive introduction of fundamentals of nonlinear optimization theory and computational methods. Topics include unconstrained and constrained optimization, quadratic and convex optimization, numerical optimization methods, optimality conditions, and duality theory. Algorithmic methods include Steepest Descent, Newton's method, Conjugate Gradient methods as well as exact and inexact line search procedures for unconstrained optimization. Constrained optimization methods include penalty and multiplier methods. Applications range from engineering and physics to economics. Moreover, generalized programming, interior point methods, and semi-definite programming will be discussed if time permits. Prerequisites: CSE 131, Math 309 and ESE 318 or permission of instructor. |
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| | 01 | M-W---- | 10:00A-11:20A | Remote / EN | Kamilov | May 11 2021 10:30AM - 12:30PM | 80 | 66 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | M-W---- | 4:00P-5:20P | Remote / EN | Zhang | May 10 2021 6:00PM - 8:00PM | 75 | 59 | 0 | | | |
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| | 01 | M-W---- | 1:00P-2:20P | Remote / EN | Shen | May 13 2021 1:00PM - 3:00PM | 40 | 20 | 0 | | | |
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| | 01 | -T-R--- | 4:00P-5:20P | Remote / EN | Zeng | May 13 2021 6:00PM - 8:00PM | 60 | 29 | 0 | | | |
| A | --W---- | 4:00P-5:00P | Remote / EN | Zeng | Default - none | 30 | 0 | 0 | | | |
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| Description: | The course provides 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) prerequisite of ESE 230 and corequisite of ESE 351; (2) prerequisites of ESE 230, ESE 318 and MEMS 255 (Mechanics II); (3) prerequisites of ESE 351; (4) permission of instructor. |
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| | 01 | M-W---- | 5:30P-7:00P | Mallinckrodt / 305 | Becnel | May 10 2021 6:00PM - 8:00PM | 12 | 10 | 0 | Desc: | Occassional labs in URB 208. |
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| | 01 | -T-R--- | 2:30P-3:50P | Crow / 201 | Mell | May 13 2021 6:00PM - 8:00PM | 53 | 29 | 0 | | | |
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| | 01 | -T-R--- | 9:00A-10:50A | Remote / EN | Zhang | No Final | 24 | 9 | 0 | | | |
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| | A | --W---- | 9:00A-11:50A | Brauer Hall / 007 | Silbaugh | Default - none | 12 | 12 | 0 | Desc: | Labs are held in Brauer 7. |
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| B | ----F-- | 9:00A-11:50A | Brauer Hall / 007 | Silbaugh | Default - none | 12 | 9 | 0 | Desc: | Labs are held in Brauer 7. |
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| | 01 | -T-R--- | 1:00P-2:20P | Remote / EN | Richard | No Final | 10 | 11 | 0 | | | |
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| | 01 | -T-R--- | 5:30P-7:00P | Crow / 201 | Ivanovich | May 11 2021 6:00PM - 8:00PM | 30 | 15 | 0 | | | |
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| | 01 | M-W---- | 1:00P-2:20P | Remote / EN | Patwari | May 13 2021 1:00PM - 3:00PM | 50 | 26 | 0 | | | |
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| | 02 | TBA | | TBA | Arthur | Default - none | 0 | 0 | 0 | | | |
| 03 | TBA | | TBA | Ching | Default - none | 0 | 1 | 0 | | | |
| 04 | TBA | | TBA | Patwari | Default - none | 0 | 2 | 0 | | | |
| 05 | TBA | | TBA | Richter | Default - none | 0 | 0 | 0 | | | |
| 06 | TBA | | TBA | Zhang, Silvia | Default - none | 0 | 1 | 0 | | | |
| 07 | TBA | | TBA | Lew | Default - none | 0 | 0 | 0 | | | |
| 08 | TBA | | TBA | Chakrabartty | Default - none | 0 | 1 | 0 | | | |
| 09 | TBA | | TBA | Katz | Default - none | 0 | 0 | 0 | | | |
| 10 | TBA | | TBA | Min | Default - none | 0 | 0 | 0 | | | |
| 11 | TBA | | TBA | [TBA] | Default - none | 0 | 0 | 0 | | | |
| 12 | TBA | | TBA | Mukai | Default - none | 0 | 0 | 0 | | | |
| 13 | TBA | | TBA | O'Sullivan | Default - none | 0 | 0 | 0 | | | |
| 14 | TBA | | TBA | Pickard | Default - none | 0 | 0 | 0 | | | |
| 15 | TBA | | TBA | Rode | Default - none | 0 | 0 | 0 | | | |
| 16 | TBA | | TBA | Rodin | Default - none | 0 | 0 | 0 | | | |
| 17 | TBA | | TBA | Schaettler | Default - none | 0 | 0 | 0 | | | |
| 18 | TBA | | TBA | Shrauner | Default - none | 0 | 0 | 0 | | | |
| 19 | TBA | | TBA | Snyder | Default - none | 0 | 0 | 0 | | | |
| 20 | TBA | | TBA | Spielman | Default - none | 0 | 0 | 0 | | | |
| 21 | TBA | | TBA | Tarn | Default - none | 0 | 0 | 0 | | | |
| 22 | TBA | | TBA | Trobaugh | Default - none | 0 | 0 | 0 | | | |
