KAIST

< (From left) Professor Sung Gap Im (KAIST), Dr. Seonghyeon Park (KAIST), M.S candidate Sang Yu Sun (KAIST), Dr. Mi-Young Son (KRIBB), (Top right) Dr. Tae Geol Lee (KRISS), Dr. Jin Gyeong Son (KRISS) > Intestinal Stem Cells (ISCs) derived from a patient's own cells have garnered significant attention as a new alternative for treating intractable intestinal diseases due to their low risk of rejection. However, clinical application has been limited by safety and regulatory issues arising from conventional culture methods that rely on animal-derived components (xenogeneic components). A KAIST research team has developed an advanced culture technology that stably grows ISCs without animal components while simultaneously enhancing their migration to damaged tissues and regenerative capabilities. KAIST announced on December 23rd that a joint research team—led by Professor Sung Gap Im from the Department of Chemical and Biomolecular Engineering, Dr. Tae Geol Lee from the Nano-Bio Measurement Group at the Korea Research Institute of Standards and Science and Dr. Mi-Young Son from the Stem Cell Convergence Research Center at the Korea Research Institute of Bioscience and Biotechnology  has developed a polymer-based culture platform that dramatically improves the migration and regeneration of ISCs in a xenogeneic-free environment. To overcome obstacles in the clinical application of stem cell therapies—such as the risk of virus transmission to patients when using substances derived from mouse fibroblasts or Matrigel—the joint research team developed "PLUS" (Polymer-coated Ultra-stable Surface). This polymer-based culture surface technology functions effectively without any animal-derived materials. < Figure 1. Precise control of polymer coating and surface modification via initiated Chemical Vapor Deposition (iCVD) process > PLUS is a synthetic polymer surface coated via a vapor deposition method. By precisely controlling surface energy and chemical composition, it significantly enhances the adhesion and mass-culture efficiency of ISCs. Notably, it maintains identical culture performance even after being stored at room temperature for three years, securing industrial scalability and storage convenience for stem cell therapeutics. Through proteomics analysis*, the research team identified that the expression of proteins related to cytoskeletal reorganization significantly increased in ISCs cultured on the PLUS environment. Proteomics Analysis: A method used to simultaneously analyze the types and quantitative changes of all proteins present within a cell or tissue. Specifically, the team confirmed that increased expression of cytoskeleton-binding and actin-binding proteins leads to a stable restructuring of the internal cellular architecture. This provides the power source for stem cells to move faster and more actively across the substrate. < Figure 2. Elucidation of the mechanism for enhanced ISC migration through precision proteomics analysis > Real-time observations using holotomography microscopy revealed that ISCs cultured on PLUS exhibited a migration speed approximately twice as fast as those on conventional surfaces. Furthermore, in a damaged tissue model, the cells demonstrated outstanding regenerative performance, repairing more than half of the damage within a single week. This proves that PLUS activates the cytoskeletal activity of stem cells, thereby boosting their practical tissue regeneration capabilities. The newly developed PLUS culture platform is evaluated as a technology that will significantly enhance the safety, mass production, and clinical feasibility of ISCs derived from human pluripotent stem cells (hPSCs). By elucidating the mechanism that simultaneously strengthens the survival, migration, and regeneration of stem cells in a xenogeneic-free environment, the team has established a foundation to fundamentally resolve safety, regulatory, and productivity issues in stem cell therapy. Professor Sung Gap Im of KAIST stated, "This research provides a synthetic culture platform that eliminates the dependence on xenogeneic components—which has hindered the clinical application of stem cell therapies—while maximizing the migration and regenerative capacity of stem cells. It will serve as a catalyst for a paradigm shift in the field of regenerative medicine." Dr. Seonghyeon Park (KAIST), Sang Yu Sun (KAIST), and Dr. Jin Gyeong Son (KRISS) participated as first authors. The research findings were published online on November 26th in Advanced Materials, the leading academic journal in materials science. Paper Title: Tailored Xenogeneic-Free Polymer Surface Promotes Dynamic Migration of Intestinal Stem Cells DOI: 10.1002/adma.202513371 This research was conducted with support from the Ministry of Science and ICT, the Ministry of SMEs and Startups, the National Research Foundation of Korea, the National Council of Science and Technology Research, KRISS, KRIBB, and the National NanoFab Center.  

