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KAIST Welcomes the Class of 2026: “Play Boldly, Learn Deeply” - President Kwang-Hyung Lee
< President Kwang-Hyung Lee pictured with NYU exchange students >
KAIST announced on December 15th that it has delivered a congratulatory message to the successful applicants of the 2026 undergraduate early admissions, sharing the university’s unique educational philosophy of encouraging challenge and failure, as well as its vision for cultivating global talent.
For the 2026 undergraduate admissions, KAIST selected future scientific leaders based on its core values and talent ideals: Creativity, Challenge, and Caring. KAIST plans to strengthen education focused on nurturing convergent talent who can cross disciplinary boundaries. The recent upward trend in applications to KAIST reflects the growing importance of scientific talent who will lead national competitiveness amidst intense global competition in AI, semiconductors, space, and biotechnology.
In his congratulatory message, President Kwang Hyung Lee emphasized, “KAIST is a place where you can play and study to your heart's content with friends, start your own business, and even experience failure. KAIST is a ‘playground for eccentrics’ where you can try anything.”
He specifically introduced a challenge-oriented academic culture, stating, “Do not fear failure. If you organize and share your experiences of failure well, you might even receive a ‘Failure Award.’”
President Lee further stressed, “KAIST is the perfect school for students who want to blaze new trails through creativity and inquiry, and for those who wish to change the world. If your goal is simply to get an ‘A’ in every subject or to secure a stable job, you do not need to come here. However, if you are a student who prefers defining your own problems over doing what others tell you and wants to challenge yourself beyond established frameworks, you must come to KAIST.”
He also highlighted the free, student-led environment by stating, “For a KAISTian, the only limit to challenge is imagination,” adding, “During my tenure as President, I have never once rejected an idea proposed by students.”
Regarding the global educational environment, President Lee explained, “KAIST is no longer just a domestic university; it is a platform where you can study, research, and be active on the world stage. We actively support students’ global experiences through the joint campus operation with New York University (NYU), the establishment of a Silicon Valley campus, and exchange programs with over 100 overseas universities.”
Meanwhile, to lead the AI era, KAIST recently established the nation’s first AI College and is building a full-scale education and research system covering all fields of artificial intelligence. The AI College plans to systematically foster next-generation AI leaders through a curriculum linked from undergraduate to graduate levels.
In addition, KAIST is strengthening education in humanities, culture, and the arts alongside science and technology. The university operates seven humanities and social science minor programs—Digital Humanities & Social Sciences, Economics, Culture Technology, Intellectual Property, Science & Technology Policy, Entrepreneurship, and Future Strategy. It also expands students' imagination and creativity through on-campus art museums, numerous galleries, and regular performances and cultural events.
Furthermore, KAIST encourages challenge and balanced growth through the “Mountaineering Scholarship,” which provides up to 700,000 KRW annually to students who complete designated hiking courses, regardless of grades or income level.
President Lee concluded his message of support by saying, “My heart is already racing at the thought of pioneering the 21st-century future with all of you. I look forward to seeing you grow into ‘stars,’ each with your own unique color, and shine on the global stage.”
< President Kwang Hyung Lee performing with the student lab club 'Gootos' at Innovate Korea 2024 >
2025.12.15 View 3378 -
AI-Engineered "Nasal Spray Antiviral Platform" Developed to Block Flu and COVID-19
<(From Left) Professor Hyun Jung Chung, Professor Ho Min Kim, Professor Ji Eun Oh>
<(From Left) Dr. Seungju Yang, Dr. Jeongwon Yun, Ph.D candidate Jae Hyuk Kwon>
Respiratory viruses that have diverse strains and mutate rapidly, such as influenza and COVID-19, are difficult to block perfectly with vaccines alone. To solve this problem, KAIST's research team has successfully developed a nasal (intranasal) antiviral platform using AI technology to overcome the existing limitations of interferon-lambda treatments—namely, being "weak against heat and disappearing quickly from the nasal mucosa."
KAIST announced on December 15th that a joint research team—consisting of Professor Ho Min Ktim and Professor Hyun Jung Chung from the Department of Biological Sciences, and Professor Ji Eun Oh from the Graduate School of Medical Science and Engineering used AI to stably redesign the interferon-lambda protein and combined it with a delivery technology that ensures effective diffusion and long-term retention in the nasal mucosa, thereby implementing a universal prevention technology for various respiratory viruses.
Interferon-lambda is an innate immune protein produced by the body to block viral infections, playing a crucial role in stopping respiratory viruses like the common cold, flu, and COVID-19. However, when formulated as a treatment for nasal administration, its actual efficacy was limited by its vulnerability to heat, degrading enzymes, mucus, and ciliary motion.
The research team used AI protein design technology to precisely reinforce the structural weaknesses of interferon-lambda.
First, they significantly increased stability by changing the loose "loop" structures of the protein—which were prone to instability—into rigid "helix" structures that lock in place like a firm spring.
Additionally, to prevent "aggregation" (proteins sticking together to form lumps), they applied "surface engineering" to make the surface more water-compatible. They also introduced "glycoengineering," adding sugar chain (glycan) structures to the protein surface to make it even more robust and stable.
As a result, the newly produced interferon-lambda showed a massive improvement in stability, surviving for two weeks 50℃ and demonstrated the ability to diffuse rapidly even through thick nasal mucus.
