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KAIST Team Wins Grand Prize at Kakao AI Incubation Project
<(From Left) Professor Jongse Park, Professor youngjin Kwon, Professor Jaehyuk Huh, Professor Knunle Olukotun>
Currently, Large Language Model (LLM) services like ChatGPT rely heavily on expensive GPU servers. This structure faces significant limitations, as costs and power consumption skyrocket as service scales increase. Researchers at KAIST have developed a next-generation AI infrastructure technology to address these challenges.
KAIST announced on January 30th that the ‘AnyBridge AI’ team, led by Professor Jongse Park from the School of Computing, has developed a next-generation AI infrastructure software. This software allows for efficient LLM services by integrating various AI accelerators instead of relying solely on GPUs. The technology won the Grand Prize at the "4 ISTs (Science & Tech Institutes) × Kakao AI Incubation Project" hosted by Kakao.
This project is a joint industry-academic collaboration between Kakao and the four major science and technology institutes (KAIST, GIST, DGIST, and UNIST). It selected outstanding teams by evaluating the technical prowess and business viability of preliminary startup teams based on AI technology. The Grand Prize winning team receives a total of 20 million KRW in prize money and up to 35 million KRW in Kakao Cloud credits.
AnyBridge AI is a technical startup team led by Professor Jongse Park (CEO), with Professors Youngjin Kwon and Jaehyuk Huh from KAIST's School of Computing participating. Based on research achievements in AI systems and computer architecture, the team aims to develop technology applicable to actual industrial sites. Furthermore, Professor Kunle Olukotun of Stanford University—co-founder of the Silicon Valley AI semiconductor startup SambaNova—is participating as an advisor to push for global technology and business expansion.
The AnyBridge team noted that most current LLM services are dependent on expensive GPU infrastructure, leading to structural limits where operating costs and power usage surge as services scale. The researchers analyzed that the root cause of this issue lies not in the performance of specific hardware, but in the absence of a system software layer capable of efficiently connecting and operating various AI accelerators, such as NPUs (AI-specialized chips) and PIMs (next-gen chips that process AI within memory), alongside GPUs.
<Technical diagram of AnyBridge: Enhancing LLM performance by flexibly utilizing various AI accelerators>
In response, the AnyBridge team proposed an integrated software stack that can service LLMs across the same interface and runtime environment, regardless of the accelerator type. Specifically, they received high praise for pointing out the limitations of existing GPU-centric LLM serving structures and presenting a "Multi-Accelerator LLM Serving Runtime Software" as their core technology.
This technology enables the implementation of a flexible AI infrastructure where the most suitable AI accelerator can be selected and combined based on the task's characteristics, without being tied to a specific vendor or hardware. This is evaluated as a major advantage that can reduce costs and power consumption while significantly increasing scalability for LLM services.
<Illustration of the Multi-Accelerator LLM Service Platform - AI-generated image>
Additionally, based on years of accumulated research in LLM serving system simulation, the AnyBridge team possesses a research foundation that can pre-verify various hardware/software design combinations without building a large-scale physical infrastructure. This point demonstrated both the technical maturity and the industrial feasibility of their work.
"This award is a result of recognizing the necessity of system software that integrates various AI accelerators, moving beyond the limits of GPU-centric AI infrastructure," said Professor Jongse Park. He added, "It is meaningful that we could expand our research results into industrial fields and entrepreneurship. We will continue to develop this into a core technology for next-generation LLM serving infrastructure through cooperation with industrial partners."
This award is seen as a prime example of KAIST's research moving beyond academic papers toward next-generation AI infrastructure technology and startups. AnyBridge AI plans to advance and verify its technology through future collaborations with Kakao and related industrial partners.
<Photo of the Grand Prize ceremony: Left - Kakao Investment CEO Do-young Kim; Right - KAIST Prof. Jongse Park>
2026.01.30 View 475 -
Robot Valley Project Activation of the Korean style Robot and AI Startup Ecosystem Fully Underway
< From left: Top Excellence Award winner Robolight (Pre-startup Founder Han-seol Choi), Top Excellence Award winner Coils (CEO Seong-ryeol Heo), Professor Jung Kim of KAIST, Grand Prize winner Noman (CEO Jung-wook Moon), Professor Kyoungchul Kong of KAIST, CEO Dae-hee Park of Daejeon Creative Economy Innovation Center, Excellence Award winner Gigaflops (CEO Min-tae Kim), Excellence Award winner BLUE APEX (Pre-startup Founder Na-hyeon Kwon) >
KAIST announced on December 10th that KAIST Holdings (CEO Hyeonmin Bae), a specialized technology commercialization investment institution, successfully held the '2025 KAIST Hu-Robotics Startup Cup' on the 9th at the main building of Daejeon Startup Park. This was held as part of the Robot Valley Project, aiming to discover and foster promising startup teams in the robotics field and establish a robot scale-up ecosystem based on a technology platform.
This competition was conducted as a core program of the Robot Valley Project (Deep-Tech Scale-up Valley Fostering Project), which is promoted by the Ministry of Science and ICT and supported by Daejeon Metropolitan City. The competition proceeded through a meet-up day with KAIST Mechanical Engineering researchers, robotics companies like Angel Robotics and Twinny, and startup experts such as Bluepoint, leading to the final round. Throughout this process, a support system for the scale-up of robot startups was established, linking technology verification, strengthening entrepreneurial capabilities, and investment linkage.
KAIST Holdings and the Deep-Tech Valley Project Group (hereinafter referred to as the Project Group) stated that this competition marks the beginning of 'establishing a Korean-style Robot and AI startup ecosystem.' Their goal through the Robot Valley Project is to create a Korean-style robot scale-up ecosystem centered around Daejeon and KAIST, and furthermore, to build a technology circulation structure utilizing verified technology platforms.
KAIST has produced successful scale-up cases in the robotics field, such as Rainbow Robotics and Angel Robotics. However, the recent robotics industry has seen a rapid increase in technological difficulty due to the convergence of mechanical engineering, AI, and control software, creating structural limitations for early-stage founders to challenge alone.
