ECE 598

Fall 2020 All Classes

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Special Topics in ECE

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Credit: 0 TO 4 hours.

Subject offerings of new and developing areas of knowledge in electrical and computer engineering intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites.

May be repeated in the same or separate terms if topics vary.

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ECE 598 class schedule data for fall 2020
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
75068	Online	HCO	9:30AM -10:50AM	TR	n.a.	Driggs-Campbell, K	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Human-Centered Robotics Section Info: This course focuses on the mathematical and algorithmic tools that allow us to design and control robots that interact with people and gives an overview of what is require for guaranteeing safety in interactive settings on physical systems. Topics include advanced robotics, levels of autonomy, decision making and control, artificial intelligence, human-in-the-loop control, and human-robot interaction. Students will practice essential research skills including critiquing papers, debating, reviewing, writing project proposals, and presenting ideas effectively. Prerequisites: Graduate standing; ECE470 (Introduction to Robotics) and ECE448/CS440 (Introduction to Artificial Intelligence) or equivalent; Familiarity with decision-making, controls, and optimization is recommended, but not required
66519	Online	HH	11:00AM -12:20PM	TR	n.a.	Al-Hassanieh, H	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Wireless Networks & Mobile Sys Section Info: The goal of this course is to introduce students to advanced research topics in wireless networks and mobile communication systems. In each lecture, we will discuss one or two research papers that introduce new wireless designs, algorithms, protocols and applications. The papers are systems oriented and focus on practical challenges and solutions for building wireless and mobile systems. The course will cover the latest research topics including the Internet of Things, cross layer design, interference management, multi-antenna systems, distributed wireless systems, network coding, backscatter communication, full-duplex radios, wireless localization and sensing, wireless security, wireless charging… Student will also learn how to design and build wireless systems through a research oriented course project that focuses on implementation aspects of practical systems. Prerequisites: Maturity in understanding of computer networking and digital communications. At least one of the following courses or an equivalent: ECE 438 (Communication Networks), ECE 439 (Wireless Networks), ECE 361/461 (Digital Communications), ECE 463 (Digital Communications Lab), ECE 459 (Communications I). Restriction(s): Restricted to Graduate - Urbana-Champaign.
75081	Online	HHO	ARRANGED	n.a.	n.a.	Al-Hassanieh, H	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Wireless Networks & Mobile Sys Section Info: The goal of this course is to introduce students to advanced research topics in wireless networks and mobile communication systems. In each lecture, we will discuss one or two research papers that introduce new wireless designs, algorithms, protocols and applications. The papers are systems oriented and focus on practical challenges and solutions for building wireless and mobile systems. The course will cover the latest research topics including the Internet of Things, cross layer design, interference management, multi-antenna systems, distributed wireless systems, network coding, backscatter communication, full-duplex radios, wireless localization and sensing, wireless security, wireless charging… Student will also learn how to design and build wireless systems through a research oriented course project that focuses on implementation aspects of practical systems. Prerequisites: Maturity in understanding of computer networking and digital communications. At least one of the following courses or an equivalent: ECE 438 (Communication Networks), ECE 439 (Wireless Networks), ECE 361/461 (Digital Communications), ECE 463 (Digital Communications Lab), ECE 459 (Communications I).
72474	Online	HPN	12:30PM -1:50PM	TR	n.a.	Mittal, R	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: High-Speed/Progrmable Networks Section Info: The ever-increasing demand for higher performance, new functionality, and flexibility has given rise to radical new designs for networking infrastructure, that not only unleash exciting new opportunities, but also challenge conventional wisdom. The goal of this course is to introduce students to such recent research and industrial advancements in networking. In each lecture, we will discuss one or two recent papers that propose (or use) unconventional new designs for network stack, network interface cards, or switches. The papers are systems oriented, focusing on practical challenges associated with designing and implementing such network systems, and cover latest topics such as programmable switches, kernel-bypass networking, RDMA, and smart NICs. Prerequisites : ECE/CS 438 (Communication Networks).