<(From Left) M.S candidate Inhyo Lee, Ph.D candidate Heekyu Kim, Ph.D candidate joonyoung Kim, Professor Seunghwa Ryu> Most of the plastic products we use are made through injection molding, a process in which molten plastic is injected into a mold to mass-produce identical items. However, even slight changes in conditions can lead to defects, so the process has long relied on the intuition of highly skilled workers. Now, KAIST researchers have proposed an AI-based solution that autonomously optimizes processes and transfers manufacturing knowledge, addressing concerns that expertise could be lost due to the retirement of skilled workers and the increase in foreign labor. KAIST (President Kwang Hyung Lee) announced on the 22nd of December that a research team led by Professor Seunghwa Ryu from the Department of Mechanical Engineering · InnoCORE PRISM-AI Center has, for the first time in the world, developed generative AI technology that autonomously optimizes injection molding processes, along with an LLM-based knowledge transfer system that makes on-site expertise accessible to anyone. The team also reported that these achievements were published consecutively in an internationally renowned journal. The first achievement is a generative AI–based process inference technology that automatically infers optimal process conditions based on environmental changes or quality requirements. Previously, whenever temperature, humidity, or desired quality levels changed, skilled workers had to rely on trial and error to readjust conditions. The research team implemented a diffusion model–based approach that reverse-engineers process conditions satisfying target quality requirements, using environmental data and process parameters collected over several months from an actual injection molding factory. In addition, the team built a surrogate model that substitutes for actual production, enabling quality prediction without running the real process. As a result, they achieved an error rate of just 1.63%, significantly lower than the 23~44% error rates of representative existing technologies such as GAN* and VAE** models traditionally used for process prediction. Experiments applying the AI-generated conditions to real processes confirmed successful production of acceptable products, demonstrating practical applicability.  *GAN (Generative Adversarial Network): a method in which two AI models compete with each other to generate data  **VAE (Variational Autoencoder): a method that compresses and learns common patterns in data and then reconstructs them <Figure 1. Generative AI–Based Process Reasoning Technology> The second achievement is the IM-Chat, an LLM-based knowledge transfer system designed to address skilled worker retirement and multilingual work environments. IM-Chat is a multi-agent AI system that combines large language models (LLMs) with retrieval-augmented generation (RAG), serving as an AI assistant for manufacturing sites by providing appropriate solutions to problems encountered by novice or foreign workers. When a worker asks a question in natural language, the AI understands it and, if necessary, automatically calls the generative process inference AI, simultaneously providing optimal process condition calculations along with relevant standards and background explanations. For example, when asked, “What is the appropriate injection pressure when the factory humidity is 43.5%?”, the AI calculates the optimal condition and presents the supporting manual references as well. With support for multilingual interfaces, foreign workers can receive the same level of decision-making support. This research is regarded as a core manufacturing AI transformation (AX) technology that can be extended beyond injection molding to molds, presses, extrusion, 3D printing, batteries, bio-manufacturing, and other industries. In particular, the work is significant in that it presents a paradigm for autonomous manufacturing AI, integrating generative AI and LLM agents through a Tool-Calling approach*, enabling AI to make its own judgments and invoke necessary functions.  *Tool-Calling approach: a method in which AI autonomously calls and uses the functions or programs required for a given situation <Figure 2. Large Language Model–Based Multilingual Knowledge Transfer Multi-Agent IM-Chat> <Figure 3. Example of Operation of the Large Language Model (LLM)–Based Multilingual Knowledge Transfer Multi-Agent IM-Chat> <Figure 4. Illustration of the Application of an LLM-Based Multilingual Knowledge Transfer Multi-Agent IM-Chat (AI-Generated)> Professor Seunghwa Ryu explained, “This is a case where we addressed fundamental problems in manufacturing in a data-driven way by combining AI that autonomously optimizes processes with LLMs that make on-site knowledge accessible to anyone,” adding, “We will continue expanding this approach to various manufacturing processes to accelerate intelligence and autonomy across the industry.” This research involved doctoral candidates Junhyeong Lee, Joon-Young Kim, and Heekyu Kim from the Department of Mechanical Engineering as co–first authors, with Professor Seunghwa Ryu as the corresponding author. The results were published consecutively in the April and December issues of Journal of Manufacturing Systems (JCR 1/69, IF 14.2), the world’s top-ranked international journal in engineering and industrial fields.  ※ Paper 1: “Development of an Injection Molding Production Condition Inference System Based on Diffusion Model,” DOI: https://doi.org/10.1016/j.jmsy.2025.01.008 ※ Paper 2: “IM-Chat: A multi-agent LLM framework integrating tool-calling and diffusion modeling for knowledge transfer in injection molding industry,” DOI: https://doi.org/10.1016/j.jmsy.2025.11.007 This research was supported by the Ministry of Science and ICT, the Ministry of SMEs and Startups, and the Ministry of Trade, Industry and Energy.

< (From left) KAIST Ph.D. candidate Hyeontaek Hwang, Research Professor Yalew Kidane, Senior Researcher Young-jong Lee, Researcher Geon-woo Park, and (Top) Professor Daeyoung Kim > When buying seafood at a supermarket, you may have wondered where the fish was caught and what process it went through to reach your dinner table. However, due to complex distribution processes, it has been difficult to transparently track that path. KAIST’s research team has developed a digital technology that solves this problem, allowing the movement path of seafood to be checked at a glance based on international standards recognized worldwide. KAIST announced on December 19th that "OLIOPASS," a GS1 international standard-based digital transformation solution developed by Director Daeyoung Kim (Professor, School of Computing) of the KAIST Auto-ID Labs Busan Innovation Center, has passed the rigorous performance verification of the GDST (Global Dialogue on Seafood Traceability). It is the first in Korea to obtain the "GDST Capable Solution" certification. < (Left) GDST Global Certification Logo, (Right) KAIST OLIOPASS Platform Logo > Only 13 technologies worldwide have received this GDST certification. Among them, only 7 entities, including KAIST, support "Full Chain" traceability technology, which manages the entire process from production and processing to distribution and sales. The GDST is an international organization established in 2015 at the suggestion of the World Economic Forum (WEF). It helps record and share information on all seafood movement processes digitally, according to the GS1 international standard agreed upon by the global community. This can be compared to creating a "common language for the supply chain" used worldwide. The GDST is a global standard system that increases the reliability of seafood history information by defining Key Data Elements (KDEs) that must be recorded during the movement of seafood and Critical Tracking Events (CTEs) that define when, where, and what moved, based on international standards. As major food distribution companies in the United States and Europe have recently begun requiring GDST compliance, this standard is becoming a de facto essential requirement for entering the global market. Since 2019, KAIST has participated as a founding member of GDST and has played a key role in designing seafood traceability models and system-to-system information interoperability. In particular, with the U.S. Food and Drug Administration (FDA) announcing the mandatory enforcement of food traceability (FSMA 204) starting in July 2028, this certification is significant as it secures a technical solution for domestic companies to meet global market regulations. OLIOPASS, which received certification on November 5th, is a digital traceability platform that combines KAIST's IoT technology with international standards (GS1 EPCIS 2.0, GS1 Digital Link). It records and shares movement information of various products and assets in a standardized language and utilizes blockchain technology to fundamentally prevent forgery or alteration. Even if systems differ between companies, history data is seamlessly linked. Furthermore, OLIOPASS is designed as an "AI-ready data" infrastructure, allowing for the easy application of next-generation AI technologies such as Large Multimodal Models (LMM), AI agents, knowledge graphs, and ontologies. This allows it to serve as a platform that supports both digital and AI transformation beyond simple history management. Daeyoung Kim, Director of the KAIST Auto-ID Labs Busan Innovation Center, stated, "This certification is an international recognition of our capability in reliable data technology across the global supply chain. We will expand OLIOPASS beyond seafood and food into various fields such as pharmaceuticals, logistics, defense, and smart cities, ensuring KAIST’s technology grows into a platform used by the world." ※ Related Link: https://thegdst.org/verified-gdst-capable-solutions/ < List of Certified Organizations >  