To solve this, the Project Group proposed the 'Scale-up Valley Construction Strategy,' which opens up the verified technologies of established senior companies to junior founders. This strategy focuses on supporting startups to concentrate on developing market-ready robot services and applications on top of verified technology platforms, rather than consuming excessive time on developing basic hardware like motors and controllers.
The Angel Robotics technology platform, presented as the core underlying technology of this strategy, consists of actuators, control modules, and core software. KAIST plans to gradually open up these foundational technologies for use by early-stage startup teams.
The Project Group emphasized that enabling startup teams to utilize such technology platforms from the initial stage is the core infrastructure for accelerating the Korean-style robot startup ecosystem.
A total of 21 teams participated in this competition, including pre-startup founders (Track A) and early-stage startups established within 3 years (Track B), all possessing human-centered robotics technology and convergence business models.
After fierce preliminaries, 8 teams advanced to the final round, and a total of 5 teams were finally selected: one Grand Prize winner, two Choi Woo-sung (Top Excellence Award) winners, and two Excellence Award winners.
The Grand Prize was awarded to 'Noman' for proposing an integrated system for a strawberry farm work robot and a rotating vertical cultivation module.
The Woo-sung Choi (Top Excellence Award) went to 'Robolight' and 'Coils.'
The Excellence Award was awarded to BLUE APEX and Gigaflops.
Professor Jung Kim, Head of the KAIST Mechanical Engineering Department and General Manager of the Robot Valley Project, said, "This competition has become the starting point for discovering future robot unicorns. For the next three years, we will continue to provide practical support for the growth of robot startups, and KAIST will play a leading role in building and expanding the deep-tech robot ecosystem centered in Daejeon."
< Group Photo of Award Winners >
Meanwhile, this competition was jointly hosted and organized by the Ministry of Science and ICT, Daejeon Metropolitan City, and the Research and Business Development Special Zone Foundation, as well as startup support organizations including KAIST, KAIST Holdings, Daejeon Technopark, and Daejeon Creative Economy Innovation Center.
2025.12.10 View 1434 -
KAIST to Foster a 'Robot Valley' in Daejeon with $10 Million Initiative
<Group Photo of Kick-off Meeting>
On September 3, KAIST announced the official launch of the "2025 Deep Tech Scale-up Valley Nurturing Project" with a kick-off meeting at the KAIST Department of Mechanical Engineering.
KAIST was selected for this project by the Ministry of Science and ICT and the Research and Development Special District Foundation. With this selection, the university plans to create a "Robot Valley".
Over the next three and a half years, KAIST will receive a total of 13.65 billion won (approximately $10 million) in funding. The university's goal is to intensively nurture globally competitive, innovative robotics companies based on foundational technologies and to develop Daejeon into a global hub for the robotics industry.
The initiative will leverage Daejeon's exceptional research talent and its startup and investment ecosystem to create a model for regional revitalization and to cultivate the robotics industry as a next-generation strategic sector.
KAIST's vision for this project is to develop "Human-Friendly Robots (HFR)" that are more than just automated machines; they are collaborative partners that share space, roles, and emotions with people.
The project will implement a multi-stage strategy that includes promoting the commercialization of robotics technology, supporting the startup ecosystem, securing global technological competitiveness, and developing robot commercialization platforms. This will establish a virtuous cycle of technology development, startup and investment growth, and reinvestment.
Unlike traditional startup support and scale-up programs, this project aims for the simultaneous growth of the entire robotics industry, not just individual companies. A key element is an open innovation model where leading robotics firms like Angel Robotics Inc. and EuRoBotics Inc. (led by Professor Byung-ho Yu and Professor Hyun Myung) will share common core technologies related to actuators, circuits, AI, and standardized data. This will allow startups to focus on developing robot products that directly meet customer needs.
The project team includes key KAIST robotics researchers. The project leader is Professor Jung Kim (President of the Korea Robotics Society) from the Department of Mechanical Engineering. Other participating professors include Geon-Jae Lee from the Department of Materials Science and Engineering (human augmentation sensors), Hyun Myung from the School of Electrical Engineering (winner of the QRC 2023 quadruped robot autonomous walking competition at IEEE ICRA), Kyung-Chul Kong from the Department of Mechanical Engineering (two-time champion of the Cybathlon International Competition and founder of Angel Robotics), and Suk-Hyung Bae from the Department of Industrial Design (winner of the ACM SIGGRAPH robot sketching competition).
In addition, the KAIST Technology Commercialization Office, KAIST Holdings, Global Techno Valley Lab (GTLAB), and the Daejeon Center for Creative Economy and Innovation will manage technology commercialization and valley construction. The Daejeon Technopark will also participate to provide comprehensive commercialization support.
"The strategic cooperation between Daejeon City's robotics industry nurturing plan and KAIST was the driving force behind the selection for this project," said Geon-Jae Lee, Director of the KAIST Technology Commercialization Office. "We will create a robotics innovation ecosystem based in Daejeon and systematically foster global companies to rival the likes of ABB in Switzerland and KUKA in Germany, which are considered among the top three robotics companies in the world."
< Kick-off Meeting Scene>
Project leader Jung Kim stated, "We will spearhead efforts to discover and nurture over 15 future unicorn companies by promoting the commercialization of deep-tech robotics developed at KAIST. The entire KAIST robotics research team will dedicate its full efforts to ensure that our research and development achievements lead to real-world industries and startups."
KAIST President Kwang-Hyung Lee emphasized, "As Korea's leading research-oriented university, KAIST will actively support Daejeon's growth into a global robotics hub. This project is more than just research and development; it will be a turning point for KAIST to stand at the center of the global robotics ecosystem and create a new growth engine for the region and the nation."
In collaboration with Daejeon City, KAIST plans to form an "HFR Valley Innovation Council" to share and review project outcomes, ultimately building a self-sustaining ecosystem. This initiative aims to establish Daejeon as a world-class robotics industry hub.
2025.09.03 View 3377 -
KAIST Takes the Lead in Developing Core Technologies for Generative AI National R&D Project
KAIST announced on the 15th of August that Professor Sanghoo Park of the Department of Nuclear and Quantum Engineering has won two consecutive awards for early-career researchers at two of the world's most prestigious plasma academic conferences.
