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Thomson Reuters ranked KAIST first among Asia’s top most innovative universities in a list that it released on August 30, 2016. Seventy-five Asian universities received this distinction.
Thomson Reuters created the list to identify those educational institutions that are “doing the most to advance science, invent new technologies, and help drive the global economy.”
The rankings were based on data drawn from each academic institution's research papers and patent filing information as evaluated by the Intellectual Property & Science division of Thomson Reuters.
Thomson Reuters described KAIST as producing "original and influential research" and noted that other organizations cited its patent portfolios as "significant prior art in their own patent applications, a strong indicator that the university has an outsized impact on global research and development."
For details, please go to the link below:
Asia’s Most Innovative Universities
Reuters
August 30, 2016
http://www.reuters.com/article/us-asiapac-reuters-ranking-innovative-un-idUSKCN1152B7#listing
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event KAIST Takes the Lead in Developing Core Technologies for Generative AI National R&D Project
KAIST (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
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<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
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research KAIST Develops AI That Automatically Designs Optimal Drug Candidates for Cancer-Targeting Mutations
< (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
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<(From left)Professor Jimin Park, Ph.D candidate Myeongeun Lee, Ph.D cadidate Jaewoong Lee,Professor Jihan Kim> Cells use various signaling molecules to regulate the nervous, immune, and vascular systems. Among these, nitric oxide (NO) and ammonia (NH₃) play important roles, but their chemical instability and gaseous nature make them difficult to generate or control externally. A KAIST research team has developed a platform that generates specific signaling molecules in situ from a si
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