73417	Online	ICM	12:30PM -1:50PM	TR	n.a.	Hu, B	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Interplay-Ctlr & Mchn Learning Section Info: Interplay between Control and Machine Learning. Advanced graduate course focuses on interplay between control and machine learning. The first half of the course focuses on tailoring control tools to study algorithms in large-scale machine learning. In the second half of the course, students will study how to combine reinforcement learning and model-based control methods for control design problems. The following topics will be covered: empirical risk minimization; first-order methods for large-scale machine learning; stochastic optimization; dissipation inequality; jump system theory; Lur’e-Postnikov type Lyapunov functions; integral quadratic constraints; KYP Lemma; graphical interpretations for optimization methods; implicit bias; neural tangent kernel and adaptive control; control-oriented analysis tools for temporal difference learning and Q-learning; reinforcement learning for linear quadratic regulator (LQR) problems; learning model predictive control for iterative tasks; zeroth-order optimization and evolutionary strategies; policy gradient for robust control (global convergence and implicit bias); adversarial reinforcement learning; data-driven control of large-scale switching systems; iterative learning control; imitation learning for control; regularization of model-free control via prior model-based design; constrained policy optimization. Prerequisite: ECE 515. ECE 534 and ECE 490 are recommended, but not required.
56132	Lecture	JK	2:00PM -3:20PM	TR	1015 Electrical & Computer Eng Bldg	Kim, J	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Intro to Humanoid Robotics Section Info: The goal of this course is to introduce students to knowledge and advanced research topics in humanoid robotics and legged locomotion area. In the first 4 weeks, the lectures will cover basic knowledge including humanoid systems, kinematics, and simple models. In the 5th and 6th weeks, a toy-size robot and simulation tools will be introduced for assignments and the final project. Starting at week 7, students will learn about legged locomotion and how to design legged locomotion controllers for 5 weeks. In the 11th and 12th weeks, we will discuss methods to capture human motions and students will capture their motions using motion capture devices. Also, the lectures will cover how to retarget the captured motions (or other data from user interface) to actual robots. Students will be asked to submit a proposal for the final project using the assigned robot or simulation tools in the 9th week, and the final project presentations will be in the 15th week. Successful projects may be run on a real, human-sized robot, THORMANG. Prerequisite: One of the following courses: ECE 470 (Introduction to Robotics, ME 445, AE 482) or ECE 489 (Robot Dynamics and Control, ME 446, GE 422). Restriction(s): Restricted to Graduate - Urbana-Champaign.
75098	Online	JKO	2:00PM -3:20PM	TR	n.a.	Kim, J	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Intro to Humanoid Robotics Section Info: The goal of this course is to introduce students to knowledge and advanced research topics in humanoid robotics and legged locomotion area. In the first 4 weeks, the lectures will cover basic knowledge including humanoid systems, kinematics, and simple models. In the 5th and 6th weeks, a toy-size robot and simulation tools will be introduced for assignments and the final project. Starting at week 7, students will learn about legged locomotion and how to design legged locomotion controllers for 5 weeks. In the 11th and 12th weeks, we will discuss methods to capture human motions and students will capture their motions using motion capture devices. Also, the lectures will cover how to retarget the captured motions (or other data from user interface) to actual robots. Students will be asked to submit a proposal for the final project using the assigned robot or simulation tools in the 9th week, and the final project presentations will be in the 15th week. Successful projects may be run on a real, human-sized robot, THORMANG. Prerequisite: One of the following courses: ECE 470 (Introduction to Robotics, ME 445, AE 482) or ECE 489 (Robot Dynamics and Control, ME 446, GE 422).
65005	Online	KSH	12:30PM -1:50PM	TR	n.a.	Haran, K	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Topics in Electromechanics Section Info: Technologies like advanced materials, new manufacturing processes and power electronics can open up the design space for new electrical machines in the transportation, energy, and industrial sector. To take full advantage of these developments, engineers need to have a good understanding of the complex trade-offs encountered in electric machine design that span multiple disciplines. They must also be comfortable with both analytical and numerical tools, and how to effectively apply these to obtain the best results. This course will attempt to prepare engineers for this opportunity by focusing on practical design considerations in electric machines. Fundamental principles of energy conversion are first reviewed. Basic design rules, analytical formulae and the use of numerical design tools will then be introduced, and experience will be gained through a hands-on design project. Prerequisite: ECE 431. Restriction(s): Restricted to Graduate - Urbana-Champaign.