Professor Park was selected as a recipient of the Early Career Award (ECA) at the Gaseous Electronics Conference (GEC), hosted by the American Physical Society, on August 4. He was also honored with the Young Investigator Award, presented by the International Plasma Chemistry Society (IPCS), on June 19.
The American Physical Society's GEC Early Career Award is given to only one person worldwide every two years, based on a comprehensive evaluation of research excellence, academic influence, and contributions to the field of plasma. The award will be presented at GEC 2025, which will be held at COEX in Seoul from October 13 to 17.
Established in 1948, the GEC is a leading academic conference in the plasma field with a 77-year history of showcasing key research achievements in all areas of plasma, including physics, chemistry, diagnostics, and application technologies. Recently, advanced application research such as eco-friendly chemical processes, next-generation semiconductors, and atomic layer and ultra-low-temperature etching technology for HBM processes have been gaining attention.
To commemorate the award, Professor Park will give an invited lecture at GEC 2025 on the topic of "Deep-Learning-Based Spectroscopic Data Analysis for Advancing Plasma Spectroscopy." In his lecture, he will use case studies to demonstrate a method that allows even non-specialists to easily and quickly perform spectroscopic data analysis—which is essential for spectroscopy, a key analytical method in modern science including plasma diagnostics—by using deep learning technology.
Professor Park also won the Young Investigator Award from the IPCS at the 26th International Symposium on Plasma Chemistry (ISPC 26), which was held in Minneapolis, USA, from June 15 to 20.
First held in 1973, the ISPC (International Symposium on Plasma Chemistry) is a representative international conference in the field of plasma chemistry, held biennially. It covers a wide range of topics, from basic plasma chemical reaction principles to applications in semiconductor processes, green energy, environmental science, and biotechnology. Researchers from industry, academia, and research institutions worldwide share their latest findings at each event. The Young Investigator Award is given to a scientist who has obtained their doctorate within the last 10 years and has demonstrated outstanding achievements in the field.
Professor Park was recognized for his leading research achievements in using plasma-liquid interactions and real-time optical diagnostic technology to environmentally fix nitrogen from the air and precisely control the quantity and types of reactive chemical species that are beneficial to the human body and the environment.
Professor Sanghoo Park stated, "It is very meaningful to receive the Young Investigator Award representing Korea at the GEC event, which is being held in Korea for the first time in its history." He added, "I am happy that my consistent interest in and achievements in fundamental plasma science have been recognized, and it is even more significant that the efforts of the KAIST research team have been acknowledged by the world's top conferences."
2025.08.16 View 3036 -
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 Ministry of Science and ICT.
In the 'Generative AI Leading Talent Cultivation Project,' KAIST was selected as a joint research institution for all three projects—two led by industry partners and one by a research institution—and will thus be tasked with the dual challenge of developing core generative AI technologies and cultivating practical, core talent through industry-academia collaborations.
Moreover, in the 'Development of a Proprietary AI Foundation Model' project, KAIST faculty members are participating as key researchers in four out of five consortia, establishing the university as a central hub for domestic generative AI research.
Each project in the Generative AI Leading Talent Cultivation Project will receive 6.7 billion won, while each consortium in the proprietary AI foundation model development project will receive a total of 200 billion won in government support, including GPU infrastructure.
As part of the 'Generative AI Leading Talent Cultivation Project,' which runs until the end of 2028, KAIST is collaborating with LG AI Research. Professor Noseong Park from the School of Computing will participate as the principal investigator for KAIST, conducting research in the field of physics-based generative AI (Physical AI). This project focuses on developing image and video generation technologies based on physical laws and developing a 'World Model.'
In particular, research being conducted by Professor Noseong Park's team and Professor Sung-Eui Yoon's team proposes a model structure designed to help AI learn the real-world rules of the physical world more precisely. This is considered a core technology for Physical AI.
Professors Noseong Park, Jae-gil Lee, Jiyoung Hwang, Sung-Eui Yoon, and Hyun-Woo Kim from the School of Computing, who have been globally recognized for their achievements in the AI field, are jointly participating in this project. This year, they have presented work at top AI conferences such as ICLR, ICRA, ICCV, and ICML, including: ▲ Research on physics-based Ollivier Ricci-flow (ICLR 2025, Prof. Noseong Park) ▲ Technology to improve the navigation efficiency of quadruped robots (ICRA 2025, Prof. Sung-Eui Yoon) ▲ A multimodal large language model for text-video retrieval (ICCV 2025, Prof. Hyun-Woo Kim) ▲ Structured representation learning for knowledge generation (ICML 2025, Prof. Jiyoung Whang).
In the collaboration with NC AI, Professor Tae-Kyun Kim from the School of Computing is participating as the principal investigator to develop multimodal AI agent technology. The research will explore technologies applicable to the entire gaming industry, such as 3D modeling, animation, avatar expression generation, and character AI. It is expected to contribute to training practical AI talents by giving them hands-on experience in the industrial field and making the game production pipeline more efficient.
As the principal investigator, Professor Tae-Kyun Kim, a renowned scholar in 3D computer vision and generative AI, is developing key technologies for creating immersive avatars in the virtual and gaming industries. He will apply a first-person full-body motion diffusion model, which he developed through a joint research project with Meta, to VR and AR environments.
Professor Tae-Kyun Kim, Minhyeok Seong, and Tae-Hyun Oh from the School of Computing, and Professors Sung-Hee Lee, Woon-Tack Woo, Jun-Yong Noh, and Kyung-Tae Lim from the Graduate School of Culture Technology, are participating in the NC AI project. They have presented globally recognized work at CVPR 2025 and ICLR 2025, including: ▲ A first-person full-body motion diffusion model (CVPR 2025, Prof. Tae-Kyun Kim) ▲ Stochastic diffusion synchronization technology for image generation (ICLR 2025, Prof. Minhyeok Seong) ▲ The creation of a large-scale 3D facial mesh video dataset (ICLR 2025, Prof. Tae-Hyun Oh) ▲ Object-adaptive agent motion generation technology, InterFaceRays (Eurographics 2025, Prof. Sung-Hee Lee) ▲ 3D neural face editing technology (CVPR 2025, Prof. Jun-Yong Noh) ▲ Research on selective search augmentation for multilingual vision-language models (COLING 2025, Prof. Kyung-Tae Lim).