| 27 | TBA | | TBA | Nehorai | Default - none | 0 | 0 | 0 | | | |
| 28 | TBA | | TBA | Yang | Default - none | 0 | 0 | 0 | | | |
| 29 | TBA | | TBA | Li | Default - none | 0 | 0 | 0 | | | |
| 30 | TBA | | TBA | Shen | Default - none | 0 | 0 | 0 | | | |
| 31 | TBA | | TBA | Wang | Default - none | 0 | 0 | 0 | | | |
| 32 | TBA | | TBA | Kurenok | Default - none | 0 | 0 | 0 | | | |
| 34 | TBA | | TBA | Mell | Default - none | 0 | 0 | 0 | | | |
| 36 | TBA | | TBA | Kamilov | Default - none | 0 | 0 | 0 | | | |
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| 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. |
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| | 01 | ----F-- | 2:00P-3:50P | Remote / EN | Wang, Dorothy | No Final | 0 | 20 | 0 | | | |
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| 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. |
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| | 01 | ----F-- | 2:00P-3:50P | Remote / EN | Wang | No Final | 0 | 14 | 0 | | | |
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| | 02 | TBA | | TBA | Arthur | Default - none | 0 | 0 | 0 | | | |
| 03 | TBA | | TBA | Ching | Default - none | 0 | 0 | 0 | | | |
| 04 | TBA | | TBA | [TBA] | Default - none | 0 | 0 | 0 | | | |
| 05 | TBA | | TBA | Brown | Default - none | 0 | 0 | 0 | | | |
| 06 | TBA | | TBA | Zhang, Silvia | Default - none | 0 | 0 | 0 | | | |
| 07 | TBA | | TBA | Lew | Default - none | 0 | 0 | 0 | | | |
| 08 | TBA | | TBA | Chakrabartty | Default - none | 0 | 0 | 0 | | | |
| 09 | TBA | | TBA | [TBA] | Default - none | 0 | 0 | 0 | | | |
| 10 | TBA | | TBA | Min | Default - none | 0 | 0 | 0 | | | |
| 11 | TBA | | TBA | [TBA] | Default - none | 0 | 0 | 0 | | | |
| 12 | TBA | | TBA | Mukai | Default - none | 0 | 0 | 0 | | | |
| 13 | TBA | | TBA | O'Sullivan | Default - none | 0 | 0 | 0 | | | |
| 14 | TBA | | TBA | Pickard | Default - none | 0 | 0 | 0 | | | |
| 15 | TBA | | TBA | Rode | Default - none | 0 | 0 | 0 | | | |
| 16 | TBA | | TBA | Rodin | Default - none | 0 | 0 | 0 | | | |
| 17 | TBA | | TBA | Schaettler | Default - none | 0 | 0 | 0 | | | |
| 18 | TBA | | TBA | Shrauner | Default - none | 0 | 0 | 0 | | | |
| 19 | TBA | | TBA | Snyder | Default - none | 0 | 0 | 0 | | | |
| 20 | TBA | | TBA | Spielman | Default - none | 0 | 0 | 0 | | | |
| 21 | TBA | | TBA | Tarn | Default - none | 0 | 0 | 0 | | | |
| 27 | TBA | | TBA | Nehorai | Default - none | 0 | 0 | 0 | | | |
| 28 | TBA | | TBA | Yang | Default - none | 0 | 0 | 0 | | | |
| 29 | TBA | | TBA | Li | Default - none | 0 | 0 | 0 | | | |
| 30 | TBA | | TBA | Shen | Default - none | 0 | 0 | 0 | | | |
| 31 | TBA | | TBA | Wang | Default - none | 0 | 0 | 0 | | | |
| 32 | TBA | | TBA | Kurenok | Default - none | 0 | 0 | 0 | | | |
| 34 | TBA | | TBA | Mell | Default - none | 0 | 0 | 0 | | | |
| 36 | TBA | | TBA | Kamilov | Default - none | 0 | 2 | 0 | | | |
| 37 | TBA | | TBA | Zeng | Default - none | 0 | 1 | 0 | | | |
| 38 | TBA | | TBA | Zhou | Default - none | 0 | 1 | 0 | | | |
| 39 | TBA | | TBA | Villa | Default - none | 0 | 0 | 0 | | | |
| 40 | TBA | | TBA | Zhou | Default - none | 0 | 0 | 0 | | |
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| | 01 | M-W---- | 4:00P-5:20P | Louderman / 458 | Kurenok | May 10 2021 6:00PM - 8:00PM | 50 | 30 | 0 | | | |
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| | 01 | -T-R--- | 4:00P-5:20P | Hillman / 60 | Kurenok | May 13 2021 6:00PM - 8:00PM | 65 | 42 | 0 | | | |
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| | 01 | -T-R--- | 4:00P-5:20P | Remote / EN | Nehorai | May 7 2021 3:30PM - 5:30PM | 70 | 34 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| 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), CSE 417T, ESE 415, and declaration of the MS in DAS. |
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| | 01 | M-W---- | 5:30P-7:00P | Seigle / 104 | La Rosa | May 10 2021 6:00PM - 8:00PM | 0 | 16 | 0 | | | |
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| Description: | Have you ever dreamed of owning an invisibility cloak, building a blackhole, wondered how to make an indestructible optical fiber, or wished your car windows could solve differential equations? In this course we delve into the physics that governs electromagnetic properties of materials and apply these insights to design artificial material systems limited by imagination rather than chemistry. Specific topics will include the design and function of negative index, near-zero index, hyperbolic, chiral, random, and topological metamaterials. We will also explore space and time varying, nonlinear, and quantum metamaterials, metasurfaces and photonic crystals. Beyond their operation, we will touch upon techniques for fabricating and characterizing these systems. Prerequisites: ESE 330, or Physics 421 and Physics 422. |