75613	Laboratory Online Lecture	MAV MAV	ARRANGED 12:30PM -1:45PM	n.a. WF	Location Pending n.a.	Forsyth, D Forsyth, D	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Methods for Bld Auton Vehicles Section Info: Vehicle time will be in person, please see sylabus or speak with your professor about regular meetings for this course. Content will be delivered online synchronously. This is restricted to MEng students. Restriction(s): Restricted to MENG:Elec & Computer Eng-UIUC.
72381	Online	NSG	11:00AM -12:20PM	TR	n.a.	Shanbhag, N	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Deep Learning in Hardware Section Info: This course will present challenges in implementing deep learning algorithms on resource-constrained hardware platforms at the Edge such as wearables, IoTs, autonomous vehicles, and biomedical devices. Fixed-point requirements of deep for deep neural networks and convolutional neural networks including the back-prop based training will be studied. Algorithm-to-architecture mapping techniques will be explored to trade-off energy-latency-accuracy in deep learning digital accelerators and analog in-memory architectures. Fundamentals of learning behavior, fixed-point analysis, architectural energy and delay models will be introduced in just-in-time manner throughout the course. Case studies of hardware (architecture and circuit) realizations of deep learning systems will be presented. Homeworks will include a mix of analysis and programming exercises in Python and Verilog leading up to a term project. Prerequisites: ECE 313 and 385.
40257	Online Lecture	ON1	11:00AM -12:20PM	TR	n.a.	Shanbhag, N	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Deep Learning in Hardware Section Info: Please note that this section is only for online, degree and non-degree students and the tuition rate is $1,110 per credit hour. Restriction(s): Restricted to Graduate - Urbana-Champaign. Restricted to MS: Civil Engr - Online - UIUC, MS:Industrial Engr Online-UIUC, MS:Mechanical Engineerng -UIUC, MS:Env Engr CivilEngr ONL-UIUC, MS:Electr & Computer Eng-UIUC, PHD:Electr & Computer Eng-UIUC, MS: Aerospace Engr-Online-UIUC, MENG:Engr:Energy Sys Onl-UIUC, NDEG:Grad Nondegree-CE-UIUC, MENG:Mech Engineering Onl-UIUC, MENG:Elec & Computer Eng-UIUC, MENG:Elec & Comp Eng ONL -UIUC, MENG:Bioeng:Gen Bioeng On-UIUC, MENG:Bioeng:Comp Gen Onl -UIUC, MENG:Bioeng:Bioinstr Onl -UIUC, MENG:Bioengr:Pharm ONL- UIUC, MENG:Engr:AeroSys Online- UIUC, or MENG:Engr:Plasma Online-UIUC.
75103	Online	RIO	12:30PM -1:50PM	TR	n.a.	Ilie, R	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: EM of Continuum Media Section Info: Electrodynamics of Continuum Media. This course is intended to engage graduate students interested in electrodynamics, remote sensing and space sciences in advanced topics and new areas of research. Successful graduate students in this research area require a breadth of knowledge in advanced electromagnetics, signal processing techniques, the interaction of fields and waves in a plasma environment. The breadth areas are well covered in the current ECE curriculum providing a firm foundation for students to build their research upon. However, there is currently no graduate-level course offered at UIUC specifically to give students exposure to the fundamental electrodynamics and plasma processes that are operative in the space environment surrounding the Earth. Prerequisites: ECE 452 or equivalent.
73943	Online	RKI	11:00AM -12:20PM	MW	n.a.	Iyer, R	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Dependable AI Systems Section Info: The emergence of AI systems and their ubiquitous adoption in automating tasks that involve humans in critical application domains (e.g., autonomous vehicles, medical assistants/devices, manufacturing, agriculture, and smart buildings) means that it is of paramount importance that we be able to place trust in these technologies. In a broad sense, a trustworthy AI system must be dependable (i.e., ensure safety, resilience, robustness, and security of its own and its operational environment) and reasonable (i.e., provide the reasoning behind produced decisions/actions). Indeed, the absence of such features not only makes people reluctant to deploy technology in the field despite successful demonstrations, but also leaves systems vulnerable to security hacks and crashes that ultimately impact human safety. As Schneir states, traditionally, computers have only outperformed humans at speed, scale, and scope whereas humans excelled at thinking, reasoning, adapting, and understanding. However, artificial intelligence (AI) changes the landscape, where computers can now infer relationships, discover patterns, react, and adapt to changes while keeping its strength in speed, scale, and scope. While AI application long remained withheld for its high computational cost, recent advances in computing (high speed network, big data storage, computation speed) led to a new era of smart systems. AI has successfully demonstrated possibility in accelerating and automating processes that were primarily a job of human actors (e.g., driving, diagnosis, or navigating). However, the proximity to and direct interaction with humans (and our surrounding environment) raises an issue of trustworthiness. This course addresses the challenge of design, implementation, and validation of dependable AI systems by providing students with an opportunity to study new challenges imposed by classic as well as emerging AI algorithms, decision making under uncertainty, and the consequent safety, reliability, and security issues. In this course, students will have an opportunity to work on real-world applications in transportation, health, and systems domain while interacting with domain experts.
