ISPSA 2026

Yeonjin Yi

(Yonsei University, Korea)

Title Probing Electronic Structures with Photoelectron Spectroscopy: A Tutorial

Biography
Lecture Summary

Educational background
1999 B. D. in Physics, Yonsei University, Seoul, Korea
2001 M. D. in Physics, Yonsei University, Seoul, Korea
2005 Ph.D. in Physics, Yonsei University, Seoul, Korea

Work experience
2005 – 2006 Post-doc., Department of Electrical Engineering, University of South Florida, USA (c/o Prof. R. Schlaf)
2006 – 2011 Senior Researcher, Korea Research Institute of Standards and Science, Korea
2011 – present Professor, Department of Physics, Yonsei University
2024 – 2025 Visiting Professor, LG Display Co., Korea

Present research activity
- Advanced Photoelectron Spectroscopy: Utilizing both direct and inverse photoelectron spectroscopy to characterize the electronic structure of semiconductors and low-dimensional hybrid materials.
- New Materials Exploration: Actively exploring and developing novel materials with tailored electronic properties for next-generation applications.

Understanding the electronic structure of materials is crucial for the rational design and operation of modern electronic devices, particularly semiconductors. The performance of these devices is fundamentally governed by the arrangement and behavior of electrons. This tutorial will provide a comprehensive overview of photoelectron spectroscopy (PES) as a powerful technique for probing and analyzing these electronic properties. We will first explain the basic principles of PES, including the photoelectric effect, and how it can be used to directly measure electron binding energies. The presentation will then explore how PES can be used to understand the electronic structures of various materials, focusing on key concepts such as energy levels, bandgaps, and quasiparticle behaviors of electrons. We will discuss practical applications of PES, including the measurement and interpretation of energy band diagrams and the determination of energy level alignments at interfaces, which are critical for device performance. The goal of this session is to provide attendees with the fundamental knowledge necessary to use PES for advanced material characterization and device physics rationalization.

Hyungjin Kim

(Hanyang University, Korea)

Title Emerging Memory Devices for In-Memory Computing Applications

Biography
Lecture Summary

Hyungjin Kim received the B.S., M.S., and Ph.D. degrees in Electrical and Computer Engineering from Seoul National University, Seoul, Korea, in 2010, 2012, and 2017, respectively. From 2018 to 2019, he served as a postdoctoral researcher at the University of California, Santa Barbara (UCSB), USA. Subsequently, from 2020 to 2024, he held the position of Assistant/Associate Professor in the Department of Electrical and Computer Engineering at Inha University, Incheon, Korea. Currently, he is an Associate Professor with the Division of Materials Science and Engineering at Hanyang University, Seoul, Korea. His research focuses on emerging memory devices and their computing applications.

The rapid growth of artificial intelligence and data-intensive applications has exposed fundamental limitations in conventional von Neumann computing systems, particularly the energy and latency overheads caused by frequent data movement between memory and processors. In-memory computing has emerged as a promising paradigm to address this challenge by performing computation directly within memory arrays. Among various candidates, emerging memory devices such as resistive switching memories and capacitive devices have attracted significant attention due to their scalability, non-volatility, and compatibility with existing semiconductor processes. This tutorial will introduce the fundamental device physics of emerging memories and their integration into array architectures for in-memory computing. Particular emphasis will be placed on how device characteristics affect system-level performance in machine learning. Furthermore, recent advances in crossbar arrays with memristive devices and memcapacitive devices will be discussed to highlight the trade-offs between accuracy, energy efficiency, and scalability.

SangHoon Shin

(Hanyang University, Korea)

Title Advanced Semiconductor Reliability from a transistor to system

Biography
Lecture Summary

Dr. SangHoon Shin is an Assistant Professor in the School of Electronics Engineering at Hanyang University ERICA since 2025, specializing in advanced semiconductor packaging and reliability. He received his Ph.D. in Electrical and Computer Engineering from Purdue University in 2017, after completing his M.S. at the University of Tokyo and B.S. at Hanyang University.
He brings extensive industry experience in cutting edge packaging technologies. At Tesla, he led the development of 2.5D AI SoC packaging and the Dojo 3D CoWoS platform for autonomous driving systems, managing process and material integration as well as reliability qualification. At Apple, he focused on SoC package integration reliability for Apple Silicon based Mac products, overseeing design-for-reliability, test specifications, and cross functional failure analysis. His earlier role at Intel involved reliability modeling and accelerated stress testing for FEOL and BEOL technologies.
Building on this background, his current research addresses heterogeneous integration, glass substrate based optical I/O, advanced 2.5D and 3D packaging platforms, and predictive reliability methodologies for high performance computing, AI, and automotive applications.

