Curriculum

We Study introductory mathematical and programming tools for big data analytics, in particular focusing on recently successful real-world applications, e.g., web search, spam filtering, crowd-sourcing, visualization, and recommendation system

In this lecture, various hardware and software components and system implementation aspects of an embedded system are covered. Covered topics include bus-based expandable ARM processor-based board, open-source embedded Linux operating system, PC-based software development environment, digital and analog interface techniques, ARM assembly language, device drivers. Hands-on experience is gained to enhance firm understanding.
(Prerequisite: EE303)

This course provides students with the knowledge and skills necessary to build a foundation in system programmings for Electrical Engineering, especially focused on operating systems and implementation. Topics include an overview of the components of an OS, concurrency, synchronization, processes, memory management, I/O devices, and file systems.

This course emphasizes practical implementation aspects of digital communication systems. A physical-layer software implementation project will be assigned for a selected commercially-deployed communication system. Topics covered in this digital communication course include (1) Digital modulation and demodulation, Optimum receivers, (2) Adaptive equalization and Synchronization, (3) Channel capacity, Error control codes.
(Prerequisite: EE321)

The primary objective of this course is to present fundamental concepts and basic techniques of optimization with possible applications, which are essential for researches in circuit design, communications, signal processing, and control engineering. Topics include linear vector spaces and linear operators, linear estimation and filtering, functional analysis, optimal control, linear programming, nonlinear programming, dynamic programming, genetic programming (evolutionary computation), and neural networks.

As more industries are adopting artificial intelligence (AI) and machine learning (ML) technology, we are facing fast-growing demands for new types of hardware that enable faster and more energy efficient processing in relevant workloads. In this class, we will overview recent advances in AI/ML models, and study various AI silicon systems from both academia and industry

This course studies the representation, analysis, and design of discrete-time signals and systems. Topics include a review of the z-transform and the discrete Fourier transform, the fast Fourier transform, digital filter structures, digital filter design techniques, analog-to-digital, and digital-to-analog data conversion, rate conversion, sampling and aliasing issues. (Prerequisite: EE202)

This course covers machine learning techniques to analyze visual data. Specifically, this course focuses on fundamental machine learning and recent deep learning methods that are widely used in visual data analysis, and discusses how these methods are applied to solve various problems with visual data. This course consists of lectures, practices, and projects.

This introductory course is intended to familiarize students with underlying principles of fiber optic communication systems. Topics include an overview of fiber optic communication systems, optics review, lightwave fundamentals, light detectors, noise analysis, and system design, etc.

As AI technologies advance, the volume of data to be processed is growing exponentially. Integrated photonics, particularly silicon photonics, has emerged as a key platform for enabling high-speed, energy-efficient data transmission in applications like Co-Packaged Optics (CPO) and optical AI accelerators.

This course introduces the fundamentals of integrated photonic devices and builds a solid understanding of key components, including waveguides, couplers, gratings, resonators, modulators, and photodetectors. Students will also gain hands-on experience modeling devices through optical simulation tools. The course offers an excellent entry point for students interested in integrated photonics.