<(From Upper Left) Ph.D candidate Seong-Bin Lee, CEO Namsuk Cho, Researcher Geonho Lee, Researcher Seungju Lee, M.S candidate Junseo Kim,  Principal Researcher Jong Tai Jang, Professor Se Kwon Kim, Professor Taewon Seo, Center Director Chae Kyung Sim, Professor Dae-Young Lee> <(From Left) Principal Researcher Jong Tai Jang, CEO Namsuk Cho, Ph.D candidate Seong-Bin Lee,  Professor Dae-Young Lee,Center Director Chae Kyung Sim> New variable-diameter wheel overcomes steep terrain and harsh lunar conditions, paving the way for subsurface lunar exploration.  A joint research team from the Korea Advanced Institute of Science and Technology (KAIST) and the Unmanned Exploration Laboratory (UEL) has developed a transformative wheel capable of navigating the Moon’s most extreme terrains, including steep lunar pits and lava tubes.   The study presents a novel "origami-inspired" deployable airless wheel that can significantly expand its diameter to traverse obstacles that would trap traditional rovers. The research was published in the December issue of Science Robotics.   The Challenge: Small Rovers vs. Big Obstacles Lunar lava tubes and pits are prime candidates for future human habitats due to their natural shielding from cosmic radiation and extreme temperature fluctuations, but accessing them is perilous. Deploying a swarm of small, independent rovers can be an effective strategy to mitigate the risks associated with a single large rover. This strategy ensures mission continuity through redundancy; even if some units fail, the remaining rovers can complete the exploration. However, small rovers face an inherent physical limitation: their compact wheel size severely restricts their ability to traverse steep, rugged terrains like lunar pit entrances. While variable-diameter wheels could theoretically solve this by offering high traversability on demand, creating such a system for the Moon has been a formidable challenge. Designing a lightweight transformable wheel that can withstand the harsh lunar environment—specifically the abrasive dust and the vacuum that causes metal parts to fuse ("cold welding")—has remained a significant engineering hurdle.   A Transformable Wheel for Extreme Environments To conquer these obstacles, a research team, led by Professor Dae-Young Lee from KAIST’s Department of Aerospace Engineering, developed a new type of compliant wheel that eliminates complex mechanical joints. By applying the structural principles of the “Da Vinci bridge” combined with origami design, the team created a wheel that uses the flexibility of its materials to transform. Capable of expanding from a compact 230 mm to 500 mm in diameter, the wheel allows compact rovers to maintain a low profile during transport, yet scale significant obstacles once deployed. Crucially, by utilizing a specialized elastic metal frame and fabric tensioners instead of traditional hinges, the design ensures reliable operation in the harsh lunar environment, effectively resisting the risks of cold welding and mechanical failure caused by fine dust. The team rigorously tested the wheel’s capabilities using artificial lunar soil (simulants). The wheel demonstrated superior traction on loose slopes and proved its structural integrity by withstanding a drop impact equivalent to a 100-meter fall in lunar gravity.   < Driving performance field tests conducted in various environments such as artificial lunar soil, extreme temperatures, mud, and rocky terrain >   Scientific and Engineering Significance The project brought together experts from major Korean space institutes to validate the technology's potential. Prof. Lee highlighted the wheel as a practical and reliable solution for navigating the Moon's most difficult terrains, expressing optimism that this unique technology would position the team as leaders in future lunar missions despite remaining challenges involving communication and power. From a scientific perspective, Dr. Chae Kyung Sim, Head of the Planetary Science Group at KASI (Korea Astronomy and Space Science Institute), emphasized the value of lunar pits as "natural geological heritages," noting that this research significantly lowers the technical barriers to accessing these sites and brings actual exploration missions closer to reality. Furthermore, Dr. Jongtae Jang, Principal Researcher at KARI (Korea Aerospace Research Institute), underscored the engineering rigor behind the design, explaining that the wheel was meticulously optimized and validated using mathematical thermal models to endure the Moon’s extreme 300-degree temperature fluctuations.   About KAIST KAIST is the first and top science and technology university in Korea. KAIST has been the gateway to advanced science and technology, innovation, and entrepreneurship, and our graduates have been key ingredients behind Korea’s innovations.   About UEL(Unmanned Exploration Laboratory), inc. has cutting edge technology about planetary exploration mobility robotics in the Republic of Korea. UEL provides unmanned exploration systems from design and manufacturing the mobility platforms to perform the rover missions on Earth, the Moon, and beyond.   Journal Reference Science Robotics DOI   10.1126/scirobotics.adx2549