The research team further protected the protein by encapsulating it in microscopic "nanoliposomes" and coated the surface with "low-molecular-weight chitosan." This significantly enhanced "mucoadhesion," allowing the treatment to stick to the nasal lining for an extended period.
When this delivery platform was applied to animal models infected with influenza, a powerful inhibitory effect was confirmed, with the virus level in the nasal cavity decreasing by more than 85%.
This technology is a mucosal immune platform that can block viral infections in their early stages simply by spraying it into the nose. It is expected to be a new therapeutic strategy that can respond quickly not only to seasonal flu but also to unexpected new or mutant viruses.
Professor Ho Min Kim stated, "Through AI-based protein design and mucosal delivery technology, we have simultaneously overcome the stability and retention time limitations of existing interferon-lambda treatments. This platform, which is stable at high temperatures and stays in the mucosa for a long time, is an innovative technology that can be used even in developing countries lacking strict cold-chain infrastructure. It also has great scalability for developing various treatments and vaccines." He added, "This is a meaningful achievement resulting from multidisciplinary convergence research, covering everything from AI protein design to drug delivery optimization and immune evaluation through infection models."
This research involved Dr. Jeongwon Yun from the KAIST InnoCORE (AI-Co-Research & Eudcation for innovative Drug Institute, AI-CRED Institute) Dr. Seungju Yang from the Department of Biological Sciences, and PhD student Jae Hyuk Kwon from the Graduate School of Medical Science and Engineering as co-first authors. The results were published consecutively in the renowned international journals Advanced Science (Nov 20) and Biomaterials Research (Nov 21).
Paper 1: Computational Design and Glycoengineering of Interferon-Lambda for Nasal Prophylaxis against Respiratory Viruses, Advanced Science, DOI: 10.1002/advs.202506764
Paper 2: Intranasal Nanoliposomes Delivering Interferon Lambda with Enhanced Mucosal Retention as an Antiviral, Biomaterials Research, DOI: 10.34133/bmr.0287
This research was conducted with support from the KAIST InnoCORE Program, Mid-Career Researcher Support Program and the Bio-Medical Technology Development Program through the National Research Foundation of Korea (NRF), Healthcare Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), the KAIST Convergence Research Institute Operation Program, and the Institute for Basic Science (IBS).
2025.12.15 View 2468 -
KAIST-KakaoBank Speeds Up 'Explainable AI' by 11 Times: "Boosts Financial AI Reliability
< (From left) Professor Jaesik Choi of the Kim Jaechul Graduate School of AI, Ph.D candidate Chanwoo Lee, Ph.D candidate Youngjin Park >
The research team led by Professor Jaesik Choi of KAIST's Kim Jaechul Graduate School of AI, in collaboration with KakaoBank Corp, announced that they have developed an accelerated explanation technology that can explain the basis of an Artificial Intelligence (AI) model's judgment in real-time. This research achievement significantly increases the practical applicability of Explainable Artificial Intelligence (hereinafter XAI) technology in fields requiring real-time decision-making, such as financial services, by achieving an average processing speed 8.5 times faster, and up to 11 times faster, than existing explanation algorithms for AI model predictions.
In the financial sector, a clear explanation for decisions made by AI systems is essential. Especially in services directly related to customer rights, such as loan screening and anomaly detection, regulatory demands to transparently present the basis for the AI model's judgment are increasingly stringent. However, conventional Explainable Artificial Intelligence (XAI) technologies required the repeated calculation of hundreds to thousands of baselines to generate accurate explanations, resulting in massive computational costs. This was a major factor limiting the application of XAI technology in real-time service environments.
To address this issue, Professor Choi's research team developed the 'ABSQR (Amortized Baseline Selection via Rank-Revealing QR)' framework for accelerating explanation algorithms. ABSQR noticed that the value function matrix generated during the AI model explanation process has a low-rank structure. It introduced a method to select only a critical few baselines from the hundreds available. This drastically reduced the computation complexity, which was previously proportional to the number of baselines, to be proportional only to the number of selected critical baselines, thereby maximizing computational efficiency while maintaining explanatory accuracy.
Specifically, ABSQR operates in two stages. The first stage systematically selects important baselines using Singular Value Decomposition (SVD) and Rank-Revealing QR decomposition techniques. Unlike existing random sampling methods, this is a deterministic selection method aimed at preserving information recovery, which guarantees the accuracy of the explanation while significantly reducing computation. The second stage introduces an amortized inference mechanism, which reuses the pre-calculated weights of the baselines through cluster-based search, allowing the system to provide an explanation for the model's prediction result in real-time service environments without repeatedly evaluating the model. The research team verified the superiority of ABSQR through experiments on various real-world datasets. Tests on standard datasets across five sectors—finance, marketing, and demographics—showed that ABSQR achieved an average processing speed 8.5 times faster than existing explanation algorithms that use all baselines, with a maximum speed improvement of over 11 times. Furthermore, the degradation of explanatory accuracy due to speed acceleration was minimized, maintaining up to 93.5% of the explanation accuracy compared to the baseline algorithm. This level is sufficient to meet the explanation quality required in real-world applications.
