Graduate (List)

In this course, I will lecture to electrical engineering students on the engineering applications of nanostructured semiconductors. The focus is primarily on the electronic structure of two-dimensional semiconductors, their modifications, and low-dimensional nanostructure transistors. In the latter part of the course, I also cover some quantum materials beyond semiconductors. Finally, we read and discuss relevant research papers.

This course covers topics of interest in integrated circuits for students at the graduate level. The course content is specifically designed by the instructor.

This course covers recent issues related with the VLSI System design.

This course introduces a basic concept, definition and computational models of Intelligence System. In addition, this course covers a relationship between the computational model with the real brain in a psychology and brain anatomy perspectives. As an example of Intelligence System on a Chip, Visual Attention Model and its multi-core processor implementation are studied with machine learning algorithms.

This course is an advanced project-based learning (PBL) course mainly targeting the students with “Interdisciplinary Incubation Center for Biomedical and System Semiconductor”. In the course, a student selects his/her own research project and practice leading the project, under supervision of the instructor and other professors/researchers with the center.

At first, we study the electrical characteristics and related neuro-dynamics, modelling, and CMOS circuit implementation methods for a single neuron. And then, we extend from single to neural network such as spike neural network (SNN). This course also introduces how to apply SNN architecture to semiconductor devices and circuits with specific case studies.

This course introduces a basic concept, definition and trends of neuromorphic and processing-in-memory (PIM). In addition, this course covers the hardware implementation of neuromorphic and PIM. Also, real implementation results of state-of-the-art neuromorphic and PIM hardware will be studied.

This lecture covers digital system-on-chip (SoC) design methodologies, which can be regarded as essential techniques for realizing the recent digital VLSI circuits. Students can design and verify system-on-chip architectures by integrating processor, on-chip bus, and digital IPs, performing advanced HW/SW co-design steps for improving the system efficiency.

This course covers topics of interest in robotics for graduate level students. Course content is specifically designed by the instructor.

This course covers topics of interest in control theory at the graduate level. Course content is specifically designed by the instructor.