Curriculum

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.

Technology entrepreneurship has an important role both in training entrepreneurship and emphasizing the importance of venture business to students majored in science and engineering. The level of understanding real-life venture businesses will also be enhanced through case studies.

This course covers key issues in initiating an IT venture startups including business idea development, business model, growth strategy, business plan, and fundraising strategy. Students work in teams throughout the semester in simulating venture formation, which ends up with business plan presentation at the end of the semester.

Based on basic concepts in semiconductor physics, this course covers fundamental principles of optoelectronic devices, such as semiconductor-based light emitters and photodetectors, for modern photonics and optoelectronics applications.

Technology for Silicon Semiconductor IC (Integrated Circuit) chip which is the basis of modern electronic systems, will be covered, focusing on its historical background, structures of modern semiconductor devices, and fabrication processes. Current and future trends of semiconductor IC technology will also be discussed.
(Prerequisite: EE211, EE362)

This course will teach students the fundamental principles and concepts for an electric power system with an emphasis on renewable energy technologies that are important from the perspectives of electrical engineering.

This course aims to provide a broad viewpoint about 3D stacked and heterogeneously integrated semiconductor devices and its history. It will include how to fabricate those devices and its potential applications such as CMOS, Si photonics, Image sensors, MicroLED displays, etc. At the same time, related fundamental device physics will be introduced.