< ABSQR Framework Overview. (1) The baseline selection stage utilizes the low-rank structure of the value function matrix to select only a small number of key baselines, and (2) the accelerated search stage reuses the pre-calculated baseline weight coefficients based on clusters. This dramatically reduces the computation complexity, which was proportional to the number of baselines, to be proportional only to the number of selected key baselines. >
A KakaoBank official stated, "We will continue relentless research and development to enhance the reliability and convenience of financial services and introduce innovative financial technologies that customers can experience." Chanwoo Lee and Youngjin Park, co-first authors from KAIST, explained the significance of the research: "This methodology solves the crucial acceleration problem for real-time application in the financial sector, proving that it is possible to provide users with the reasons behind a learning model's decision in real-time." They added, "This research provides new insights into what constitutes unnecessary computation and the selection of important baselines in explanation algorithms, practically contributing to the improvement of explanation technology efficiency." This research, co-authored by PhD candidates Chanwoo Lee and Youngjin Park from the KAIST Kim Jaechul Graduate School of AI, and researchers Hyeongeun Lee and Yeeun Yoo from the KakaoBank Financial Technology Research Institute, was presented on November 12 at the 'CIKM 2025 (ACM International Conference on Information and Knowledge Management)', the world's highest-authority academic conference in the field of information and knowledge management. ※ Paper Title: Amortized Baseline Selection via Rank-Revealing QR for Efficient Model Explanation
※ Author Information:
※ Author Information: DOI: https://doi.org/10.1145/3746252.3761036
Co-First Authors: Chanwoo Lee (KAIST Kim Jaechul Graduate School of AI), Youngjin Park (KAIST Kim Jaechul Graduate School of AI), Hyeogeun Lee (KakaoBank), Yeeun Yoo (KakaoBank)
Co-Authors: Daehee Han (KakaoBank), Junho Choi (KAIST Kim Jaechul Graduate School of AI), Kunhyung Kim (KAIST Kim Jaechul Graduate School of AI)
Corresponding Authors: Nari Kim (KAIST Kim Jaechul Graduate School of AI), Jaesik Choi (KAIST Kim Jaechul Graduate School of AI)
Meanwhile, this research achievement was conducted through KakaoBank's industry-academia research project 'Advanced Research on Explainable Artificial Intelligence Algorithms in the Financial Sector' and the Ministry of Science and ICT/Institute for Information & Communications Technology Planning and Evaluation (IITP) supported project 'Development of Explainable Artificial Intelligence Technology Providing Explainability in a Plug-and-Play Manner and Verification of Explanation Provision for AI Systems.'
2025.12.12 View 2733 -
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 3019 -
KAIST Predicts Human Group Behavior with AI! 1st Place at the World’s Top Conference… Major Success after 23 Years
<(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 this technology, the research team achieved the remarkable feat of winning the Best Paper Award at the world-renowned data mining conference “IEEE ICDM,” hosted by the Institute of Electrical and Electronics Engineers (IEEE). This is the highest honor awarded to only one paper out of 785 submissions worldwide, and marks the first time in 23 years that a Korean university research team has received this award, once again demonstrating KAIST’s technological leadership on the global research stage.
Today, group interactions involving many participants at the same time—such as online communities, research collaborations, and group chats—are rapidly increasing across society. However, there has been a lack of technology that can precisely explain both how such group behavior is structured and how individual characteristics influence it at the same time.
To overcome this limitation, Professor Kijung Shin’s research team developed an AI model called “NoAH (Node Attribute-based Hypergraph Generator),” which realistically reproduces the interplay between individual attributes and group structure.
NoAH is an artificial intelligence that explains and imitates what kinds of group behaviors emerge when people’s characteristics come together. For example, it can analyze and faithfully reproduce how information such as a person’s interests and roles actually combine to form group behavior.
As such, NoAH is an AI that generates “realistic group behavior” by simultaneously reflecting human traits and relationships. It was shown to reproduce various real-world group behaviors—such as product purchase combinations in e-commerce, the spread of online discussions, and co-authorship networks among researchers—far more realistically than existing models.
< The process of generating group interactions using NoAH >
Professor Kijung Shin stated, “This study opens a new AI paradigm that enables a richer understanding of complex interactions by considering not only the structure of groups but also individual attributes together,” and added, “Analyses of online communities, messengers, and social networks will become far more precise.”
This research was conducted by a team consisting of Professor Kijung Shin and KAIST Kim Jaechul Graduate School of AI students: master’s students Jaewan Chun and Seokbum Yoon, and doctoral students Minyoung Choe and Geon Lee, and was presented at IEEE ICDM on November 18.
※ Paper title: “Attributed Hypergraph Generation with Realistic Interplay Between Structure and Attributes” Original paper: https://arxiv.org/abs/2509.21838
< Photo from the award ceremony held on November 14 at the International Spy Museum in Washington, D.C.>
Meanwhile, including this award-winning paper, Professor Shin’s research team presented a total of four papers at IEEE ICDM this year. In addition, in 2023, the team also received the Best Student Paper Runner-up (4th place) at the same conference.
This work was supported by Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. RS-202400457882, AI Research Hub Project) (RS-2019-II190075, Artificial Intelligence Graduate School Program (KAIST)) (No. RS-2022-II220871, Development of AI Autonomy and Knowledge Enhancement for AI Agent Collaboration).
2025.12.09 View 3237 -
KAIST Drives National Competitiveness with a Dual-Impact Model for AI Research and Regional Innovation
<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) innovation hubs and key leading institutions for regional innovation.
