The objective of this course is to provide the basic concepts and algorithms required to develop mobile robots that act autonomously in complex environments. The main emphasis is on mobile robot locomotion and kinematics, control, sensing, localization, mapping, path and motion planning. Prerequisites: APMA 2130, APMA 3080, APMA 3100, and CS 2130 or equivalent. 

This class discusses solid state devices that are used for renewable energy application. While we will provide a general overview of most new and interesting technologies via lectures, discussions, and research presentations, we will focus on the detailed technical aspects of few devices namely: solar cells, thermionic devices, thermoelectric devices, solar thermal (CSPs), and batteries.

This course introduces photovoltaics and solar energy generation and gives an overview of the subject. The course will describe the operation of photovoltaic cells and efficiency improvements, industrial processes, solar thermal power generation, thin films, and nanomaterials for photovoltaics and future technologies.  Prerequisites: ECE 2200 or PHYS 2415 and APMA 2130 or MATH 3250.

Quantum electronics, the study of light and matter interaction, has become the cornerstone in many areas of optical science and technology. This course reviews the principles of lasers then introduces the generalized nonlinear wave equations. This course will cover typical nonlinear effects and their applications in telecommunication, ultrafast laser, quantum computing/information and chemical/bio spectroscopy.  Prerequisite: ECE 3209.

Analyzes the measurement and behavior of high-frequency circuits and components; equivalent circuit models for lumped elements; measurement of standing waves, power, and frequency; use of vector network analyzers and spectrum analyzers; and computer-aided design, fabrication, and characterization of microstrip circuits. Corequisite: ECE 5260 or instructor permission.

This course explores the intricacies of AI hardware, including the current landscape and anticipating the necessary developments in response to AI's rapid growth and widespread integration across all computing tiers. Through this exploration, you will gain an understanding of both the existing technologies and the future challenges in AI hardware design and implementation. Prerequisites: ECE 2330 or CS 2130. 

This course explores advanced embedded systems topics such as design and validation of embedded computing systems, embedded C programming, real-time operating systems for microcontrollers, safety and security, cyber-physical systems, Internet of Things, and robotics. The course includes hands-on experience, paper presentations, and discussions.  Prerequisite: ECE 3430

Focuses on the techniques for designing and analyzing dependable computer-based systems. Topics include fault models and effects, fault avoidance techniques, hardware redundancy, error detecting and correcting codes, time redundancy, software redundancy, combinatorial reliability modeling, Markov reliability modeling, availability modeling, maintainability, safety modeling, trade-off analysis, design for testability, and the testing of redundant digital systems. Cross-listed as CS 4434. Prerequisite: ECE 3430 or CS 3330 and APMA 3100 or APMA 3110.

A fourth-level undergraduate course covering a topic not normally covered in the course offerings. The topic usually reflects new developments in the electrical and computer engineering field. Offering is based on student and faculty interests.

Topics include the design and analysis of analog integrated circuits; feedback amplifier analysis and design, including stability, compensation, and offset-correction; layout and floor-planning issues associated with mixed-signal IC design; selected applications of analog circuits such as A/D and D/A converters, references, and comparators; extensive use of CAD tools for design entry, simulation, and layout; and the creation of an analog integrated circuit design project. Prerequisites: ECE 3660 or instructor permission.