Graduate (List)

This course will teach students fundamental concepts and technologies for energy harvesting systems and their related circuits, as well as power management IC technologies that can minimize power usage.

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 system identification to know the unknown system parameters for controlling the system. There are two schemes for the control of the unknown system: one is direct adaptive control and the other is indirect adaptive control. Robust adaptive control and adaptive control for nonlinear systems are dealt with.
(Prerequisite: EE581)

This course introduces variable structure control (VSC) theory which is one of the robust control theories. Various basic theorems of VSC will be analyzed in the sliding mode. Expanding the target plant from a second order plant to the n-th order plant, it will be studied how to determine switching conditions and switching vectors. Stability will be analyzed by designing a feedback control loop. By integrating multi-variable structure with optimal control theory and adaptive control theory, the problem of system optimization and the problem of determining coefficients of switching vector in sliding mode will be resolved. Based on those theories, discrete variable structure control (DVSC) will be introduced. Finally, it will be studied how to apply those theories to the control system in robot systems, space aerial planes, satellites, chemical plants, power plants and motors.

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.

This course covers topics of interest in electrical engineering at the graduate level. The course content is specifically designed by the instructor.

This course covers topics of interest in electrical engineering at the graduate level. The course content is specifically designed by the instructor.