As the C language, which forms the basis of critical global software like operating systems, faces security limitations, KAIST's research team is pioneering core original technology research for the accurate automatic conversion to Rust to replace it. By proving the mathematical correctness of the conversion, a limitation of existing Artificial Intelligence (LLM) methods, and solving C language security issues through automatic conversion to Rust, they presented a new direction and vision for future software security research. This work has been selected as the cover story for CACM, the world's highest-authority academic journal, thereby demonstrating KAIST's global research leadership in the field of computer science.

Did you know your brain might be more receptive to learning new things depending on the time of day? This study examined how a 24-hour cycle alters brain plasticity and neuronal excitability in rats.

NIMS has been developing chemical sensors as a key component of the artificial olfaction technology (olfactory sensors), with the aim of putting this technology into practical use. In this study, explainable AI (XAI) was used to reveal how chemical sensors discriminate among various odorant molecules. The findings may help guide the selection of receptor materials for developing high-performance chemical sensors capable of detecting odorant molecules. The achievement is expected not only to improve the performance of artificial olfaction but also to advance understanding of human olfactory mechanisms. This research was published online in ACS Applied Materials & Interfaces on September 9, 2025.