In the project led by the Korea Electronics Technology Institute (KETI), Professor Seungryong Kim from the Kim Jae-chul Graduate School of AI is participating in generative AI technology development. His team recently developed new technology for extracting robust point-tracking information from video data in collaboration with Adobe Research and Google DeepMind, proposing a key technology for clearly understanding and generating videos.
Each industry partner will open joint courses with KAIST and provide their generative AI foundation models for education and research. Selected outstanding students will be dispatched to these companies to conduct practical research, and KAIST faculty will also serve as adjunct professors at the in-house AI graduate school established by LG AI Research.
Meanwhile, KAIST showed an unrivaled presence by participating in four consortia for the Ministry of Science and ICT's 'Proprietary AI Foundation Model Development' project.
In the NC AI Consortium, Professors Tae-Kyun Kim, Sung-Eui Yoon, Noseong Park, Jiyoung Hwang, and Minhyeok Seong from the School of Computing are participating, focusing on the development of multimodal foundation models (LMMs) and robot-based models. They are particularly concentrating on developing LMMs that learn common sense about space, physics, and time. They have formed a research team optimized for developing next-generation, multimodal AI models that can understand and interact with the physical world, equipped with an 'all-purpose AI brain' capable of simultaneously understanding and processing diverse information such as text, images, video, and sound.
In the Upstage Consortium, Professors Jae-gil Lee and Hyeon-eon Oh from the School of Computing, both renowned scholars in data AI and NLP (natural language processing), along with Professor Kyung-Tae Lim from the Graduate School of Culture Technology, an LLM expert, are responsible for developing vertical models for industries such as finance, law, and manufacturing. The KAIST researchers will concentrate on developing practical AI models that are directly applicable to industrial settings and tailored to each specific industry.
The Naver Consortium includes Professor Tae-Hyun Oh from the School of Computing, who has developed key technology for multimodal learning and compositional language-vision models, Professor Hyun-Woo Kim, who has proposed video reasoning and generation methods using language models, and faculty from the Kim Jae-chul Graduate School of AI and the Department of Electrical Engineering.
In the SKT Consortium, Professor Ki-min Lee from the Kim Jae-chul Graduate School of AI, who has achieved outstanding results in text-to-image generation, human preference modeling, and visual robotic manipulation technology development, is participating. This technology is expected to play a key role in developing personalized services and customized AI solutions for telecommunications companies.
This outcome is considered a successful culmination of KAIST's strategy for developing AI technology based on industry demand and centered on on-site demonstrations.
KAIST President Kwang Hyung Lee said, "For AI technology to go beyond academic achievements and be connected to and practical for industry, continuous government support, research, and education centered on industry-academia collaboration are essential. KAIST will continue to strive to solve problems in industrial settings and make a real contribution to enhancing the competitiveness of the AI ecosystem."
He added that while the project led by Professor Sung-Ju Hwang from the Kim Jae-chul Graduate School of AI, which had applied as a lead institution for the proprietary foundation model development project, was unfortunately not selected, it was a meaningful challenge that stood out for its original approach and bold attempts. President Lee further commented, "Regardless of whether it was selected or not, such attempts will accumulate and make the Korean AI ecosystem even richer."
2025.08.13 View 3628 -
KAIST sends out Music and Bio-Signs of Professor Kwon Ji-yong, a.k.a. G-Dragon, into Space to Pulsate through Universe and Resonate among Stars
KAIST (President Kwang-Hyung Lee) announced on the 10th of April that it successfully promoted the world’s first ‘Space Sound Source Transmission Project’ based on media art at the KAIST Space Research Institute on April 9th through collaboration between Professor Jinjoon Lee of the Graduate School of Culture Technology, a world-renowned media artist, and the global K-Pop artist, G-Dragon.
This project was proposed as part of the ‘AI Entertech Research Center’ being promoted by KAIST and Galaxy Corporation. It is a project to transmit the message and sound of G-Dragon (real name, Kwon Ji-yong), a singer/song writer affiliated with Galaxy Corporation and a visiting professor in the Department of Mechanical Engineering at KAIST, to space for the first time in the world.
This is a convergence project that combines science, technology, art, and popular music, and is a new form of ‘space culture content’ experiment that connects KAIST’s cutting-edge space technology, Professor Jinjoon Lee’s media art work, and G-Dragon’s voice and sound source containing his latest digital single, "HOME SWEET HOME".
< Photo 1. Professor Jinjoon Lee's Open Your Eyes Project "Iris"'s imagery projected on the 13m space antenna at the Space Research Institute >
This collaboration was planned with the theme of ‘emotional signals that expand the inner universe of humans to the outer universe.’ The image of G-Dragon’s iris was augmented through AI as a window into soul symbolizing his uniqueness and identity, and the new song “Home Sweet Home” was combined as an audio message containing the vibration of that emotion.
This was actually transmitted into space using a next-generation small satellite developed by KAIST Space Research Institute, completing a symbolic performance in which an individual’s inner universe is transmitted to outer space.
Professor Jinjoon Lee’s cinematic media art work “Iris” was unveiled at the site. This work was screened in the world’s first projection mapping method* on KAIST Space Research Institute’s 13m space antenna. This video was created using generative artificial intelligence (AI) technology based on the image of G-Dragon's iris, and combined with sound using the data of the sounds of Emile Bell rings – the bell that holds a thousand years of history, it presented an emotional art experience that transcends time and space.
*Projection Mapping: A technology that projects light and images onto actual structures to create visual changes, and is a method of expression that artistically reinterprets space.
This work is one of the major research achievements of KAIST TX Lab and Professor Lee based on new media technology based on biometric data such as iris, heartbeat, and brain waves.
Professor Jinjoon Lee said, "The iris is a symbol that reflects inner emotions and identity, so much so that it is called the 'mirror of the soul,' and this work sought to express 'the infinite universe seen from the inside of humanity' through G-Dragon's gaze."