2025.03–Present, Assistant Professor, School of Electrical Engineering, Hanyang University ERICA
2022.04–2025.02, Tesla, Staff Semiconductor Engineer
2020.01–2022.03, Apple, SoC Package Integration Reliability Engineer
2018.05–2020.01, Intel, CMOS Reliability R&D Engineer
2017.04–2018.04, IBM T.J. Watson Research Center, Postdoctoral Researcher
2012.08–2017.05, Ph.D. in Electrical and Computer Engineering, Purdue University
2010.10–2012.09, M.S. in Electrical and Electronic Engineering, The University of Tokyo
2003.03–2009.08, B.S. in Electronics and Computer Engineering, Hanyang University

Yong-Hoon Kim

(KAIST, Korea)

Title Toward Ab Initio Technology Computer-Aided Design

Biography
Lecture Summary

Prof. Yong-Hoon Kim is a Professor in the School of Electrical Engineering at Korea Advanced Institute of Science and Technology (KAIST). His research interests are in first-principles calculation approaches for nonequilibrium open quantum systems and their applications to nanodevices based on functional low-dimensional materials. Notable achievements include the development of multi-space constrained-search density functional theory (MS-DFT), DeepSCF machine learning formalism, and the quantum-hybridization negative differential resistance (QH-NDR) mechanism, and many others. Prof. Kim received B.S. degree in physics from Seoul National University in 1995 and Ph.D. degree in theoretical condensed matter physics from University of Illinois Urbana-Champaign in 2000. He was a Humboldt Fellow at Technische Universität München from 2000 and 2002, and a postdoctoral researcher at California Institute of Technology from 2002 to 2004. In 2004, he returned to Korea as an Assistant Professor at Korea Institute for Advanced Study, and since then affiliated with University of Seoul from 2006 to 2010 and with KAIST since 2010.

The continued miniaturization of semiconductor devices, long encapsulated by Moore’s law, has now reached the atomic-scale limit, necessitating the explicit incorporation of quantum-mechanical effects into device simulations without reliance on empirical parameters. This Tutorial aims to provide a guided introduction to recent efforts to bridge first-principles electronic-structure calculations—represented by density functional theory (DFT)—with semiconductor device simulations, commonly known as technology computer-aided design (TCAD). After briefly outlining the TCAD in semiconductor technology and reviewing the fundamental physics underpinning standard TCAD, the DFT-based non-equilibrium Green's function (NEGF) theory is introduced as a leading approach for first-principles TCAD simulations. Despite its widespread adoption, the DFT–NEGF scheme suffers from inherent conceptual and practical limitations rooted in the Landauer transport picture. As an alternative, the multi-space constrained-search DFT (MS-DFT) formalism is then introduced, which we have been developing over the past decade or so [1]. The central conceptual advance of MS-DFT lies in replacing the Landauer viewpoint with a multi-space excitation framework, in which quantum transport is mapped onto energy- and position-resolved electron excitations. I highlight the key features of the MS-DFT formalism [2], showcase representative results from its application to 2D and molecular transistors [3], and conclude by discussing several promising directions for future development.

References
[1] J. Lee, H. Lee, and Y.-H. Kim, Proc. Nat. Acad. Sci. USA, 117, 10142 (2024); J. Lee, H.S. Kim, and Y.-H. Kim, Adv. Sci. 7, 2001038 (2020).
[2] Y.-H. Kim and R.-G. Lee, IEEE Nanotech. Mag. 18, 4 (2024).
[3] Z. Huang, et al., ACS Nano18, 28700 (2024); D. Kim, et al., Sci. Adv. 11, eadt3603 (2025).

Program

Tutorial Speakers