< Professor Junmo Kim and Ph.D. candidate Minchan Kwon, School of Electrical Engineering > No matter how much data they learn, why do Artificial Intelligence (AI) models often miss the mark on human intent? Conventional "comparison learning," designed to help AI understand human preferences, has frequently led to confusion rather than clarity. A KAIST research team has now presented a new learning solution that allows AI to accurately learn human preferences even with limited data by assigning it a "private tutor." On December17th, a research team led by Professor Junmo Kim of KAIST School of Electrical Engineering announced the development of "TVKD" (Teacher Value-based Knowledge Distillation), a reinforcement learning framework that significantly improves data efficiency and learning stability while effectively reflecting human preferences. Existing AI training methods typically rely on collecting massive amounts of "preference comparison" data—simple structures like "A is better than B." However, this approach requires vast datasets and often causes the AI to become confused in ambiguous situations where the distinction is unclear. To solve this problem, the research team proposed a method in which a ‘Teacher model’ that has first deeply understood human preferences delivers only the core information to a ‘Student model.’ This can be compared to a private tutor who organizes and teaches complex content, and the research team named this ‘Preference Distillation.’ The biggest feature of this technology is that instead of simply imitating ‘good or bad,’ it is designed so that the teacher model learns a ‘Value Function’ that numerically judges how valuable each situation is, and then delivers this to the student model. Through this, the AI can learn by making comprehensive judgments about ‘why this choice is better’ rather than fragmentary comparisons, even in ambiguous situations. < Conceptual diagram of TVKD: After teaching the human preference dataset to the teacher model, learning proceeds by delivering the teacher's information and the dataset to the student model > The core of this technology is twofold. First, by reflecting value judgments that consider the entire context into the student model, learning that understands the overall flow rather than fragmentary answers has become possible. Second, a technique was introduced to adjust learning importance according to the reliability of preference data. Clear data is significantly reflected in learning, while the influence of ambiguous or noisy data is reduced, allowing the AI to learn stably even in realistic environments. As a result of the research team applying this technology to various AI models and conducting experiments, it showed more accurate and stable performance than methods previously known to have the best performance. In particular, it recorded achievements that stably outperformed existing top technologies in major evaluation indices such as MT-Bench and AlpacaEval. Professor Junmo Kim said, “In reality, human preference data is not always sufficient or perfect,” and added, “This technology will allow AI to learn consistently even under such constraints, so it will be highly practical in various fields.” < Performance comparison results for each task of MT-Bench. It can be confirmed that the proposed TVKD framework records generally higher scores than existing methods. > < Visualization results of the Shaping term. The top tokens (converted into words) judged as important by the teacher model within the response are displayed in red, intuitively showing which tokens have a greater influence during the value-based alignment process. > Ph.D. candidate Minchan Kwon from our university’s School of Electrical Engineering participated as the first author, and the research results were accepted at ‘NeurIPS 2025’, the most prestigious international conference in the field of artificial intelligence. The research was presented at a poster session on December 3, 2025 (US Pacific Time). ※ Paper Title: Preference Distillation via Value based Reinforcement Learning, DOI: https://doi.org/10.48550/arXiv.2509.16965 Meanwhile, this research was carried out with support from the Information & Communications Technology Planning & Evaluation (IITP) funded by the government (Ministry of Science and ICT) in 2024 (No. RS-2024-00439020, Development of Sustainable Real-time Multimodal Interactive Generative AI, SW Star Lab).