< Photo 2. (From left) Professor Jinjoon Lee of the Graduate School of Culture Technology and G-Dragon (Visiting Professor Kwon Ji-yong of the Department of Mechanical Engineering) >
He continued, "The universe is a realm of technology as well as a stage for imagination and emotion, and I look forward to an encounter with the unknown through a new attempt to speak of art in the language of science including AI and imagine science in the form of art." “G-Dragon’s voice and music have now begun their journey to space,” said Yong-ho Choi, Galaxy Corporation’s Chief Happiness Officer (CHO). “This project is an act of leaving music as a legacy for humanity, while also having an important meaning of attempting to communicate with space.” He added, “This is a pioneering step to introduce human culture to space, and it will remain as a monumental performance that opens a new chapter in the history of music comparable to the Beatles.”
Galaxy Corporation is leading the future entertainment technology industry through its collaboration with KAIST, and was recently selected as the only entertainment technology company in a private meeting with Microsoft CEO Nadella. In particular, it is promoting the globalization of AI entertainment technology, receiving praise as a “pioneer of imagination” for new forms of AI entertainment content, including the AI contents for the deceased.
< Photo 3. Photo of G-Dragon's Home Sweet Home being sent into the space via Professor Jinjoon Lee's Space Sound Source Transmission Project >
Through this project, KAIST Space Research Institute presented new possibilities for utilizing satellite technology, and showed a model for science to connect with society in a more popular way.
KAIST President Kwang-Hyung Lee said, “KAIST is a place that always supports new imaginations and challenges,” and added, “We will continue to strive to continue creative research that no one has ever thought of, like this project that combines science, technology, and art.”
In the meantime, Galaxy Corporation, the agency of G-Dragon’s Professor Kwon Ji-yong, is an AI entertainment company that presents a new paradigm based on IP, media, tech, and entertainment convergence technology.
2025.04.10 View 10277 -
KAIST Holds 2025 Commencement Ceremony
KAIST (President Kwang-Hyung Lee) held its 2025 Commencement Ceremony at the Lyu Keun-Chul Sports Complex on the Daejeon Main Campus at 2 p.m. on the 14th of February.
< A scene from KAIST Commencement 2025 - Guests of Honor and Administrative Professors Entering the Stage headed by the color guards of the ELKA (Encouraging Leaders of KAIST) >
At this ceremony, a total of 3,144 degrees were conferred, including 785 doctorates, 1,643 masters, and 716 bachelors. With this, KAIST has produced a total of 81,156 advanced science and technology personnel, including 17,313 doctorates, 41,566 masters, and 22,277 bachelors since its establishment in 1971.
Changyu Lee from the School of Computing received the Minister of Science and ICT Award, and the Chairman of the KAIST Board of Trustees Award went to Lance Khizner Dabu Gragasin, an international student from the Philippines of the Department of Chemical and Biological Engineering. The President’s Award was given to Seoyeong Yang of the Department of Biological Sciences, and the Alumni Association President’s Award and the Development Foundation Chairman’s Award was given to Gahyeon Bae of the Department of Industrial Design and Buyeon Kim of the Department of Mechanical Engineering, respectively.
Minister of Science and ICT Sang-Im Yoo joined the ceremony to deliver a congratulatory speech and to present the awards to outstanding graduates.
< Minister Sang-Im Yoo of the Ministry of Science, Technology and ICT giving his congratulatory message at KAIST Commencement 2025 >
The valedictorian speeches were given by Minjae Kim of the School of Computing, who has practiced the value of sharing that learning is not competition but cooperation, and Mohammed Haruna Hamza of the Department of Aerospace Engineering, a Nigerian international student. Mr. Hamza is the first foreign student to represent the graduating class as valedictorian since the founding of KAIST.
Hamza lost his home and school in his home country due to a terrorist group’s bombing and moved south, but despite the adversity, he continued his studies while pursuing his dream of becoming an aerospace engineer. As a result of his efforts, Hamza was invited by the Korean government to study at KAIST. He expressed his determination to pursue his dream by saying, “I am grateful for the people and experiences that helped me overcome my adversity. The future is the result of the decisions we make today.”
A Pakistani international student was chosen as one of this year's "Most Talked about Graduates of the Year". It is Ali Syed Sheraz who wore his doctoral cap at this year’s commencement ceremony. Ali, a single father who left his one-year-old son behind in his home country, working as a university lecturer. He joined the Ph.D. program in mechanical engineering in 2019 with a passion for mechanical energy.
Ali’s academic journey was full of challenges and growth. Due to COVID-19, his research was suspended for six months, and he had difficulty continuing his studies undergoing three surgeries after a bicycle accident, including a surgery for a fractured elbow, a nose surgery, and removal of kidney stones.
However, he accepted these failure and hardship as a process of growth and participated in the ‘Failed Project Showcase’ and ‘Failure Essay Contest’ held by the KAIST Failure Society, sharing his experiences and growing into a more solid researcher.
< Most Talked about Graduate Graduate of the Year - Syed Sheraz Ali >
Despite experiencing various hardships, he found lessons to learn from them and changed his perspective, which made him unafraid of taking on new challenges. He showed through his own example that failure is not just stumbling blocks but can be a stepping stone to success by looking at his studies and personal life positively.
Furthermore, after becoming the president of the Muslim Student Association, Ali introduced halal menus to the cafeteria on campus so that more Muslim students could eat comfortably. Thanks to this change, his time at KAIST has become an opportunity to understand and experience various cultures more.
Ali is researching artificial muscles (soft actuators) with the world's highest bending strain using MXene, an artificial muscle nanomaterial that can move smoothly, in Professor Il-kwon Oh's lab.
Ali said, "After completing my Ph.D., I plan to develop soft robots, healthcare electronics, and next-generation tactile technology based on MXene, a next-generation 2D material. It is important for my juniors not to be afraid of failure and to have a challenging attitude."
Another 'Most Talked about Graduate of the Year', Mr. Sung-Hyun Jung, who graduated with a master's degree from the Graduate School of Bio Innvation Management, is the CEO of Promedius, a medical AI startup, and has commercialized an osteoporosis diagnosis software based on chest X-rays using AI, and grown it into a leading company in the bone health field.
CEO Jung's challenge shows that KAIST's management education is not just theoretical but practical enough to be applied immediately in the field. CEO Jung, who is also the father of three daughters, experienced business failure in China during the period when the conflict between Korea and China was intensifying.