This move aligns with the policy direction of President Jae-myung Lee. On November 4th, President Jae-myung Lee stated in a Cabinet meeting, "STEM talent is the core of national competitiveness," adding that "the increase in applicants for early admissions to the four major science and technology institutes is a very desirable phenomenon for the nation's future." In particular, the President requested that the government "actively seek concrete policies, such as expanding the allowance for transfers between STEM fields, increasing budget support, securing excellent faculty, and upgrading research and education infrastructure, because science and technology institutes can also significantly contribute to regional balanced development."
KAIST President Kwang Hyung Lee stated, "Strengthening AI research capabilities and regional balanced development is a Dual-Impact Model for AI Research and Regional Innovation that boosts national competitiveness." He confirmed that through the government's policy direction, the innovation philosophy KAIST has pursued—that 'the region is national competitiveness'—has been established as a core national direction.
In reality, KAIST continues to firmly play a central role in nurturing the talent that sustains South Korea's science and technology sector, even amid the deepening phenomenon of students flocking to medical schools. The increase in early admission applicants to the four science and technology institutes proves the successful establishment of education and research foundations where students can choose the dream of becoming science and technology professionals instead of doctors. To accelerate this trend, KAIST is focusing on establishing a National AI Research Lab and pioneering the next-generation AI research paradigm with the goal of becoming one of the top three AI powerhouses (G3) globally.
Our university was selected not only to lead the development of the next-generation bio-AI model 'K-Fold'—which surpasses Google DeepMind—and as a key participating institution in the Lunit consortium, but also as a core research team in the national AI flagship project, the 'Generative AI Leading Talent Cultivation Program.' Through discovering research topics that reflect diverse technological demands from industries, nurturing advanced AI talent, and demonstrating research outcomes in industrial settings, KAIST is being reborn as a field-ready leader guiding the AI Transformation (AX) across all of South Korea's industries.
KAIST's AI research competitiveness has also been officially recognized overseas. NVIDIA CEO Jensen Huang personally introduced KAIST as an "Amazing University" during his keynote speech at the 2025 APEC CEO Summit (Oct. 31), highly evaluating KAIST's world-class research capabilities and global collaboration potential.
Regional innovation is also gaining momentum. Our university is expanding physical AI-based research infrastructure in regions like Jeonbuk and Gyeongnam, centered around its main campus in Daejeon. Through the AI and robot-based 'Robot Valley Project' and the 'Global Innovation Startup Growth Hub Project,' in cooperation with Daejeon City, KAIST is supporting the advancement of local industries and the growth and global expansion of startups.
<ANGEL SUIT, a gait-training robot>
In particular, Sovagen—a bio-company founded on the technology of Professor Jeong Ho Lee of the KAIST Graduate School of Medical Science—recently succeeded in an overseas technology transfer of an RNA new drug for epilepsy valued at 750 billion KRW, proving a virtuous cycle model of innovation where university research translates into actual industry success.
Furthermore, the foundation for future talent development is being strengthened through efforts like promoting a culture of challenging research via the 'Failure Lab,' and early nurturing of outstanding talent through the 'Junior KAIST' and '3+4 TUBE Programs.' While setting the direction for regional university innovation through the specialized and performance-centric 'KAIST Model,' the university is also taking the lead in popularizing science and fulfilling its social responsibilities.
President Kwang Hyung Lee emphasized, "We will continue to pursue the expansion of the AI research budget and the establishment of international joint research infrastructure through close cooperation with the government." He concluded, "We will cultivate young talents who have chosen the future to be the main players in South Korean science and technology, fulfilling our central role in the 'AI Powerhouse Republic of Korea,' where the nation and the regions grow together."
2025.12.09 View 2983 -
KAIST, National Quantum Fab Research Institute Opening Ceremony and Research Building Groundbreaking Ceremony Held
<Groundbreaking Ceremony Shovel Scene for the KAIST National Quantum Fab Research Building>
KAIST announced on December 3rd that it held the opening ceremony for the National Quantum Fab Research Institute and the groundbreaking ceremony for the Quantum Fab Research Building at the KAIST main campus in Daejeon, officially commencing the construction of the nation's core infrastructure to enhance South Korea's quantum technology competitiveness.
The event began with a progress report and introduction of the institute by Yong Hoon Cho, Director of the Quantum Fab Research Institute, followed by a groundbreaking ceremony to mark the official start of the Quantum Fab Research Building's construction and an unveiling of the plaque. Approximately 50 officials attended the event, including Jang-woo Lee, Mayor of Daejeon, Kwang Hyung Lee, President of KAIST, and the presidents of the National Nanofab Center and the Korea Research Institute of Standards and Science, representing government, local government, and collaborating organizations.
<Plaque-Unveiling Scene at the Opening of the KAIST National Quantum Fab Research Institute>
Since being selected as the lead institution for the Quantum Fab in a competition held by the Ministry of Science and ICT and the Institute for Information & Communications Technology Planning & Evaluation last year, our university secured a commitment of 20 billion KRW from the Daejeon Metropolitan City for construction costs and completed the institute's establishment and design. The new Quantum Fab Research Building, with a total floor area of 2,498 ㎡, is targeted for completion in 2027.
