This honors colloquium will be project and team-oriented. The project will have some connection to the broad field of signals and systems including, but not restricted to, the topic areas: Digital communication systems, Digital signal and image processing, Computer networks/communications, Feedback control systems. The projects will be coding and simulation-based, using MATLAB, Python, and Simulink. Projects with a hardware component will also be considered on an individual basis.

This course introduces the students to the design of embedded systems with a focus in unprecedented cyber-physical systems and internet of things applications. It takes a holistic approach to design end-to-end systems by addressing challenges at the hardware, software, and network layers of the stack. Special attention is paid to design trustworthy systems for applications running on commodity platforms and operating systems.

This course introduces the students to the design of embedded systems with a focus in unprecedented cyber-physical systems and internet of things applications. It takes a holistic approach to design end-to-end systems by addressing challenges at the hardware, software, and network layers of the stack. Special attention is paid to design trustworthy systems for applications running on commodity platforms and operating systems

The course will focus on advanced analytical tools for modeling and analysis of modern networks including: network optimization, queuing theory, game theory, mean field theory, and matching theory. Examples of resource allocation problems in ultra-reliable low-latency networks, virtual networks, multi-access edge networks, 5G/6G networks will be discussed by using these tools.

Supplemental course for students who have completed ECE 242 (Data Structures and Algorithms) or COMPSCI 187 (Programming with Data Structures). Homework assignments and projects within Fast Fourier Transforms and Algorithms needed for Machine Learning. Python required.

Data structures course using the Python programming language. Basic mathematical, logical, and programming concepts relevant to description and manipulation of information structures such as arrays, lists, trees, graphs, and files; the underlying principles of algorithm design and analysis applied to sorting and searching problems.

Data structures course using the Python programming language. Basic mathematical, logical, and programming concepts relevant to description and manipulation of information structures such as arrays, lists, trees, graphs, and files; the underlying principles of algorithm design and analysis applied to sorting and searching problems.

Data structures course using the Python programming language. Basic mathematical, logical, and programming concepts relevant to description and manipulation of information structures such as arrays, lists, trees, graphs, and files; the underlying principles of algorithm design and analysis applied to sorting and searching problems.

Analysis of circuit response to sinusoidal excitation; phasor analysis, impedance, admittance, power, frequency response, transfer functions, Bode plots, filters. Linear analysis of nonlinear circuits; DC biasing of 3 terminal devices, small signal analysis, single device amplifiers, small signal gain and frequency response.