KAIST ranked 40th in the 2018 QS World University Rankings, one place higher than last year. According to the QS (Quacquarelli Symonds) World’s Top 100 universities released on June 7, KAIST is the second highest ranked Korean university among the five Korean universities listed, following Seoul National University which ranked 36th.
KAIST displayed outstanding performance by ranking 16th in citations per faculty. In the 2018 rankings, universities that are strong in science, technology, and engineering claimed some of the highest positions. MIT topped the list and Caltech took fourth, ETH Zurich seventh, followed by Imperial College London which took eighth.
According to the analysis compiled by QS, universities focusing on science and technology are dominating the global universities rankings. This tendency comes from the fact that engineering schools have an advantage when evaluating the quality of research according to the number of citations per faculty member.
Provost O Ok Park predicts that science and technology will be key players in the Fourth Industrial Revolution era. “In the coming years, universities that excel in multi and interdisciplinary research will lead future growth. KAIST also continues to focus on transdisciplinary education and research,” he said.
<Professor Mikyoung Lim from KAIST Department of Mathematical Sciences> Professor Mikyoung Lim from KAIST Department of Mathematical Sciences gave a plenary talk on "Research on Inverse Problems based on Geometric Function Theory" at AIP 2025 (12th Applied Inverse Problems Conference). AIP is one of the leading international conferences in applied mathematics, organized biennially by the Inverse Problems International Association (IPIA). This year's conference was held from July 2
2025-08-14KAIST (President Kwang Hyung Lee) is leading the transition to AI Transformation (AX) by advancing research topics based on the practical technological demands of industries, fostering AI talent, and demonstrating research outcomes in industrial settings. In this context, KAIST announced on the 13th of August that it is at the forefront of strengthening the nation's AI technology competitiveness by developing core AI technologies via national R&D projects for generative AI led by the Minis
2025-08-13<(From Left) Donghyoung Han, CTO of GraphAI Co, Ph.D candidate Jeongmin Bae from KAIST, Professor Min-soo Kim from KAIST> Alongside text-based large language models (LLMs) including ChatGPT, in industrial fields, GNN (Graph Neural Network)-based graph AI models that analyze unstructured data such as financial transactions, stocks, social media, and patient records in graph form are being actively used. However, there is a limitation in that full graph learning—training the entire
2025-08-13<ID-style photograph against a laboratory background featuring an OLED contact lens sample (center), flanked by the principal authors (left: Professor Seunghyup Yoo ; right: Dr. Jee Hoon Sim). Above them (from top to bottom) are: Professor Se Joon Woo, Professor Sei Kwang Hahn, Dr. Su-Bon Kim, and Dr. Hyeonwook Chae> Electroretinography (ERG) is an ophthalmic diagnostic method used to determine whether the retina is functioning normally. It is widely employed for diagnosing hereditary
2025-08-12< (From left) Ph.D candidate Wonho Zhung, Ph.D cadidate Joongwon Lee , Prof. Woo Young Kim , Ph.D candidate Jisu Seo > Traditional drug development methods involve identifying a target protin (e.g., a cancer cell receptor) that causes disease, and then searching through countless molecular candidates (potential drugs) that could bind to that protein and block its function. This process is costly, time-consuming, and has a low success rate. KAIST researchers have developed an AI model th
2025-08-12