SKKU RANBIZ

Media & Communication Prof. BAEK, TAE HYUN Luxury brands have increasingly embraced internet memes in their social media advertising campaigns. For example, Gucci’s #TFWGucci campaign demonstrated how luxury brands can incorporate memes into their digital communication strategies to capture consumer attention. Memes—digital content that spreads rapidly through sharing, imitation, and adaptation across online communities—have become a popular way for brands to engage consumers. Branded memes, in particular, leverage humor, relatability, and virality to communicate brand messages in a more engaging and shareable format. However, the use of memes by luxury brands may seem somewhat unexpected, given that these brands have traditionally emphasized exclusivity, prestige, and sophistication. Although many companies actively employ meme advertising to connect with consumers, it remains unclear whether this communication strategy enhances consumer responses or weakens a brand’s premium image.

2026-06-05

Chemical Engineering Prof. PARK, SUNGJUNE The research group led by Prof. Sungjune Park from the Department of Chemical Engineering has developed an ultra-stretchable, anti-freezing hydrogel electrolyte using liquid metal particles. The material can stretch up to nine times its original length while maintaining stable electrochemical performance, even at −20 °C. This work provides a promising platform for energy storage devices that must operate reliably under extreme environmental conditions. With the rapid growth of wearable electronics, there is increasing demand for energy storage systems that combine mechanical flexibility with environmental stability. However, conventional hydrogel electrolytes typically suffer from low mechanical strength and freezing at low temperatures, leading to significant performance degradation.

2026-06-04

Statistics Prof. LEE, KYOUNGJAE The research team of Professor Kyoungjae Lee of the Department of Statistics at Sungkyunkwan University, through joint research with Professor Won Chang of Seoul National University and Professor Xuan Cao of the University of Cincinnati, developed Bayesian inference for the hidden dependence structures of multi-group high-dimensional data. A Dependence Map in High-Dimensional Data In today’s scientific and industrial fields, high-dimensional data in which numerous variables are observed simultaneously, such as genomic, climate, financial, and sensor data, are rapidly increasing. In such data, an important problem is to learn the dependent structures connecting the variables and to identify a “dependence map” that reveals hidden information in massive datasets. For example, in climate data, temperatures in nearby regions may be related to one another, and in genomic data, genes located in adjacent positions may act together. If such dependence can be incorporated into inference, more efficient inference is possible than analyzing each variable separately.

2026-05-27