ECE 498

Spring 2026 All Classes

All Classes

Special Topics in ECE

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Credit: 1 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.

0 to 4 undergraduate hours. 0 to 4 graduate hours. May be repeated in the same or separate terms if topics vary.

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ECE 498 class schedule data for spring 2026
CRN	Type	Section	Time	Day	Location	Instructor	Section Details
33961	Laboratory Lecture	AB3 AB3	10:00AM -12:50PM 11:00AM -12:30PM	F TR	4024 Electrical & Computer Eng Bldg 3013 Electrical & Computer Eng Bldg	Banerjee, A Maheshwari, A Banerjee, A Maheshwari, A	Part of Term: 1 Date Range: 01/20/26-05/06/26 Credit: 4 hours Section Title: Power Electronics Control Section Info: This course aims to educate students in the detailed modeling, average-value modeling, thermal considerations, and control design of power electronic converters. Part 1 addresses energy storage and switch components and modeling techniques in major classes of power converters. Detailed and average-value modeling and control concepts are presented. Part 2 focuses on PWM strategies, controller designs, and their control impact. Part 3 considers grid-tied applications and nonlinear control methods for power converters. Material on transient thermal models will connect the impact of controls on thermal effects. The course includes a final project for experience in the design, control, and simulation of power converters for an electric vehicle application. Prerequisites: ECE 464 (required) and ECE 486 (recommended). Restriction(s): Restricted to BS:Computer Engineering -UIUC, BS:Electrical Engineerng -UIUC, MS:Electr & Computer Eng-UIUC, or PHD:Electr & Computer Eng-UIUC.
77294	Lecture	BH3	9:30AM -10:50AM	TR	4025 Campus Instructional Facility	Hu, B	Part of Term: 1 Date Range: 01/20/26-05/06/26 Credit: 3 hours Section Title: LLM Reasoning for Engineering Section Info: This course explores the cutting-edge intersection of large language models (LLMs) and machine reasoning, with a specific emphasis on their transformative potential in engineering disciplines. Modern LLMs, such as GPT, Claude, Gemini, and Llama, are foundation models with vast knowledge bases. These models have demonstrated significant potential in solving complex reasoning and coding tasks. But what do they offer engineers? This course addresses that question by examining LLM reasoning and its application to a range of engineering fields, including control systems, circuit design, power systems, signal processing, aerospace, and transportation engineering. Key topics include: How do LLMs function? How can they be leveraged for reasoning? What is the quality of LLM-generated reasoning for various engineering tasks? How much can we trust the engineering design solutions from LLMs? What are the fundamental limitations of LLM reasoning for engineering? What engineering benchmarks exist for evaluating LLM capabilities? How can LLM reasoning be integrated with domain-specific tools to create LLM agents? Finally, what are the future directions for building even more powerful reasoning machines for engineering applications? In addition to lectures, students will present the latest research papers, and team up to work on course projects. Restriction(s): Restricted to Undergrad - Urbana-Champaign.
77295	Lecture	BH4	9:30AM -10:50AM	TR	4025 Campus Instructional Facility	Hu, B	Part of Term: 1 Date Range: 01/20/26-05/06/26 Credit: 4 hours Section Title: LLM Reasoning for Engineering Section Info: This course explores the cutting-edge intersection of large language models (LLMs) and machine reasoning, with a specific emphasis on their transformative potential in engineering disciplines. Modern LLMs, such as GPT, Claude, Gemini, and Llama, are foundation models with vast knowledge bases. These models have demonstrated significant potential in solving complex reasoning and coding tasks. But what do they offer engineers? This course addresses that question by examining LLM reasoning and its application to a range of engineering fields, including control systems, circuit design, power systems, signal processing, aerospace, and transportation engineering. Key topics include: How do LLMs function? How can they be leveraged for reasoning? What is the quality of LLM-generated reasoning for various engineering tasks? How much can we trust the engineering design solutions from LLMs? What are the fundamental limitations of LLM reasoning for engineering? What engineering benchmarks exist for evaluating LLM capabilities? How can LLM reasoning be integrated with domain-specific tools to create LLM agents? Finally, what are the future directions for building even more powerful reasoning machines for engineering applications? In addition to lectures, students will present the latest research papers, and team up to work on course projects. Restriction(s): Restricted to Graduate - Urbana-Champaign.
33960	Lecture	RCU	4:00PM -5:20PM	MW	1013 Electrical & Computer Eng Bldg	Roy Choudhury, R	Part of Term: 1 Date Range: 01/20/26-05/06/26 Credit: 3 hours Section Title: Deep Generative Models Restriction(s): Restricted to Undergrad - Urbana-Champaign.
76192	Lecture	RK	8:00AM -9:20AM	TR	Location Pending	Kumar, R	Part of Term: 1 Date Range: 01/20/26-05/06/26 Credit: 3 hours Section Title: Concepts in Computer Org & Des Section Info: This course is an intensive introduction to the fundamentals of computer architecture. Relying heavily upon the elementary principles taught in ECE 220, and ECE 385, we will discuss the basic design, or architecture, of computing hardware. Computer systems involve architecture design at many levels. We will focus on the instruction set architecture (ISA) level (the interface between the software and computing hardware) and the microarchitecture level (the computing hardware itself). We will examine to some extent, the level above the instruction set (the programming language level) and the level below the microarchitecture (the logic gate level) in order to deepen our understanding of computing systems. Prerequisites: ECE385 Restriction(s): Restricted to MENG:Elec & Computer Eng-UIUC.
33964	Lecture	SR	1:00PM -2:20PM	MWF	3081 Electrical & Computer Eng Bldg	Rakheja, S	Part of Term: 1 Date Range: 01/20/26-05/06/26 Credit: 4 hours Section Title: Model & Simulation RF Devices Section Info: High Electron Mobility Transistors (HEMTs) and their applications to RF power amplification. Students will learn the fundamentals of compact model development in Verilog-A, simulate HEMTs in Synopsys Sentaurus Device (SDevice) to quantify the DC, transient, and S-parameter response of HEMTs, analyze thermal behaviors of HEMTs and impact on high-frequency performance, and use SDevice simulations to calibrate the compact models, and eventually run large-scale RF simulations in Keysight ADS. The course will introduce students to industry standard modeling and simulation tools, while emphasizing the key physics of high-frequency devices. Guest lectures from technical experts at leading device and circuit simulation software companies will help students connect the dots from theoretical concepts to practical demonstrations of RF devices and circuits.