He moved to Silicon Valley in the United States to revive his business and tried to acquire even small businesses, but the reality was not easy. He worked hard, standing 14 hours a day in a kimchi factory and a restaurant kitchen to make a living. After finishing his life in the United States, CEO Jung returned to Korea and had the opportunity to join Lunit, a global medical AI leader founded by KAIST graduates. CEO Jung experienced the growth of the global medical AI market firsthand with unit Chairman Seungwook Paek.
When he entered the Master's Program at the Graduate School of Bio Innvation Management in 2023 to acquire more specialized knowledge, CEO Jung had just transferred to Promedius and was in a crisis situation with only about 6 months left before the company's funds were exhausted.
While considering a change in business direction because he judged that it would be difficult to survive with existing business items, he learned keywords and investment review perspectives that venture capital (VC) pays attention to in Professor Hoonje Cho’s ‘Bio-innovation Business Startup Strategy and Practice’ class. He attracted 11.4 billion won in investment by applying the investment proposal he wrote based on what he learned from the class to actual practice.
< Most Talked about Graduate of the Year - Sung-Hyun Jung >
In addition, he applied the innovation strategy in the medical field he learned in Professor Kihwan Park’s ‘Innovation and Marketing in Bio and Pharmaceutics’ to the field of osteoporosis, and achieved the result of being selected as the first Asian company to be a corporate advisory committee member of the International Osteoporosis Foundation (IOF). Through this, he established the company as a representative global entity in the osteoporosis field in just one year.
CEO Jung, who applied what he learned from KAIST to actual management and achieved results in the global market in a short period of time, said, “I want to prove that KAIST education is not limited to theory, but is very practical.” He said, “I want to let people know that my life, once full of hardship, got on the track toward success after encountering KAIST,” and expressed his ambition, saying, “My long-term goal is to create a world-class company that is recognized globally.”
In addition, an honorary doctorate was awarded to Chairman Joong Keun Lee of Booyoung Group at the commencement ceremony.
Chairman Joong Keun Lee, who is an entrepreneur that led Booyoung Group, a leading general construction company, received the honorary doctorate in business administration, for leading the development of domestic housing welfare, education, and culture.
KAIST Provost Gyunmin Lee said, “Chairman Joong Keun Lee spared no effort in providing dedicated support for the development of domestic science and technology and the cultivation of future talents. He is awarded the honorary doctorate in recognition of his social responsibility in various fields, including scholarships and support for educational facilities, as well as domestic and international education, culture, veterans affairs, and overseas support.”
Since founding Booyoung Group in 1983, Chairman Lee has boldly entered the rental housing business, a field that large construction companies had avoided, and has played a significant role in improving the quality of life of ordinary citizens by supplying 230,000 households out of 383 complexes and approximately 300,000 households nationwide as rental housing, thereby contributing greatly to the stability of national housing.
< Chairman Joong Keun Lee giving his acceptance speech for his honorary Doctorate >
Chairman Joong Keun Lee, who has been offering hope for a sustainable future, said, “I am honored to receive an honorary doctorate from KAIST, and I hope that KAIST students will nurture their dreams and talents and grow into global talents who will contribute to national development.”
President Kwang-Hyung Lee said, “Chairman Joong Keun Lee has been carrying out various social contribution activities, and in particular, through supporting academic infrastructure, which is the core of national competitiveness, we can see his deep interest in and sense of responsibility for the development of science and technology in our country.” He added, “I am truly delighted to have him as a member of the KAIST family, and I congratulate him on behalf of all members, including our students.”
President Kwang-Hyung Lee also delivered a message of encouragement at the ceremony to charge the graduates to, “Find and keep a dream of your own, be on the lookout for opportunities, don’t be afraid of making mistakes, and do not shy away from taking on challenging tasks.” He added, “Even if you fail, don’t give up. Keep on trying so that you will get to that stage of radiate your own light on the stages where anything is possible.” (End)
2025.02.14 View 13153 -
KAIST ISSS Research Session Captivates 150↑ International Scholars, Achieve Major Success
< Photo. Scholars gatheres for NRF Information Session at Chung Keun Mo Hall >
KAIST’s International Office, headed by Vice President Soyoung Kim, successfully organized the ‘NRF Information Session for International Scholars’ on September 11, 2024, in collaboration with the National Research Foundation of Korea (NRF).
The event was held at KAIST’s main campus to enourage the international scholar’s active participation in research projects and support their establishment of stable research environment and integration into Korea’s academic community by introducing NRF’s key research programs.
Divided into two main segments – science and engineering, and humanities and social sciences – the session attracted approximately 150 international faculty and researchers from 23 universities across the nation.
The event commenced with a keynote address by Vice President Soyoung Kim, followed by a presentation from Dr. Seol Min of the National Research Foundation, who highlighted basic research initiatives in the science and technology sector. Subsequently, Professor Daniel Martin from the Digital Humanities and Social Sciences Department and Professor Thomas Steinberger from the Department of Business and Technology Management presented practical research project support case studies, sharing invaluable insights gained from their domestic research experiences.
Following the information session, participants engaged in a networking event, where researchers involved in major R&D projects exchanged insights and discussed their ongoing research initiatives.
An international professor remarked, “My understanding of NRF’s research programs for international researchers has broadened considerably. I am now more inclined to actively participate in projects organized by NRF in the future.”
Vice President Kim expressed her aspiration that the event would address the challenges faced by researchers and offer essential support to those engaged in research projects. “We will stay attuned to the needs of the research community and work towards creating a more supportive research environment,” said the VP.
Meanwhile, KAIST hosts a distinguished faculty comprising 134 professors from 22 countries and 71 researchers representing 23 nations, all contributing to groundbreaking academic achievements. Additionally, KAIST is home to over 1,000 international students from more than 100 countries, actively pursuing their studies. This diverse composition of global talent reinforces KAIST's position as a leading international hub for research and education.
2024.09.13 View 9764 -
Deep Learning Framework to Enable Material Design in Unseen Domain
Researchers propose a deep neural network-based forward design space exploration using active transfer learning and data augmentation
A new study proposed a deep neural network-based forward design approach that enables an efficient search for superior materials far beyond the domain of the initial training set. This approach compensates for the weak predictive power of neural networks on an unseen domain through gradual updates of the neural network with active transfer learning and data augmentation methods.
