Curriculum

This course covers the theoretical framework for understanding the electronic properties of quantum confined devices, such as semiconductor heterostructures, two-dimensional materials, quantum wires, and quantum dots. Along with the fundamental principles, the course discusses operational characteristics of nanoscale electronic devices.

This course introduces students to a variety of media elements including text, graphics, sound, video, hardware and software components and the necessity for interactivity in multimedia as well. By introducing associate fundamental technologies, the course aims to help and encourage students to develop their imaginative and creative skills using multimedia. (Prerequisite: EE202)

This course teaches the principles of wireless network access techniques and system applications. The main focus of contents covers wireless medium access techniques, multiple access control and scheduling, system capacity optimization, and their applications to WiFi, WiMax, and ad-hoc sensor networks.

This course is on the design and implementation of database and big data systems. The first part covers database design and usage. The second part covers the internals of database systems and recent NoSQL and NewSQL systems.

In this course, a broad and practical overview for robotics is given in a multi-disciplinary perspective. Key principles such as coordinate transformation, navigation, control, motion planning, and decision making are taught. Recent advances in drons, self-driving cars, and AI for robotics are also introduced.

This course surveys scientific computing and data science methods relevant for physical electronics. First, traditional numerical analysis methods for the solution of ordinary and partial differential equations will be presented. Next, machine learning approaches and their mathematical basis will be surveyed in view of a modern numerical analysis framework.

The course begins with the quantum logic and aims to deliver how quantum advantages can be achieved in communication and computational tasks. Examples of quantum algorithms and quantum protocols are provided. Known approaches to implement quantum information processing are explained.

Two major themes of this course are ‘Modern Control System’ and ‘Computational Intelligence’. Each lecture will address a balanced emphasis on the theory about the control system and its applications in practice. The first part of this course includes digital control system design and state-space methods for control system design. The basic system identification scheme will also be included, considering the control of unknown systems. Once background knowledge of the modern control system is established, this course will then focus on the second part composed of computational intelligence using fuzzy logic, artificial neural network, and evolutionary computation as main topics to introduce recent trend in intelligent control. Term projects will be assigned to test the algorithms to the given problems. (Prerequisites: EE381)

Special topics in electrical engineering for new theoretical and applied fields will be covered in this lecture that involves a suitable subtopic(s).

Special topics in electrical engineering for new theoretical and applied fields will be covered in this lecture that involves a suitable subtopic(s).