The new building will house South Korea's largest specialized, open-access cleanroom fab for quantum devices. A total of 45 billion KRW or more will be invested by 2031, including national funds, local government funds, and KAIST's budget. Over 37 units of advanced equipment will be installed in the 1st and 3rd-floor FAB cleanrooms in stages, along with stability facilities such as Class 100-1,000 cleanliness standards, constant temperature/humidity, and emergency power supply.
The KAIST Quantum Fab operates on a fully open-access system allowing researchers to directly carry out processes. It will support processing technologies for various quantum platforms, including photons, point defects, and neutral atoms, and will also enhance user programs such as training and workshops. Phase 1 service began in July of this year, and Phase 2 full-scale operation, based on the newly installed equipment, will start in 2028.
Jang-woo Lee, Mayor of Daejeon, stated, "The KAIST open-access Quantum Fab is a core platform that will lead the industrialization of quantum technology in South Korea," adding, "Especially since the US and South Korea have designated quantum computing as a strategic field in their $350 billion technology cooperation package, Daejeon's role is becoming even more crucial."
Director Yong-Hoon Cho said, "Through a user-centric process support system, we will play a central role in the national quantum research ecosystem," adding, "Based on our research capabilities and support system, we will expand industry-academia-research cooperation and aim to leap forward as a pilot quantum fab."
President Kwang Hyung Lee remarked, "Quantum science and technology is a core strategic area that will determine the future technological hegemony," and "We will take this opening and groundbreaking ceremony as an opportunity for industry, academia, research, and government to join forces and strengthen the competitiveness of the national quantum ecosystem."
KAIST plans to focus on establishing a self-sustainable virtuous cycle system centered around the Quantum Fab, and will further dedicate efforts to enhancing national strategic technology competitiveness through the nurturing of specialized talent and the development of processing technologies for each platform.
<Bird’s Eye View of the KAIST National Quantum Fab Research Building>
2025.12.04 View 3101 -
KAIST Unveils Cause of Performance Degradation in Electric Vehicle High-Nickel Batteries: "Added with Good Intentions
<(From left in the front row) Professor Nam-Soon Choi, Professor Dong-Hwa Seo, (back row, from left) Ph.D candidate Gihoon Lee, Ph.D candidate Seung Hee Han, Ph.D candidate Jae-Seung Kim, (top) M.S candidate Junyoung Kim>
High-nickel batteries, which are high-energy lithium-ion batteries primarily used in electric vehicles, offer high energy density but suffer from rapid performance degradation. A research team from KAIST has, for the first time globally, identified the fundamental cause of the rapid deterioration (degradation) of high-nickel batteries and proposed a new approach to solve it.
KAIST announced on December 3rd that a research team led by Professor Nam-Soon Choi of the Department of Chemical and Biomolecular Engineering, in collaboration with a research team led by Professor Dong-Hwa Seo of the Department of Materials Science and Engineering, has revealed that the electrolyte additive 'succinonitrile (CN4), which has been used to improve battery stability and lifespan, is actually the key culprit causing performance degradation in high-nickel batteries.
In a battery, electricity is generated as lithium ions travel between the cathode and the anode. A small amount of CN4 is included in the electrolyte to facilitate the movement of lithium. The research team confirmed through computer calculations that CN4, which has two nitrile (-CN) structures, attaches excessively strongly to the nickel ions on the surface of the high-nickel cathode.
The nitrile structure is a 'hook-like' structure, where carbon and nitrogen are bound by a triple bond, making it adhere well to metal ions. This strong bonding destroys the protective electrical double layer (EDL) that should form on the cathode surface. During the charging and discharging process, the cathode structure is distorted (Jahn-Teller distortion), and even electrons from the cathode are drawn out to the CN4, leading to rapid damage of the cathode.
Nickel ions that leak out during this process migrate through the electrolyte to the anode surface, where they accumulate. This nickel acts as a 'bad catalyst' that accelerates electrolyte decomposition and wastes lithium, further speeding up battery degradation.
Various analyses confirmed that CN4 transforms the high-nickel cathode surface into an abnormal layer deficient in nickel, and changes the normally stable structure into an abnormal 'rock-salt structure'.
This proves the dual nature of CN4: while useful in LCO batteries (lithium cobalt oxide), it actually causes the structural collapse in high-nickel batteries with a high nickel ratio.
This research holds significant meaning as a precise analysis that goes beyond simple control of charging/discharging conditions, to even elucidating the actual electron transfer occurring between metal ions and electrolyte molecules. Based on this achievement, the research team plans to develop a new electrolyte additive optimized for high-nickel cathodes.
<Schematic diagram of the ligand coordination between CN₄ molecules and Ni³⁺ on the high-nickel cathode surface and the cathode structural degradation process>
Professor Nam-Soon Choi stated, "A precise, molecular-level understanding is essential to enhance battery lifespan and stability. This research will pave the way for the development of new additives that do not excessively bond with nickel, significantly contributing to the commercialization of next-generation high-capacity batteries."
This research, jointly led by Professor Nam-Soon Choi, Seung Hee Han, Junyoung Kim, and Gihoon Lee of the Department of Chemical and Biomolecular Engineering, and Professor Dong-Hwa Seo and Jae-Seung Kim of the Department of Materials Science and Engineering as co-first authors, was published online on November 14th in the prestigious international journal 'ACS Energy Letters' and was selected as the cover article.
