Electrical Engineering

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.

The purpose of this course is to introduce Micro-Electro-Mechanical Systems to students with mechanical and electrical engineering background. Key topics include Basic IC board manufacturing process, basic MEMS development process, microsensors, microactuators, system energy supply, assembly and testing, current technology applications, and the industry’s future.

This course provides the basic tools and knowledge needed to design optical systems. At the end of the course, students will be able to take system requirements, select possible components and approaches, create candidate designs, and analyze and optimize their performance. Students learn and utilize standard optical design tools, particularly ray-tracing, as well as learning how to create custom system models with wave, polarization, or Gaussian-beam optical modeling. The course objectives include basic design techniques for ray optics; wave optics in isotopic media; design concepts for optical instruments (microscope, telescope, camera lenses); aberration in optical system (real world problems); how to select optical components (lenses, fibers, optical source and detectors); and optical CAD tools discussion (ZEMAX education version).

This course addresses modeling and control of dynamic systems. It focuses on systems that can be modeled by Ordinary Differential Equations (ODEs), and that satisfy certain linearity and time-invariance conditions (a.k.a. LTI systems).  The course also analyzes the output response of these systems to initial conditions and inputs; investigates feedback control on LTI systems, and introduces the methods of classical control techniques.  Students learn how to design a controller that ensures desirable properties (e.g., stability, performance, and robustness) with a given dynamic system.