Undergraduate


  • Electromagnetics 1 (Spring): In the EM-1 lectures, while learning about why we need a vector analysis and where we apply it to, E-field and M-field in a static condition (i.e. conservative) is to be studied along with Gauss’s law and Ampere’s law. Since electric (E) and magnetic (M) fields are a vector quantity, respectively, we need a vector analysis to formulate them efficiently and mathematically, for example, divergence, gradient, curl, and so on. Eventually, Maxwell’s equations for static fields are deduced and derived.
  • Electromagnetics 2 (temporarily stopped): In the EM-2 lectures, we are now moving onto studies on Time-variant Maxwell’s equations which are more general forms than static versions learned in lectures of EM-1. This would make an interesting outcome where E-field can get a curl and non-conservative fields can be generated whereas EM1 was a static condition where almost every fields are conservative. Based on these, we will also learn about Transmission line theory and plane waves.
  • Semiconductor Engineering (Fall): In the SE lectures, students will learn semiconductor physics and electronic devices, such as PN-junction diodes, BJTs, FETs, and so on. Since Prof. Sungsik LEE is a world-wide recognized expert in the semiconductor research field, this lecture will give students a special opportunity to have a very professional content and the world-class teaching from him.
  • Display Engineering (temporarily stopped): In the DE lectures, students will learn thin film transistors (TFTs) in terms of device physics since the TFT is a fundamental component for display backplanes. Since Prof. Sungsik LEE is a world-wide recognized expert in the semiconductor research field including TFTs, this lecture will give students a special opportunity to have a very professional content and the world-class teaching from him.
  • Final Year Project (졸업과제): In the final year project, 4th year students will learn AI semiconductors and related device physics using the SILVACO-based T-CAD semiconductor simulation in conjunction with a neural network, e.g. CNN, along with the Python programming.

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