※ Paper Title: Unveiling Bidentate Nitrile-Driven Structural Degradation in Ultra-High-Nickel Cathodes,
https://doi.org/10.1021/acsenergylett.5c02845
<Cover Page of International Journal(ACS Energy Letters)>
The research was supported by Samsung SDI.
2025.12.03 View 2865 -
Success in Measuring Nano Droplets, A New Breakthrough in Hydrogen, Semiconductor, and Battery Research
<(From Left) Ph.D candidate Uichang Jeong, Professor Seungbum Hong>
In hydrogen production catalysts, water droplets must detach easily from the surface to prevent blockage by bubbles, allowing for faster hydrogen generation. In semiconductor manufacturing, the quality of the process is determined by how evenly water or liquid spreads on the surface, or how quickly it dries. However, directly observing how such water or liquid spreads and moves on a surface ('wettability') at the nanoscale has been technically almost impossible until now, forcing researchers to rely mostly on conjecture. KAIST announced on December 2nd that a research team led by Professor Seungbum Hong of the Department of Materials Science and Engineering, in collaboration with Professor Jongwoo Lim's team at Seoul National University, has developed a technology to directly observe nano-sized water droplets in real-time using an Atomic Force Microscope (AFM) and to calculate the contact angle based on the droplet's shape. This research, by enabling the visual confirmation of the actual shape of nano-droplets, allows for the precise analysis of how well water droplets adhere to and detach from a surface. This is expected to be immediately applicable to various advanced technologies where liquid movement determines performance, such as hydrogen production catalysts, fuel cells, batteries, and semiconductor processes. Recently, precise measurement at the nanoscale has become crucial for wettability analysis technology. Traditional methods using large water droplets, several millimeters in size, could distinguish between hydrophilicity (where water spreads easily) and hydrophobicity (where water doesn't spread easily) on the surface. However, at the nanoscale, the droplets are too small to directly observe their shape. The research team successfully induced nano-droplets to form naturally by gently cooling the surface to a temperature where atmospheric water vapor does not freeze. They then observed these droplets using the non-contact mode of the AFM to capture their original shape. Since nano-droplets are sensitive and can be deformed by mere contact with the probe, precise control is essential. Furthermore, when the team applied this technique to the ferroelectric material lithium tantalate, they were the first to confirm a difference in the nano-droplet contact angle depending on the material's electrical direction (polarization). This difference, which was not visible with large droplets, demonstrates that nano-droplets are highly sensitive to the electrical state of the surface. The team then applied this technology to the water electrolysis catalyst used in hydrogen production, observing a single nano-droplet. This result aids in understanding how water reacts on the catalyst surface and can be used to analyze catalyst performance, particularly how well bubbles detach.
<Figure 1. Nanoscale droplet visualization using non-contact mode>
<Figure 2. Single-droplet visualization formed on sub-micron-sized water-splitting catalyst LiFeLDH particles>
Professor Seungbum Hong stated, "This research is an important case demonstrating that the Atomic Force Microscope can be used to directly visualize nano-sized water droplets and even measure the contact angle. Being able to observe the behavior of water droplets in the nano-world, which was previously invisible, will establish this as a core analysis technology for the development of next-generation energy and electronic materials." This research, in which Uichang Jeong, a PhD candidate in the KAIST Department of Materials Science and Engineering, participated as the first author, was published on October 17th in 'ACS Applied Materials and Interfaces', a prestigious journal in the field of new materials and chemical engineering published by the American Chemical Society (ACS).
Paper Title: Nanoscale Visualization and Contact Angle Analysis of Water Droplets on Ferroelectric Materials
DOI: https://doi.org/10.1021/acsami.5c14404
This research was supported by the Ministry of Science and ICT and the National Research Foundation of Korea.
2025.12.03 View 1882 -
The World's Smallest Fully Wireless Neural Implant Achieved
< (From left) Sunwoo Lee, KAIST Joint Professor, Alyosha Molnar, Cornell University Professor >
The human brain contains about 100 billion brain cells, and the chemical and electrical signals they exchange create most mental functions. Neural implant technology for precisely reading these signals is essential for the research and treatment of neurodegenerative diseases. A research team from KAIST and international collaborators has successfully implemented a fully wireless, ultra-small implant, which was previously only a theoretical possibility, going beyond simple miniaturization and weight reduction of neural implants.
KAIST announced on the November 27th that a joint research team led by Professor Sunwoo Lee (Joint Professor in Materials Science and Engineering at KAIST and from the School of Electrical and Electronic Engineering at Nanyang Technological University, NTU) and Professor Alyosha Molnar's team from Cornell University in the US has developed 'MOTE (Micro-Scale Opto-Electronic Tetherless Electrode)', an ultra-small wireless neural implant less than 100 micrometers (µm) — smaller than a grain of salt. The team successfully implanted this device into the brains of laboratory mice and stably measured brain waves for one year.
In the brain, invisible, minute electrical signals constantly move, creating our various mental activities such as memory, judgment, and emotion. The technology to directly measure these signals outside the body without connecting wires has been highlighted as key for brain research and the treatment of neurological disorders like dementia and Parkinson's disease.
However, existing implants have limitations: their thick wired structure causes movement in the brain, leading to inflammation and signal degradation over time, and their size and heat generation restrict long-term use.
To overcome these limitations, the research team created an ultra-small circuit based on the existing semiconductor process (CMOS) and combined it with their self-developed ultra-fine Micro-LEDs (µLEDs) to drastically miniaturize the device. They also applied a special surface coating to significantly enhance durability, allowing it to withstand the biological environment for a long time.