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| | 01 | -T-R--- | 2:30P-3:50P | Brown / 118 | Lawrence | May 13 2021 3:30PM - 5:30PM | 40 | 7 | 0 | | | |
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| Description: | This course is a graduate level course taught in two parts. Part 1 covers frequency domain analysis of multivariable systems, robustness theory and structured singular value mu analysis, linear quadratic optimal control system design using state and output feedback architectures, H-infinity optimal control, LQG/LTR, and output feedback projective controls. Part 2 covers the design of direct model reference adaptive controllers for uncertain nonlinear systems, Lyapunov stability theory, Barbalat lemma, neural networks, state feedback model reference adaptive control, and adaptive observer-based loop transfer recovery output feedback. Homework and computer design projects use aerospace examples. The adaptive controllers are developed to be an increment added to the robust control baseline architecture (covered in part 1).Prerequisite: ESE 543 Control Systems Design by State Space Methods or ESE 551 Linear Dynamic Systems or equivalent. |
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| | 01 | ----F-- | 1:00P-3:50P | Remote / EN | Wise | Exam Last Day of Class | 75 | 25 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| | 01 | M-W---- | 10:00A-11:20A | Remote / EN | Ching | May 12 2021 10:30AM - 12:30PM | 35 | 13 | 0 | | | |
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| Description: | A rigorous introduction to recent developments in systems and controls. Focus is on the discussion of interdisciplinary applications of complex systems that motivate emerging topics in dynamics and control, and state-of-the-art methods for addressing the control, computation, and learning problems involving these large-scale systems. Topics to be covered include geometric and stochastic control of high-dimensional systems, operator and topological methods for dynamic learning, and data-driven methods for dynamical systems and controls with applications to complex networks, multi-agent and ensemble systems. Technical tools to be discussed for understanding these topics include basics of differential geometry, stochastic calculus and stochastic differential equations, as well as reinforcement learning. Students learn about the state-of-the-art research in the field, and ultimately apply their knowledge to conduct a final project. Prerequisite: Linear algebra (Math 429) or equivalent, ESE 415 Optimization, ESE 551 Linear Dynamic Systems, ESE 553 Nonlinear Dynamic Systems, and ESE 520 Probability and Stochastic Processes. |
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| | 01 | M-W---- | 11:30A-12:50P | Remote / EN | Li | May 12 2021 10:30AM - 12:30PM | 25 | 11 | 0 | | | |
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| | 01 | M-W---- | 11:30A-12:50P | Remote / EN | Chakrabartty | May 12 2021 10:30AM - 12:30PM | 0 | 7 | 0 | | | |
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| | 01 | M-W---- | 1:00P-2:20P | Remote / EN | Min | May 13 2021 1:00PM - 3:00PM | 40 | 5 | 0 | | | |
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| Description: | Analysis, design, and application of modern optical imaging systems with emphasis on biological imaging. First part of course will focus on the physical principles underlying the operation of imaging systems and their mathematical models. Topics include ray optics (speed of light, refractive index, laws of reflection and refraction, plane surfaces, mirrors, lenses, aberrations), wave optics (amplitude and intensity, frequency and wavelength, superposition and interference, interferometry), Fourier optics (space-invariant linear systems, Huygens-Fresnel principle, angular spectrum, Fresnel diffraction, Fraunhofer diffraction, frequency analysis of imaging systems), and light-matter interaction (absorption, scattering, dispersion, fluorescence). Second part of course will compare modern quantitative imaging technologies including, but not limited to, digital holography, computational imaging, and super-resolution microscopy. Students will evaluate and critique recent optical imaging literature.Pre-requisites: ESE 318 and ESE 319 or their equivalents; ESE 330 or PHY 421 or equivalent.
