ECE 598

Fall 2026 Part of Term 1

Part of Term 1
Aug 24-Dec 9

Special Topics in ECE

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 2026
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
80794	Lecture-Discussion	A	2:00PM -3:20PM	TR	1015 Electrical & Computer Eng Bldg	Gallo, F	Availability: Closed Part of Term: 1 Date Range: 08/24/26-12/09/26 Credit: 3 hours Section Title: Public Speaking for Eng Grad Section Info: This course focuses on the oral communication skills engineering graduate students need to be successful. Topics include presentation organization and delivery (stance, gestures, volume, energy, articulation, and pronunciation), audience analysis, visual aids, nonverbal behavior, self-introductions in the form of various elevator pitches, answering questions at conferences, and small talk for networking purposes. The majority of the class time is devoted to communication practice. Restriction(s): Restricted to Graduate - Urbana-Champaign.
47508	Lecture	CR	8:30AM -9:50AM	MW	3017 Electrical & Computer Eng Bldg	Hanumolu, P Radhakrishnan, C	Availability: Open (Restricted) Part of Term: 1 Date Range: 08/24/26-12/09/26 Credit: 4 hours Section Title: Digitally Asst Circuit Design Section Info: Signal Processing in circuit design, Quantization, ADC, ADC specifications and non-idealities, Least mean square estimation, Adaptive signal processing, High speed communication links non-idealities, equalizers, decision feedback equalization, oversampling, noise-shaping, delta-sigma DAC, non-idealities in DACs, digital correction of delta-sigma DAC non-idealities. Prerequisites: ECE 310, ECE 342 Restriction(s): Restricted to Graduate - Urbana-Champaign. Not intended for MENG:Elec & Comp Eng ONL -UIUC.
80770	Lecture	DA	12:30PM -1:50PM	TR	3013 Electrical & Computer Eng Bldg	Alabi, D	Availability: CrossListOpen (Restricted) Part of Term: 1 Date Range: 08/24/26-12/09/26 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.
56132	Lecture	JK	5:00PM -6:20PM	TR	4070 Electrical & Computer Eng Bldg	Kim, J	Availability: Closed Part of Term: 1 Date Range: 08/24/26-12/09/26 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.
40256	Lecture	RC	5:00PM -6:20PM	TR	2015 Electrical & Computer Eng Bldg	Chu, R	Availability: Open (Restricted) Part of Term: 1 Date Range: 08/24/26-12/09/26 Credit: 4 hours Section Title: High-Speed & High-Power Field Section Info: This course discusses high-speed and high-power field-effect transistors. Students will gain an in-depth understanding of design and analysis of state-of-the-art transistor technology used in RF and power electronics. Key topics include frequency-domain analysis for RF transistors, time-domain analysis for power transistors, and choice of materials and device structures used for each application. Prerequisites: ECE340 or equivalent Restriction(s): Restricted to Graduate - Urbana-Champaign.
40258	Online	RCR	ARRANGED	n.a.	n.a.	Roy Choudhury, R	Availability: Open (Restricted) Part of Term: 1 Date Range: 08/24/26-12/09/26 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 MENG:Elec & Comp Eng ONL -UIUC.
81006	Lecture	RE	11:00AM -12:20PM	TR	4070 Electrical & Computer Eng Bldg	Engelken, R	Availability: Open (Restricted) Part of Term: 1 Date Range: 08/24/26-12/09/26 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.
43841	Lecture	YB	4:00PM -5:20PM	MW	3015 Electrical & Computer Eng Bldg	Baryshnikov, Y	Availability: CrossListOpen (Restricted) Part of Term: 1 Date Range: 08/24/26-12/09/26 Credit: 4 hours Section Title: Intro to Topological Data Section Info: This course provides a rigorous, ground-up foundation in Topological Data Analysis (TDA) tailored for engineering graduate students. It bridges deterministic topology — algebraic topology, to be precise, — with spatial statistics, focusing on uncertainty quantification, Gaussian Random Fields (GRFs), and robust feature extraction using persistent homology. The course emphasizes theoretical guarantees and probabilistic modeling over black-box machine learning integration. Good knowledge of analysis, linear algebra (MATH257 should suffice) and probability theory (at least ECE313) will be expected. Restriction(s): Restricted to Graduate - Urbana-Champaign.
37033	Lecture	YH	9:30AM -10:50AM	TR	2015 Electrical & Computer Eng Bldg	Hu, Y	Availability: Open (Restricted) Part of Term: 1 Date Range: 08/24/26-12/09/26 Credit: 3 hours Section Title: Network DDoS Defense Section Info: This graduate-level course covers volumetric DDos attacks from the 1988 Morris Worm to the present, as well as a variety of academic approaches for mitigating such attacks. The goal of this class is for students to understand the tradeoffs of computational complexity, end-point deployment, and router deployment. Prerequisites: ECE/CS 438 Restriction(s): Restricted to Graduate - Urbana-Champaign.
72081	Online Lecture	ZZ	3:30PM -4:50PM	TR	n.a.	Zhao, Z	Availability: Pending Part of Term: 1 Date Range: 08/24/26-12/09/26 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. Restriction(s): Restricted to Graduate - Urbana-Champaign.