people
(Professor Dae-Sik Im of the Department of Biological Sciences)
Professor Dae-Sik Im of the Department of Biological Sciences, a renowned molecular cell biologist, was named to head the Science, Technology and Innovation Office in the Ministry of Science and ICT on August 31. He will be responsible for the oversight of national R&D projects as well as budget deliberation. Joining the KAIST faculty in 2002, he led the Creative Research Center of Cell Division and Differentiation at KAIST.
Announcing the nomination of Professor Im, Cheong Wa Dae spokesman Park Soo-Hyun said, “Professor Im will be the best person to lead the innovation of the research infrastructure system for basic research studies. We believe that his expertise and leadership will make a significant impact in enhancing the nation’s science and technology competitiveness. This vice minister position in the Ministry of Science and ICT was newly created in an effort to enhance national science and technology initiatives by President Moon Jae-In.
Professor Im said at the news conference, “I would like to make a sustainable, as well as credible, system ensuring the ingenuity of scientists in Korean labs. To this end, I will make every effort to enhance Korea’s innovative research environment in a way to maximize research achievements.”
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research KAIST reveals for the first time the mechanism by which alcohol triggers liver inflammation
<(From left)Dr. Keungmo Yang, Professor Won-Il Jeong, Ph.D candidate Kyurae Kim> Excessive alcohol consumption causes alcoholic liver disease, and about 20% of these cases progress to alcohol-associated steatohepatitis (ASH), which can lead to liver cirrhosis and liver failure. Early diagnosis and treatment are therefore extremely important. A KAIST research team has identified a new molecular mechanism in which alcohol-damaged liver cells increase reactive oxygen species (ROS), leading
2025-07-17 -
research KAIST Ushers in Era of Predicting ‘Optimal Alloys’ Using AI, Without High-Temperature Experiments
<Picture1.(From Left) Prof. Seungbum Hong, Ph.D candidate Youngwoo Choi> Steel alloys used in automobiles and machinery parts are typically manufactured through a melting process at high temperatures. The phenomenon where the components remain unchanged during melting is called “congruent melting.” KAIST researchers have now addressed this process—traditionally only possible through high-temperature experiments—using artificial intelligence (AI). This study dra
2025-07-14 -
research KAIST Shows That the Brain Can Distinguish Glucose: Clues to Treat Obesity and Diabetes
<(From left)Prof. Greg S.B Suh, Dr. Jieun Kim, Dr. Shinhye Kim, Researcher Wongyo Jeong) “How does our brain distinguish glucose from the many nutrients absorbed in the gut?” Starting with this question, a KAIST research team has demonstrated that the brain can selectively recognize specific nutrients—particularly glucose—beyond simply detecting total calorie content. This study is expected to offer a new paradigm for appetite control and the treatment of metabolic
2025-07-09 -
research KAIST Develops Novel Candidiasis Treatment Overcoming Side Effects and Resistance
<(From left) Ph. D Candidate Ju Yeon Chung, Prof.Hyun Jung Chung, Ph.D candidate Seungju Yang, Ph.D candidate Ayoung Park, Dr. Yoon-Kyoung Hong from Asan Medical Center, Prof. Yong Pil Chong, Dr. Eunhee Jeon> Candida, a type of fungus, which can spread throughout the body via the bloodstream, leading to organ damage and sepsis. Recently, the incidence of candidiasis has surged due to the increase in immunosuppressive therapies, medical implants, and transplantation. Korean researc
2025-07-08 -
research KAIST Presents a Breakthrough in Overcoming Drug Resistance in Cancer – Hope for Treating Intractable Diseases like Diabetes
<(From the left) Prof. Hyun Uk Kim, Ph.D candiate Hae Deok Jung, Ph.D candidate Jina Lim, Prof.Yoosik Kim from the Department of Chemical and Biomolecular Engineering> One of the biggest obstacles in cancer treatment is drug resistance in cancer cells. Conventional efforts have focused on identifying new drug targets to eliminate these resistant cells, but such approaches can often lead to even stronger resistance. Now, researchers at KAIST have developed a computational framework to pr
2025-07-08