ECE 598

Fall 2021 All Classes

All Classes

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 2021
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
37027	Online Lecture	ARO	9:30AM -10:50AM	TR	n.a.	Stillwell, A	Part of Term: 1 Date Range: 08/23/21-12/08/21 Credit: 4 hours Section Title: Advanced Power Electronics Section Info: Power electronics are a key enabling technology in renewable distributed energy resources in the electricity grid, vehicle electrification, mobile devices, low-power Internet of Things devices, and data centers. This course covers advanced topics in power electronics, including converter topologies, soft-switching and resonant converters, control, inductor and transformer design, and hybrid switched capacitor topologies. Application examples from solar, electric machine drives, and power-supply on a chip will be provided to motivate each topic. Prerequisite: ECE 464 or equivalent. Restriction(s): Restricted to Graduate - Urbana-Champaign.
49452	Lecture	ARS	9:30AM -10:50AM	TR	2015 Electrical & Computer Eng Bldg	Stillwell, A	Part of Term: 1 Date Range: 08/23/21-12/08/21 Credit: 4 hours Section Title: Advanced Power Electronics Section Info: Power electronics are a key enabling technology in renewable distributed energy resources in the electricity grid, vehicle electrification, mobile devices, low-power Internet of Things devices, and data centers. This course covers advanced topics in power electronics, including converter topologies, soft-switching and resonant converters, control, inductor and transformer design, and hybrid switched capacitor topologies. Application examples from solar, electric machine drives, and power-supply on a chip will be provided to motivate each topic. Prerequisite: ECE 464 or equivalent. Restriction(s): Restricted to Graduate - Urbana-Champaign.
51575	Lecture	BC	12:30PM -1:50PM	TR	3013 Electrical & Computer Eng Bldg	Cunningham, B Li, N	Part of Term: 1 Date Range: 08/23/21-12/08/21 Credit: 4 hours Section Title: Advanced Biosensors Section Info: Fundamental principles at the intersection of engineering, biology, and data science that are pushing the forefront of biosensor technology used for diagnostics and life science research. Prerequisite: ECE/BIOE 416 (Biosensors) Restriction(s): Restricted to Graduate - Urbana-Champaign.
37033	Online Lecture	BCO	12:30PM -1:50PM	TR	n.a.	Cunningham, B Li, N	Part of Term: 1 Date Range: 08/23/21-12/08/21 Credit: 4 hours Section Title: Advanced Biosensors Section Info: Fundamental principles at the intersection of engineering, biology, and data science that are pushing the forefront of biosensor technology used for diagnostics and life science research. Prerequisite: ECE/BIOE 416 (Biosensors) Restriction(s): Restricted to Graduate - Urbana-Champaign.
56132	Lecture	JK	2:00PM -3:20PM	TR	3081 Electrical & Computer Eng Bldg	Gim, K Kim, J	Part of Term: 1 Date Range: 08/23/21-12/08/21 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.
37034	Online Lecture	JKO	2:00PM -3:20PM	TR	n.a.	Gim, K Kim, J	Part of Term: 1 Date Range: 08/23/21-12/08/21 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.
72498	Lecture	MS	12:30PM -1:50PM	TR	3020 Electrical & Computer Eng Bldg	Huang, J	Part of Term: 1 Date Range: 08/23/21-12/08/21 Credit: 4 hours Section Title: Adv Memory & Storage Systems Section Info: In this course, we will discuss advanced techniques for building memory and storage systems. The course will cover a variety of latest research topics centered around the memory and storage systems that include the new and emerging hardware architecture, memory/storage systems software, memory-centric applications, near-storage computing, rack-scale storage, storage security and reliability, mobile/wearable/IoT storage, and storage in large-scale data centers. Through this course, students will learn not only the fundamental concepts of memory and storage systems via the lecture materials, but also the hands-on experience of building and evaluating a memory/storage-centric system via projects. Prerequisites: One of the following: ECE 391, ECE 411, or ECE 511
73943	Lecture	RKI	11:00AM -12:20PM	MW	2017 Electrical & Computer Eng Bldg	Choudhary, A Iyer, R	Part of Term: 1 Date Range: 08/23/21-12/08/21 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. Restriction(s): Restricted to Graduate - Urbana-Champaign.
72446	Online Lecture	SG	9:30AM -10:50AM	TR	n.a.	Gupta, S	Part of Term: 1 Date Range: 08/23/21-12/08/21 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). Restriction(s): Restricted to Graduate - Urbana-Champaign.
75799	Online Lecture	SGO	9:30AM -10:50AM	TR	n.a.	Gupta, S	Part of Term: 1 Date Range: 08/23/21-12/08/21 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). Restriction(s): Restricted to Graduate - Urbana-Champaign.
37025	Online Lecture	YZ	11:00AM -12:20PM	TR	n.a.	Zhao, Y	Part of Term: 1 Date Range: 08/23/21-12/08/21 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 Restriction(s): Restricted to Graduate - Urbana-Champaign.