The resulting MOTE is less than 100 µm thick and has a volume of less than 1 nanoliter, making it thinner than a human hair and smaller than a grain of salt, the world's smallest level among currently reported wireless neural implants.
Another key feature of MOTE is that it is a fully wireless system that requires no battery. The device is structured to receive external light to generate power, detect brain waves, and then transmit the information back outside embedded in the light signal using Pulse Position Modulation (PPM).
This method drastically reduces energy consumption, minimizes the risk of heat generation, and eliminates the need for battery replacement, enabling long-term use.
The research team conducted a one-year long-term experiment by implanting the ultra-small MOTE into the brains of mice. The results showed normal brain wave measurement over the extended period, with almost no inflammation observed around the implant and no degradation in device performance.
This is considered the first clear demonstration that an ultra-small wireless implant can maintain normal function for a prolonged time inside a living body.
< MOTE neural implant on a salt crystal (left), MOTE neural implants after 296 days of implantation in a laboratory mouse (right) >
Professor Sunwoo Lee stated, "The greatest significance of the newly developed neural implant lies in its actual implementation of a fully wireless, ultra-small implant that was previously only anticipated as a possibility, going beyond simple miniaturization and weight reduction." He added, "This proves the technological possibility of resolving not only the known unknowns raised during the development and use of wireless neural implants, but also the unknown unknowns that newly emerge during the actual development process."
He further added, "This technology will be broadly applicable not only to brain science research but also to nervous system disease monitoring and the development of long-term recording-based treatment technologies."
The research results were published online in the prestigious journal Nature Electronics on November 3rd. ※ Paper Title: A subnanolitre tetherless optoelectronic microsystem for chronic neural recording in awake mice, DOI: https://doi.org/10.1038/s41928-025-01484-1
This research was supported by the US National Institutes of Health (NIH), Nanyang Technological University (Singapore), the Singapore National Research Foundation, the Singapore Ministry of Education, and the ASPIRE League Partnership Seed Fund 2024. The specialized fabrication processes were conducted at the Cornell NanoScale Facility (part of the US National Nanotechnology Coordinated Infrastructure, NNCI) and NTU's Nanyang NanoFabrication Centre.
2025.11.27 View 2588 -
How Does AI Think? KAIST Achieves First Visualization of the Internal Structure Behind AI Decision-Making
<(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 (President Kwang Hyung Lee) announced on the 26th of November that Professor Jaesik Choi’s research team at the Kim Jaechul Graduate School of AI has developed a new explainable AI (XAI) technology that visualizes the concept-formation process inside a model at the level of circuits, enabling humans to understand the basis on which AI makes decisions.
The study is evaluated as a significant step forward that allows researchers to structurally examine “how AI thinks.”
Inside deep learning models, there exist basic computational units called neurons, which function similarly to those in the human brain. Neurons detect small features within an image—such as the shape of an ear, a specific color, or an outline—and compute a value (signal) that is transmitted to the next layer.
In contrast, a circuit refers to a structure in which multiple neurons are connected to jointly recognize a single meaning (concept). For example, to recognize the concept of cat ear, neurons detecting outline shapes, neurons detecting triangular forms, and neurons detecting fur-color patterns must activate in sequence, forming a functional unit (circuit).
Up until now, most explanation techniques have taken a neuron-centric approach based on the idea that “a specific neuron detects a specific concept.” However, in reality, deep learning models form concepts through cooperative circuit structures involving many neurons. Based on this observation, the KAIST research team proposed a technique that expands the unit of concept representation from “neuron → circuit.”
The research team’s newly developed technology, Granular Concept Circuits (GCC), is a novel method that analyzes and visualizes how an image-classification model internally forms concepts at the circuit level.
GCC automatically traces circuits by computing Neuron Sensitivity and Semantic Flow. Neuron Sensitivity indicates how strongly a neuron responds to a particular feature, while Semantic Flow measures how strongly that feature is passed on to the next concept. Using these metrics, the system can visualize, step-by-step, how basic features such as color and texture are assembled into higher-level concepts.
The team conducted experiments in which specific circuits were temporarily disabled (ablation). As a result, when the circuit responsible for a concept was deactivated, the AI’s predictions actually changed.
In other words, the experiment directly demonstrated that the corresponding circuit indeed performs the function of recognizing that concept.
This study is regarded as the first to reveal, at a fine-grained circuit level, the actual structural process by which concepts are formed inside complex deep learning models. Through this, the research suggests practical applicability across the entire explainable AI (XAI) domain—including strengthening transparency in AI decision-making, analyzing the causes of misclassification, detecting bias, improving model debugging and architecture, and enhancing safety and accountability.
The research team stated, “This technology shows the concept structures that AI forms internally in a way that humans can understand,” adding that “this study provides a scientific starting point for researching how AI thinks.”
Professor Jaesik Choi emphasized, “Unlike previous approaches that simplified complex models for explanation, this is the first approach to precisely interpret the model’s interior at the level of fine-grained circuits,” and added, “We demonstrated that the concepts learned by AI can be automatically traced and visualized.”
