Dong-Myoung Kim donated 2 billion KRW to fund the Kim Jae-Chul AI Graduate School

< President Lee (left) poses with Dong-Myoung Kim who donated 2 billion KRW to KAIST during a ceremony on December 6. >
Dong-Myong Kim, a 90-year-old resident living in Seongnam City in Kyonggido made a gift of 300 million KRW in cash and property valued at 1.7 billion KRW to fund the Kim Jae-Chul AI Graduate School. KAIST President Kwang Hyung Lee and a senior leadership team warmly received Kim during the donation ceremony on December 6 and delivered a plaque of appreciation.
Kim, a certified judicial scrivener, sent a letter regarding his intention to donate to the KAIST Development Foundation Office in October. Development foundation officers contacted him for a meeting and presented the major achievements of KAIST and new vision for the future during the meeting. After meeting with KAIST officials, Kim completed all the legal procedures for donating such as handing over the title of his property.
A Development Foundation official said that Kim was well aware of what KAIST has achieved and is doing now. “He had already searched KAIST’s website and scrutinized what we are doing now. He was clear about his intentions,” said the official.
Kim said that media news reports on the recent series of huge donations to KAIST inspired him. “I thought there was something special behind the donors’ intention to make such a decision.”
Kim said the studies on futurism he started in the 1980s led him to become interested in new technologies. “I firmly believe that KAIST will make huge contributions to the nation and our society through advances in science and technology. It is said that the joy of giving is much larger than that of receiving. I am now experiencing such immense joy. I will be even happier if KAIST can lead the nation through its AI research.”
President Kwang Hyung Lee said Kim’s letter of intention touched him deeply. He thanked Kim, saying that the entire KAIST community will make every effort to respond to Kim’s donation wishes.
<(From Left) Ph.D candidate Geon Lee, Ph.D candidate Minyoung Choe, M.S candidate Jaewan Chun, Professor Kijung Shin, M.S candidate Seokbum Yoon> KAIST (President Kwang Hyung Lee) announced on the 9th of December that Professor Kijung Shin’s research team at the Kim Jaechul Graduate School of AI has developed a groundbreaking AI technology that predicts complex social group behavior by analyzing how individual attributes such as age and role influence group relationships. With th
2025-12-09<Photo of KAIST Students> KAIST announced on December 9th that it will accelerate the nurturing of world-class scientific talent and regional balanced development. This follows the government's recent announcement on 'Leaping to a Science and Technology Powerhouse, the Republic of Korea, Where People Dream of Becoming Science and Technology Professionals Again (Nov. 7),' which explicitly named the four major science and technology institutes, including KAIST, as AX (AI Transformation) i
2025-12-09<(From Left) Ph.D candidate Sungyoon Woo, Professor Il-Doo Kim, Professor Seung S.Lee, Ph.D candiate Jihwan Chae, Researcher Jiyeon Yu, (Upper Right) Dr. Yujang Cho> A KAIST research team has drawn attention by developing a new water-based air purification technology that combines “nano water droplets that capture dust” with a “nano sponge structure that autonomously draws up water,” enabling dust removal using nano water droplets without filters, self-supplied w
2025-12-08<(Top row, from left) Professor Kang Taek Lee, Ph.D candidate Yejin Kang, Dr. Dongyeon Kim, (Bottom row, from left) M.S candidate Mincheol Lee, Ph.D candidate Seeun Oh, Ph.D candidate Seungsoo Jang, Ph.D candidate Hyeonggeun Kim> As power demand surges in the AI era, the “protonic ceramic electrochemical cell (PCEC),” which can simultaneously produce electricity and hydrogen, is gaining attention as a next-generation energy technology. However, this cell has faced the techni
2025-12-05<(From Left) Ph.D candidate Daehee Kwon, Ph.D candidate Sehyun lee, Professor Jaesik Choi> Although deep learning–based image recognition technology is rapidly advancing, it still remains difficult to clearly explain the criteria AI uses internally to observe and judge images. In particular, technologies that analyze how large-scale models combine various concepts (e.g., cat ears, car wheels) to reach a conclusion have long been recognized as a major unsolved challenge. KAIST (Pr
2025-11-26