Professor Seungwha Ryu believes that this study will help address a variety of optimization problems that have an astronomical number of possible design configurations. For the grid composite optimization problem, the proposed framework was able to provide excellent designs close to the global optima, even with the addition of a very small dataset corresponding to less than 0.5% of the initial training data-set size. This study was reported in npj Computational Materials last month.
“We wanted to mitigate the limitation of the neural network, weak predictive power beyond the training set domain for the material or structure design,” said Professor Ryu from the Department of Mechanical Engineering.
Neural network-based generative models have been actively investigated as an inverse design method for finding novel materials in a vast design space. However, the applicability of conventional generative models is limited because they cannot access data outside the range of training sets. Advanced generative models that were devised to overcome this limitation also suffer from weak predictive power for the unseen domain.
Professor Ryu’s team, in collaboration with researchers from Professor Grace Gu’s group at UC Berkeley, devised a design method that simultaneously expands the domain using the strong predictive power of a deep neural network and searches for the optimal design by repetitively performing three key steps.
First, it searches for few candidates with improved properties located close to the training set via genetic algorithms, by mixing superior designs within the training set. Then, it checks to see if the candidates really have improved properties, and expands the training set by duplicating the validated designs via a data augmentation method. Finally, they can expand the reliable prediction domain by updating the neural network with the new superior designs via transfer learning. Because the expansion proceeds along relatively narrow but correct routes toward the optimal design (depicted in the schematic of Fig. 1), the framework enables an efficient search.
As a data-hungry method, a deep neural network model tends to have reliable predictive power only within and near the domain of the training set. When the optimal configuration of materials and structures lies far beyond the initial training set, which frequently is the case, neural network-based design methods suffer from weak predictive power and become inefficient.
Researchers expect that the framework will be applicable for a wide range of optimization problems in other science and engineering disciplines with astronomically large design space, because it provides an efficient way of gradually expanding the reliable prediction domain toward the target design while avoiding the risk of being stuck in local minima. Especially, being a less-data-hungry method, design problems in which data generation is time-consuming and expensive will benefit most from this new framework.
The research team is currently applying the optimization framework for the design task of metamaterial structures, segmented thermoelectric generators, and optimal sensor distributions. “From these sets of on-going studies, we expect to better recognize the pros and cons, and the potential of the suggested algorithm. Ultimately, we want to devise more efficient machine learning-based design approaches,” explained Professor Ryu.This study was funded by the National Research Foundation of Korea and the KAIST Global Singularity Research Project.
-Publication
Yongtae Kim, Youngsoo, Charles Yang, Kundo Park, Grace X. Gu, and Seunghwa Ryu, “Deep learning framework for material design space exploration using active transfer learning and data augmentation,” npj Computational Materials (https://doi.org/10.1038/s41524-021-00609-2)
-Profile
Professor Seunghwa Ryu
Mechanics & Materials Modeling Lab
Department of Mechanical Engineering
KAIST
2021.09.29 View 18497 -
Genomic Data Reveals New Insights into Human Embryonic Development
KAIST researchers have used whole-genome sequencing to track the development from a single fertilized-egg to a human body
Genomic scientists at KAIST have revealed new insights into the process of human embryonic development using large-scale, whole-genome sequencing of cells and tissues from adult humans. The study, published in Nature on Aug.25, is the first to analyse somatic mutations in normal tissue across multiple organs within and between humans.
An adult human body comprises trillions of cells of more than 200 types. How a human develops from a single fertilized egg to a fully grown adult is a fundamental question in biomedical science. Due to the ethical challenges of performing studies on human embryos, however, the details of this process remain largely unknown.
To overcome these issues, the research team took a different approach. They analysed genetic mutations in cells taken from adult human post-mortem tissue. Specifically, they identified mutations that occur spontaneously in early developmental cell divisions. These mutations, also called genomic scars, act like unique genetic fingerprints that can be used to trace the embryonic development process.
The study, which looked at 334 single-cell colonies and 379 tissue samples from seven recently deceased human body donors, is the largest single-cell, whole-genome analysis carried out to date. The researchers examined the genomic scars of each individual in order to reconstruct their early embryonic cellular dynamics.
The result revealed several key characteristics of the human embryonic development process. Firstly, mutation rates are higher in the first cell division, but then decrease to approximately one mutation per cell during later cell division. Secondly, early cells contributed unequally to the development of the embryo in all informative donors, for example, at the two-cell stage, one of the cells always left more progeny cells than the other. The ratio of this was different from person to person, implying that the process varies between individuals and is not fully deterministic.
The researchers were also able to deduce the timing of when cells begin to differentiate into individual organ-specific cells. They found that within three days of fertilization, embryonic cells began to be distributed asymmetrically into tissues for the left and right sides of the body, followed by differentiation into three germ layers, and then differentiation into specific tissues and organs.
“It is an impressive scientific achievement that, within 20 years of the completion of human genome project, genomic technology has advanced to the extent that we are now able to accurately identify mutations in a single-cell genome,” said Professor Young Seok Ju from the Graduate School of Medical Science and Engineering at KAIST. “This technology will enable us to track human embryogenesis at even higher resolutions in the future.”
The techniques used in this study could be used to improve our understanding of rare diseases caused by abnormalities in embryonic development, and to design new precision diagnostics and treatments for patients.
The research was completed in collaboration with Kyungpook National University Hospital, the Korea Institute of Science and Technology Information, Catholic University of Korea School of Medicine, Genome Insights Inc, and Immune Square Inc. This work was supported by the Suh Kyungbae Foundation, the Ministry of Health and Welfare of Korea, the National Research Foundastion of Korea.
-PublicationSeongyeol Park, Nanda Mali, Ryul Kim et al. ‘Clonal dynamics in early human embryogenesis inferred from somatic mutation’ Nature Online ahead of print, Aug. 25, 2021 (https://doi.org/10.1038/s41586-021-03786-8)
-ProfileProfessor Young Seok JuLab of Cancer Genomics (https://www.julab.kaist.ac.kr/)Graduate School of Medical Science and EngineeringKAIST
2021.08.31 View 13971 -
Repurposed Drugs Present New Strategy for Treating COVID-19
Virtual screening of 6,218 drugs and cell-based assays identifies best therapeutic medication candidates
A joint research group from KAIST and Institut Pasteur Korea has identified repurposed drugs for COVID-19 treatment through virtual screening and cell-based assays. The research team suggested the strategy for virtual screening with greatly reduced false positives by incorporating pre-docking filtering based on shape similarity and post-docking filtering based on interaction similarity. This strategy will help develop therapeutic medications for COVID-19 and other antiviral diseases more rapidly. This study was reported at the Proceedings of the National Academy of Sciences of the United States of America (PNAS).