< Overview of the Conceptual Circuit Proposed by the Research Team >
This study, with Ph.D. candidates Dahee Kwon and Sehyun Lee from KAIST Kim Jaechul Graduate School of AI as co–first authors, was presented on October 21 at the International Conference on Computer Vision (ICCV).
Paper title: Granular Concept Circuits: Toward a Fine-Grained Circuit Discovery for Concept Representations
Paper link: https://openaccess.thecvf.com/content/ICCV2025/papers/Kwon_Granular_Concept_Circuits_Toward_a_Fine-Grained_Circuit_Discovery_for_Concept_ICCV_2025_paper.pdf
This research was supported by the Ministry of Science and ICT and the Institute for Information & Communications Technology Planning & Evaluation (IITP) under the “Development of Artificial Intelligence Technology for Personalized Plug-and-Play Explanation and Verification of Explanation” project, the AI Research Hub Project, and the KAIST AI Graduate School Program, and was carried out with support from the Defense Acquisition Program Administration (DAPA) and the Agency for Defense Development (ADD) at the KAIST Center for Applied Research in Artificial Intelligence.
2025.11.26 View 3450 -
KAIST K HERO Rides Nuri Rocket, Next Generation Micro Hall Thruster Technology Verified in Space
< (From left) Ph.D candidate Jaehong Park, COSMOVY researcher Yoonsoo Kim, Professor Wonho Choe, Ph.D candidate Dongha Park, M.S candidate Seungbeom Heo >
KAIST announced on the November 26th that the CubeSat 'K-HERO (KAIST Hall Effect Rocket Orbiter)', developed by the research team of Professor Wonho Choe from the Department of Nuclear and Quantum Engineering, is scheduled to launch into space aboard the 4th Nuri rocket launch vehicle on November 27th from the Naro Space Center in Goheung, Jeollanam-do.
This 4th Nuri launch is the first to be managed by the private company Hanwha Aerospace, which received technology transfer from the Korea Aerospace Research Institute (KARI), marking a significant milestone in the transformation of the domestic space industry. Along with the main payload, the Next-Generation Medium Satellite 3, twelve CubeSats developed by industry, academia, and research institutions will be onboard, with K-HERO being one of them.
The development of K-HERO was officially initiated when Professor Wonho Choe's research team was selected as the basic satellite development team in the '2022 CubeSat Competition' organized by KARI.
The basic satellite is a technology verification satellite designed to confirm whether the design and core components operate normally in the space environment before proceeding with the flight model (FM) production. K-HERO is a 3U standard CubeSat with dimensions of $10\text{ cm}$ (width) $\times$ $10\text{ cm}$ (length) $\times$ $30\text{ cm}$ (height) and a weight of $3.9\text{ kg}$. It was designed to satisfy all stability, electrical specifications, and interface conditions with the launch vehicle.
The core mission of K-HERO is to directly verify the in-space operation of the 150 W class micro-satellite Hall thruster developed by the research team.
The Hall thruster can be simply described as a 'space engine powered by electricity'. It is an electric propulsion engine that moves the satellite slowly but very efficiently using electricity.
Instead of burning a lot of fuel to generate instantaneous thrust, like a rocket, it works by using electricity to turn gas (Xenon) into a plasma state and rapidly accelerating it backward to push the satellite forward. Hall thrusters are considered a core technology for the era of small and constellation satellites due to their high fuel efficiency.
< Image of plasma generation in the micro-satellite Hall thruster mounted on the K-HERO CubeSat >
Hall thrusters are already a proven technology, having been used in large satellites and deep-space probes for over 20-30 years. However, their size and power requirements were large, so in the past, they were mainly operated on large geostationary (GEO) communication/broadcasting satellites and used by NASA and ESA deep-space probes for long-distance flights.
Recently, the emergence of the SpaceX Starlink satellite constellation has led to a surge in demand for small and micro electric thrusters. As the global space industry shifts towards satellite constellations, 'small and efficient thrusters' have become essential technology.
K-HERO is the first case of direct in-space demonstration of a micro Hall thruster made with domestic technology, and it is expected to be an important milestone in enhancing domestic technological competitiveness.
Professor Wonho Choe's research team began research on Hall thrusters in Korea in 2003, securing original technology based on plasma physics. In 2013, they successfully mounted a 200 W class Hall thruster on the 'KAIST Science and Technology Satellite 3,' proving its practical utility. This time, they have improved the design to operate even at a lower power of 30 W, developing a next-generation model aimed at micro-satellites.
COSMOVY Inc, a laboratory startup founded by Professor Wonho Choe's research team, also participated in the development of K-HERO, further strengthening the foundation for technology commercialization.
< K-HERO CubeSat being loaded into the Nuri rocket's CubeSat dispenser (Photo source: Korea Aerospace Research Institute) >
Professor Wonho Choe stated, "Starting with K-HERO, the number of small satellites equipped with electric thrusters will increase significantly in Korea. The Hall thruster being verified this time can be utilized for various missions, including low-Earth orbit constellation surveillance and reconnaissance satellites, 6G communication satellites, very-low-Earth orbit high-resolution satellites, and asteroid probes."
President Kwang Hyung Lee stated, "The launch of K-HERO is a significant opportunity to directly verify KAIST's electric propulsion technology on a micro-satellite platform once again in space, and it will be an important turning point that will further enhance the technological competitiveness of small satellites in Korea. KAIST will continue to contribute to the development of our country's space technology.
2025.11.26 View 2921