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| | 01 | M-W---- | 2:30P-3:50P | Hillman / 60 | Lew | May 11 2021 3:30PM - 5:30PM | 30 | 23 | 0 | | | | Actions: | | Books | | Syllabus | | Syllabi are provided to students to support their course planning; refer to the syllabus for constraints on use. |
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| Description: | This class will develop a fundamental understanding of the physics and mathematical methods that underlie biological imaging and critically examine case studies of seminal biological imaging technology literature. The physics section will examine how electromagnetic and acoustic waves interact with tissues and cells, how waves can be used to image the biological structure and function, image formation methods and diffraction limited imaging. The math section will examine image decomposition using basis functions (e.g. fourier transforms), synthesis of measurement data, image analysis for feature extraction, reduction of multi-dimensional imaging datasets, multivariate regression, and statistical image analysis. Original literature on electron, confocal and two photon microscopy, ultrasound, computed tomography, functional and structural magnetic resonance imaging and other emerging imaging technology will be critiqued. |
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| | 01 | -T-R--- | 8:30A-9:50A | Hillman / 60 | O'Sullivan | May 10 2021 1:00PM - 3:00PM | 50 | 23 | 0 | | | |
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| | 01 | TBA | | Remote / EN | Feher | No Final | 300 | 135 | 0 | | | |
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| | 02 | TBA | | TBA | Arthur | Default - none | 0 | 0 | 0 | | | |
| 03 | TBA | | TBA | Ching | Default - none | 0 | 0 | 0 | | | |
| 04 | TBA | | TBA | [TBA] | Default - none | 0 | 0 | 0 | | | |
| 05 | TBA | | TBA | Brown | Default - none | 0 | 0 | 0 | | | |
| 06 | TBA | | TBA | Zhang, Silvia | Default - none | 0 | 0 | 0 | | | |
| 07 | TBA | | TBA | Lew | Default - none | 0 | 0 | 0 | | | |
| 08 | TBA | | TBA | Chakrabartty | Default - none | 0 | 0 | 0 | | | |
| 09 | TBA | | TBA | [TBA] | Default - none | 0 | 0 | 0 | | | |
| 10 | TBA | | TBA | Min | Default - none | 0 | 0 | 0 | | | |
| 11 | TBA | | TBA | Feher | Default - none | 0 | 0 | 0 | | | |
| 12 | TBA | | TBA | Mukai | Default - none | 0 | 0 | 0 | | | |
| 13 | TBA | | TBA | O'Sullivan | Default - none | 0 | 1 | 0 | | | |
| 14 | TBA | | TBA | Pickard | Default - none | 0 | 0 | 0 | | | |
| 15 | TBA | | TBA | Rode | Default - none | 0 | 0 | 0 | | | |
| 16 | TBA | | TBA | Rodin | Default - none | 0 | 0 | 0 | | | |
| 17 | TBA | | TBA | Schaettler | Default - none | 0 | 0 | 0 | | | |
| 18 | TBA | | TBA | Shrauner | Default - none | 0 | 0 | 0 | | | |
| 19 | TBA | | TBA | Snyder | Default - none | 0 | 0 | 0 | | | |
| 20 | TBA | | TBA | Spielman | Default - none | 0 | 0 | 0 | | | |
| 21 | TBA | | TBA | Tarn | Default - none | 0 | 0 | 0 | | | |
| 27 | TBA | | TBA | Nehorai | Default - none | 0 | 0 | 0 | | | |
