Electrical Engineering

This course introduces the following topics: operating-system structure, processes, threads, CPU scheduling, process synchronization, deadlocks, main memory, virtual memory, and file-system interface. Students attend two UNIX tutorials. Prerequisite: a course in computer organization and structure.

This course provides an in-depth treatment of fundamental topics of network design based on the Internet protocol stack model. It introduces how networks work through understanding of the underlying principles of sound network design. This course covers topics including network requirements, architecture, protocol stack models, Ethernet Token Ring, Wireless, and FDDI networks, bridges, switching and routing in IP and ATM networks, and internetworking. Apart from learning the concepts in networks, the students gain expertise in analyzing and designing networking protocols through mini-projects. The course requires students to take prerequisites.

This course covers the principles and applications of electrical engineering. Topics include resistive circuits; inductance and capacitance; rransients; steady-state sinusoidal analysis; frequency response, bode plots, and resonance; amplifiers; operational amplifiers; diodes; and logic circuits.

This course covers the following topics: fundamentals, linear time-invariant systems, Fourier series and Fourier transform, discrete Fourier transform, time and frequency characterizations of signals and systems, sampling and sampling theorem, communication systems, Laplace transform, Z-transform, and linear feedback systems. Text: Oppenheim and Willsky, SIGNALS & SYSTEMS.

This course discusses theoretical and methodological knowledge of continuous and discrete-time signals and linear and time-invariant (LTI) systems in the frequency domain. . 

The course examines machine learning with a specific focus on deep learning technology. It will include the latest and state of the art technologies. Topics include self-attention, transformer, generative model, explainable AI, adversarial attack, privacy, domain adaptation, quantum ML, compression, and meta-learning.

This lab conducts research into high speed DC/RF 2D materials, specifically graphene and MoS2. Skills taught include DC, RF, and optical measurements, layer structure design, TCAD simulation, photomask design, ADS circuit modeling, and band diagram simulation. Reading materials assigned every week along with discussion section and lab work.