72446	Online	SG	3:30PM -4:50PM	TR	n.a.	Gupta, S	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Learning-Based Robotics Section Info: This course will introduce students to recent developments in the area of learning-based robotics. The course will start with an overview of background material from relevant subfields: computer vision, machine learning, robotics and control theory. Next, we will discuss advanced techniques for learning policies for robots, such as model-free reinforcement learning with function approximators, model learning, model-based RL with learned models, imitation learning, inverse reinforcement learning, self-supervised learning, exploration, and hierarchical reinforcement learning. These advanced techniques will be covered via recent research papers that develop and validate them. The course will conclude with case-studies on robotic navigation, and manipulation from recent papers. Project work as part of the course will provide a flavor of research in this new emerging area. Prerequisites: Understanding of basic concepts in artificial intelligence, and machine learning. Students must have taken at least one of the following courses: ECE 448 / CS 440 (Introduction to Artificial Intelligence), ECE 544NA (Pattern Recognition), ECE 549 / CS 543 (Computer Vision).
70563	Online	WZ	9:30AM -10:50AM	TR	n.a.	Zhu, W	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: 2D Material Electr & Photonics Section Info: 2D Material Electronics and Photonics. Two-dimensional (2D) material characterizations, 2D electronic devices, 2D optical devices. Prerequisite: ECE 340 or equivalent.
37025	Lecture	YZ	3:30PM -4:50PM	TR	3017 Electrical & Computer Eng Bldg	Zhao, Y	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Light-Matter Interaction Section Info: Topic: In this course, we will learn about the light-matter interactions from the fundamentals, starting with the classical interpretation of materials, such as dipole oscillators, linear optical properties, and dispersion relations. We will study nonlinear contributions and understand how this leads to the generation of new frequencies and irradiance-dependent refractive index and absorption, and consider how quantum mechanics modifies our picture of the optical properties. As applications of these fundamental knowledge, we will discuss the design principles and characterization techniques of various metamaterials for imaging and sensing. Prerequisite: ECE 350, one of ECE 460 or PHYS 402, or consent of the instructor
75104	Online	YZO	3:30PM -4:50PM	TR	n.a.	Zhao, Y	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Light-Matter Interaction Section Info: In this course, we will learn about the light-matter interactions from the fundamentals, starting with the classical interpretation of materials, such as dipole oscillators, linear optical properties, and dispersion relations. We will study nonlinear contributions and understand how this leads to the generation of new frequencies and irradiance-dependent refractive index and absorption, and consider how quantum mechanics modifies our picture of the optical properties. As applications of these fundamental knowledge, we will discuss the design principles and characterization techniques of various metamaterials for imaging and sensing. Prerequisite: ECE 350, one of ECE 460 or PHYS 402, or consent of the instructor
73594	Online	ZP	9:00AM -10:20AM	TR	n.a.	Peng, Z	Part of Term: 1 Date Range: 08/24/20-12/09/20 Credit: 4 hours Section Title: Wave Physics in Wireless Comm Section Info: Wave Physics in Wireless Communication. Electromagnetic theory provides the fundamental physics of wireless communications. In this graduate course, we will discuss the wave physics of information transmission in diverse and complex environments. Students will learn physics-based modelling of the wireless system through electromagnetic theory, which, in turn, will appreciate the formulation and development of commensurate communication theory. Prerequisites: ECE 350 or ECE 520; ECE 361; ECE 454 or ECE 577; or consent of the instructor.