| 28 | TBA | | TBA | Yang | Default - none | 0 | 0 | 0 | | | |
| 29 | TBA | | TBA | Li | Default - none | 0 | 0 | 0 | | | |
| 30 | TBA | | TBA | Shen | Default - none | 0 | 0 | 0 | | | |
| 31 | TBA | | TBA | Wang | Default - none | 0 | 0 | 0 | | | |
| 32 | TBA | | TBA | Kurenok | Default - none | 0 | 0 | 0 | | | |
| 34 | TBA | | TBA | Mell | Default - none | 0 | 0 | 0 | | | |
| 36 | TBA | | TBA | Kamilov | Default - none | 0 | 1 | 0 | | | |
| 37 | TBA | | TBA | Zeng | Default - none | 0 | 0 | 0 | | | |
| 38 | TBA | | TBA | Zhou | Default - none | 0 | 0 | 0 | | | |
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| | 02 | TBA | | TBA | Arthur | Default - none | 9 | 0 | 0 | | | |
| 03 | TBA | | TBA | Ching | Default - none | 9 | 4 | 0 | | | |
| 04 | TBA | | TBA | Zhou | Default - none | 9 | 0 | 0 | | | |
| 05 | TBA | | TBA | Brown | Default - none | 9 | 0 | 0 | | | |
| 06 | TBA | | TBA | Zhang, Silvia | Default - none | 9 | 4 | 0 | | | |
| 07 | TBA | | TBA | Lew | Default - none | 9 | 1 | 0 | | | |
| 08 | TBA | | TBA | Chakrabartty | Default - none | 9 | 1 | 0 | | | |
| 09 | TBA | | TBA | [TBA] | Default - none | 9 | 0 | 0 | | | |
| 10 | TBA | | TBA | Min | Default - none | 9 | 0 | 0 | | | |
| 11 | TBA | | TBA | Wang, Yong | Default - none | 9 | 3 | 0 | | | |
| 12 | TBA | | TBA | Mukai | Default - none | 9 | 0 | 0 | | | |
| 13 | TBA | | TBA | O'Sullivan | Default - none | 9 | 6 | 0 | | | |
| 14 | TBA | | TBA | Pickard | Default - none | 9 | 0 | 0 | | | |
| 15 | TBA | | TBA | Rode | Default - none | 9 | 0 | 0 | | | |
| 16 | TBA | | TBA | Rodin | Default - none | 9 | 0 | 0 | | | |
| 17 | TBA | | TBA | Schaettler | Default - none | 9 | 0 | 0 | | | |
| 18 | TBA | | TBA | Shrauner | Default - none | 9 | 0 | 0 | | | |
| 19 | TBA | | TBA | Snyder | Default - none | 9 | 0 | 0 | | | |
| 20 | TBA | | TBA | Spielman | Default - none | 9 | 0 | 0 | | | |
| 21 | TBA | | TBA | Tarn | Default - none | 9 | 0 | 0 | | | |
| 27 | TBA | | TBA | Nehorai | Default - none | 9 | 2 | 0 | | | |
| 28 | TBA | | TBA | Yang | Default - none | 9 | 6 | 0 | | | |
| 29 | TBA | | TBA | Li | Default - none | 10 | 5 | 0 | | | |
| 30 | TBA | | TBA | Shen | Default - none | 10 | 3 | 0 | | | |
| 31 | TBA | | TBA | Wang | Default - none | 10 | 0 | 0 | | | |
| 32 | TBA | | TBA | Kurenok | Default - none | 10 | 0 | 0 | | | |
| 34 | TBA | | TBA | Mell | Default - none | 10 | 0 | 0 | | | |
| 36 | TBA | | TBA | Kamilov | Default - none | 9 | 1 | 0 | | | |
| 37 | TBA | | TBA | Anastasio | Default - none | 9 | 0 | 0 | | | |
| 38 | TBA | | TBA | Zeng | Default - none | 9 | 3 | 0 | | | |
| 39 | TBA | | TBA | Patwari | No Final | 9 | 3 | 0 | | | |
| 40 | TBA | | TBA | Sotiras | No Final | 999 | 3 | 0 | | | |
| 42 | TBA | | TBA | Raman | No Final | 999 | 0 | 0 | | | |
| 45 | TBA | | TBA | Wang | No Final | 999 | 2 | 0 | | |
| 46 | TBA | | TBA | Sinopoli | No Final | 999 | 1 | 0 | | |
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| | 01 | TBA | | TBA | O'Sullivan | Default - none | 0 | 3 | 0 | | | |
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