ECE 598

Fall 2025 Part of Term 1

Part of Term 1
Aug 25-Dec 10

Special Topics in ECE

SHOW FINAL EXAM SCHEDULE

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.

My Favorites

My Schedule

Section Status updates every 10 minutes.

ECE 598 class schedule data for fall 2025
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
79795	Lecture	AL1	5:00PM -7:50PM	M	2015 Electrical & Computer Eng Bldg	Nicol, D	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Trust Critical Infrastructure Section Info: This course will focus on the trustworthiness of computer and communications technology used to control critical infrastructures such as the power grid, water systems, and manufacturing. It introduces the operational technology (OT) used in these systems and in the supervisory control and data acquisition (SCADA) networks that use it. It introduces hardware, software, and communication protocols found in these systems, and gives students experience with programming and monitoring them using open-source state-of-the-art simulators of OT systems. The course includes material on operational and regulatory requirements placed on these systems, with respect to processes used to establish and validate safety and cyber-security. It also includes material on “consequence-driven cyber-informed engineering”, which lays out principles for designing critical infrastructures from the beginning of the lifecycle to be trustworthy against failures and cyber-attacks. Restriction(s): Restricted to Graduate - Urbana-Champaign.
80770	Lecture	DA	9:30AM -10:50AM	TR	2015 Electrical & Computer Eng Bldg	Alabi, D	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Info-Theoretic Cryptography Section Info: we will study foundational and recent work on the use of information theory to design and analyze cryptographic protocols. In the first half of the course, we will study privacy attacks that motivate strong privacy and security definitions. Then, we will explore the basics of differential privacy. In the second half, we will study some core works on zero-knowledge proofs and watermarking of generative models. Restriction(s): Restricted to Graduate - Urbana-Champaign.
56288	Lecture	HRI	11:00AM -12:20PM	MW	3015 Electrical & Computer Eng Bldg	Driggs-Campbell, K Schreiber, A	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Human Robot Interaction 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; An introductory robotics course (e.g., ECE470 (Introduction to Robotics), ABE424 (Principles of Mobile Robotics), ECE484 (Principles of Safe Autonomy)); ECE448/CS440 (Introduction to Artificial Intelligence) or equivalent; familiarity with controls (e.g., ECE515) and optimization (e.g., ECE490) is recommended, but not required Restriction(s): Restricted to Graduate - Urbana-Champaign.
80819	Lecture	IS	2:00PM -3:20PM	MW	2015 Electrical & Computer Eng Bldg	Shomorony, I	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Info Theory High-Dimensional Section Info: This course will expose students to a variety of theoretical tools that are useful in the context of high-dimensional probability and statistics. Students will learn to analyze the behavior of high-dimensional random vectors and matrices, and to utilize these insights to study statistical tasks motivated by large-scale datasets. We will explore how techniques from information theory can be used to derive converse results, and how techniques from random matrix theory and graph theory can be used to design estimators with theoretical guarantees. Topics will include information measures and inequalities, concentration inequalities, information-theoretic lower bounding techniques, sparse signal recovery, large-scale regression via leverage scores, inference tasks on large graphs, and dimensionality reduction. Prerequisite: Main prerequisite is ECE 534 (Random Processes) or equivalent course. ECE 563 (Information Theory) or some prior exposure to information theory thinking is recommended but not required. Restriction(s): Restricted to Graduate - Urbana-Champaign.
56132	Lecture	JK	5:00PM -6:20PM	TR	3015 Electrical & Computer Eng Bldg	Kim, J	Part of Term: 1 Date Range: 08/25/25-12/10/25 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.
80780	Lecture	RCG	4:00PM -5:20PM	MW	4025 Campus Instructional Facility	Roy Choudhury, R	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Deep Generative Models Section Info: This course develops the foundations of generative models, covering the four main pillars: variational inference (VAE), diffusion models (Diffusion), generative adversarial networks (GAN), and normalizing flows (Flow). Although mostly mathematical, the treatment of topics will be from first principles, often revisiting core undergraduate material (in linear algebra, probability, optimization), and visualizing them in the context of neural networks. Each topic will close with recent research papers and their corresponding applications. Please visit the course website here: https://rrc-uiuc.notion.site/gen-models-fa25 Restriction(s): Restricted to Graduate - Urbana-Champaign.
81006	Lecture	RE	11:00AM -12:20PM	TR	4070 Electrical & Computer Eng Bldg	Engelken, R	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Dynamical Syst & Neural Netwrk Section Info: This graduate course explores the interplay between dynamical systems theory and neural networks (artificial and biological). Students analyze how stability, attractors, bifurcations, and chaos govern behavior, learning, and computation. Covers foundational discrete/continuous-time dynamical systems, applied to analyzing machine learning models (including training dynamics) and modeling complex neural circuits (rate-based and spiking). Emphasis is on hands-on computational analysis and developing theoretical understanding. The course culminates in a research project applying these interdisciplinary concepts. Restriction(s): Restricted to Graduate - Urbana-Champaign.
56456	Lecture	RI	12:30PM -1:50PM	TR	3020 Electrical & Computer Eng Bldg	Ilie, R	Part of Term: 1 Date Range: 08/25/25-12/10/25 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. Restriction(s): Restricted to Graduate - Urbana-Champaign.
72081	Online Lecture	ZZ	3:30PM -4:50PM	TR	n.a.	Zhao, Z	Part of Term: 1 Date Range: 08/25/25-12/10/25 Credit: 4 hours Section Title: Diffusion Flow Matching Models Section Info: This course covers state-of-the-art techniques in generative modeling, focusing on diffusion and flow matching models. Students will gain a thorough understanding of the theory and practical applications of these models for generating high-dimensional data. Key topics will include the basics of generative models, the mathematical principles behind diffusion and flow-based methods, and real-world applications. The course will also prioritize hands-on learning through coding assignments and reviews of current research literature. Prerequisites: Knowledge of machine learning, linear algebra, calculus, and probability, python programming. ECE 313, CS 446/ECE449 or instructor approval.