Graduate (List)

This course covers many facets of the topic of high-resolution radar, including basic principles, radar systems, Doppler radar, polarimetric radar, and spaceborne radar, and Synthetic Aperture Radar.

This course is designed to provide graduate students the cutting-edge technology of semiconductor memory devices and solutions. Special emphasis will be on the device and design issues in the DRAM and NAND Flash memory technology. Several advanced topics will be discussed, including the next-generation memory devices, processing in memory (PIM), CMOS image sensors (CIS), and data science for semiconductor memory.

This course will cover advanced device physics of MOSFETs and their ultimate scaling. Recent trends such as a new device structure and a new material will be introduced, and various types of memory devices as an example of detailed applications are also covered. Through a depth of study in quantum effects, reliability issues, and modeling, this course can provide core knowledge of next device technologies and a chance to explore new applications. (Prerequisite: EE362, EE561)

In this course, the basic concept and principle of plasma electronics will be studied. In particular, the basic phenomena of electronics in gas phase and the fundamental theory of plasmonics will be studied. The application of plasma electronics for plasma process and high-efficiency electronic displays and energy devices will be also discussed.

In this course, a new technology trend in electronics, flexible electronics, will be discussed and studied. The fundamental concept of flexible devices and materials including fabrication process will be introduced, and the applications of flexible electronics to TFTs, Display, Solar cell, and Sensors are also discussed.

This course covers broad aspects of electrical engineering including fundamental concepts, history, and various application areas. Roles and futures of electrical engineering are also addressed in this course.

This course deals with sensor fusion, decision making and information procession on real time for intelligent robots. To have a higher level of cognition, advanced level of problem-solving methods are presented for task planning, scheduling and navigation planning.
(Prerequisite: EE682, EE683)

This course covers fundamentals of p-n junction and MOSFET. Afterwards, Device structure, operational principle, design technology for DRAM, SRAM, Flash memory will be covered in depth. Beyond future device and design with architecture for next generation memory, logic device and design technology for system LSI will be introduced by KAIST faculty and Samsung engineers.

This course covers the practical design and analysis of various DC / DC converters in the power conversion system. High-frequency transformer, inductor, Magnetic Amplifier, Snubber, and Feedback Stabilization is studied to give students deep insight into power conversion system. Also, the power factor correction circuit is introduced as an AC / DC converter. Every student carries out the term project about design and modeling of a DC / DC converter. On completion of this course, students will have confidence in their ability of design and analysis of power conversion system.
(Prerequisites: EE391, EE594)

This course covers advanced research topics in Systems research for Artificial Intelligence and Machine Learning. The course is designed to cover system software, distributed machine learning frameworks, and AI applications in the context of Cloud and Mobile computing. We will carry on an in-depth study on the environment in which AI applications run including NPU, GPU, CPU and mobile APUs as well as software systems design to run AI applications on various platforms.