Researchers screened 6,218 drugs from a collection of FDA-approved drugs or those under clinical trial and identified 38 potential repurposed drugs for COVID-19 with this strategy. Among them, seven compounds inhibited SARS-CoV-2 replication in Vero cells. Three of these drugs, emodin, omipalisib, and tipifarnib, showed anti-SARS-CoV-2 activity in human lung cells, Calu-3.
Drug repurposing is a practical strategy for developing antiviral drugs in a short period of time, especially during a global pandemic. In many instances, drug repurposing starts with the virtual screening of approved drugs. However, the actual hit rate of virtual screening is low and most of the predicted drug candidates are false positives.
The research group developed effective filtering algorithms before and after the docking simulations to improve the hit rates. In the pre-docking filtering process, compounds with similar shapes to the known active compounds for each target protein were selected and used for docking simulations. In the post-docking filtering process, the chemicals identified through their docking simulations were evaluated considering the docking energy and the similarity of the protein-ligand interactions with the known active compounds.
The experimental results showed that the virtual screening strategy reached a high hit rate of 18.4%, leading to the identification of seven potential drugs out of the 38 drugs initially selected.
“We plan to conduct further preclinical trials for optimizing drug concentrations as one of the three candidates didn’t resolve the toxicity issues in preclinical trials,” said Woo Dae Jang, one of the researchers from KAIST.
“The most important part of this research is that we developed a platform technology that can rapidly identify novel compounds for COVID-19 treatment. If we use this technology, we will be able to quickly respond to new infectious diseases as well as variants of the coronavirus,” said Distinguished Professor Sang Yup Lee.
This work was supported by the KAIST Mobile Clinic Module Project funded by the Ministry of Science and ICT (MSIT) and the National Research Foundation of Korea (NRF). The National Culture Collection for Pathogens in Korea provided the SARS-CoV-2 (NCCP43326).
-PublicationWoo Dae Jang, Sangeun Jeon, Seungtaek Kim, and Sang Yup Lee. Drugs repurposed for COVID-19 by virtual screening of 6,218 drugs and cell-based assay. Proc. Natl. Acad. Sci. U.S.A. (https://doi/org/10.1073/pnas.2024302118)
-ProfileDistinguished Professor Sang Yup LeeMetabolic &Biomolecular Engineering National Research Laboratoryhttp://mbel.kaist.ac.kr
Department of Chemical and Biomolecular EngineeringKAIST
2021.07.08 View 21839 -
Observing Individual Atoms in 3D Nanomaterials and Their Surfaces
Atoms are the basic building blocks for all materials. To tailor functional properties, it is essential to accurately determine their atomic structures. KAIST researchers observed the 3D atomic structure of a nanoparticle at the atom level via neural network-assisted atomic electron tomography.
Using a platinum nanoparticle as a model system, a research team led by Professor Yongsoo Yang demonstrated that an atomicity-based deep learning approach can reliably identify the 3D surface atomic structure with a precision of 15 picometers (only about 1/3 of a hydrogen atom’s radius). The atomic displacement, strain, and facet analysis revealed that the surface atomic structure and strain are related to both the shape of the nanoparticle and the particle-substrate interface.
Combined with quantum mechanical calculations such as density functional theory, the ability to precisely identify surface atomic structure will serve as a powerful key for understanding catalytic performance and oxidation effect.
“We solved the problem of determining the 3D surface atomic structure of nanomaterials in a reliable manner. It has been difficult to accurately measure the surface atomic structures due to the ‘missing wedge problem’ in electron tomography, which arises from geometrical limitations, allowing only part of a full tomographic angular range to be measured. We resolved the problem using a deep learning-based approach,” explained Professor Yang.
The missing wedge problem results in elongation and ringing artifacts, negatively affecting the accuracy of the atomic structure determined from the tomogram, especially for identifying the surface structures. The missing wedge problem has been the main roadblock for the precise determination of the 3D surface atomic structures of nanomaterials.
The team used atomic electron tomography (AET), which is basically a very high-resolution CT scan for nanomaterials using transmission electron microscopes. AET allows individual atom level 3D atomic structural determination.
“The main idea behind this deep learning-based approach is atomicity—the fact that all matter is composed of atoms. This means that true atomic resolution electron tomogram should only contain sharp 3D atomic potentials convolved with the electron beam profile,” said Professor Yang.
“A deep neural network can be trained using simulated tomograms that suffer from missing wedges as inputs, and the ground truth 3D atomic volumes as targets. The trained deep learning network effectively augments the imperfect tomograms and removes the artifacts resulting from the missing wedge problem.”
The precision of 3D atomic structure can be enhanced by nearly 70% by applying the deep learning-based augmentation. The accuracy of surface atom identification was also significantly improved.
Structure-property relationships of functional nanomaterials, especially the ones that strongly depend on the surface structures, such as catalytic properties for fuel-cell applications, can now be revealed at one of the most fundamental scales: the atomic scale.
Professor Yang concluded, “We would like to fully map out the 3D atomic structure with higher precision and better elemental specificity. And not being limited to atomic structures, we aim to measure the physical, chemical, and functional properties of nanomaterials at the 3D atomic scale by further advancing electron tomography techniques.”
This research, reported at Nature Communications, was funded by the National Research Foundation of Korea and the KAIST Global Singularity Research M3I3 Project.
-Publication
Juhyeok Lee, Chaehwa Jeong & Yongsoo Yang
“Single-atom level determination of 3-dimensional surface atomic structure via neural network-assisted atomic electron tomography”
Nature Communications
-Profile
Professor Yongsoo Yang
Department of Physics
Multi-Dimensional Atomic Imaging Lab (MDAIL)
http://mdail.kaist.ac.kr
KAIST
2021.05.12 View 18497