< Group Photo of the Awards Ceremony > KAIST has announced that the awards ceremony for the ‘2025 Foreign Disinformation Response Idea Competition for University Students (Counter-Disinformation Challenge),’ organized by the Institute for Security Convergence in collaboration with the National Intelligence Service (NIS), is scheduled to be held on the afternoon of the 23rd at the KAIST Munji Campus. This competition, held for the second time since its inaugural launch last year, was established to inform the public about the current state of the creation and spread of foreign disinformation and its resulting social and national harms, as well as to seek future response measures. It solicited practical ideas covering both technology and policy from university students and the general public. Based on the awareness of the issues raised through last year’s competition, our university focused this year on strengthening the link between technology and policy and discovering ideas that can lead to actual research and development (R&D) and institutional improvements. Through this, the university plans to establish the foundation for a mid-to-long-term strategy for responding to foreign disinformation. The competition was held from November 1st to December 5th in two categories: ▲ Technical ideas to prevent the spread of foreign disinformation, and ▲ Policy proposals and institutional improvement ideas to solve foreign disinformation issues. A total of 144 teams, comprising 259 university and graduate students (including those on leave) from across the country, participated. Among them, 18 teams were selected as the final winners. This represents an improvement in both the scale of participation and the completeness of the proposals compared to last year, demonstrating the high level of interest among the youth in responding to foreign disinformation. The awards consist of: ▲ Technical Idea category: 1 Grand Prize, 3 First Prizes, 5 Excellence Prizes; ▲ Policy Proposal and Institutional Improvement category: 1 Grand Prize, 3 First Prizes, 5 Excellence Prizes. The Grand Prize (KAIST President's Award) in the ‘Technical Idea for Disinformation Response’ category will be awarded to Team ‘Lemming,’ composed of students Lee Jun, Kang Yun-ah, and Ma Seon-young from Jeju National University. Team Lemming proposed a technology that utilizes multi-persona AI agents to virtually simulate the creation, spread, and response processes of disinformation. Additionally, the Grand Prize (KAIST President's Award) in the ‘Policy Proposal and Institutional Improvement for Disinformation Response’ category will be awarded to Team ‘Kim Anbo Girls,’ composed of student Kim Yeon-jung from Jungwon University and student Kim Hyun-jin from Baekseok Arts University. Bae Joong-myeon, Director of the KAIST Institute for Security Convergence, stated, “Foreign disinformation is a future-type security threat where technology, policy, and society are complexly intertwined. We plan to link the students’ ideas to future R&D and policy reviews through collaboration with the National Intelligence Service and the Cyber Security Research Center of the KAIST Institute for Security Convergence.” Meanwhile, the National Intelligence Service, which sponsored this competition, has been accepting reports of foreign disinformation 24 hours a day, 365 days a year through the ‘111 Reporting Center’ and its official website since September 2024, and is promoting the strengthening of an integrated response system through cooperation with related organizations. < Event Poster >

< Hu-sik Kim, 28th President of KAIST Alumni Association (CEO of Vieworks) > KAIST announced on December 23rd that Hu-sik Kim, CEO of Vieworks—a company specializing in medical and industrial imaging solutions—has been appointed as the 28th President of the KAIST Alumni Association. President-elect Hu-sik Kim, an alumnus with a Master’s degree in Physics (Class of ’95) from KAIST, is a technology-driven leader who has dedicated 26 years to the field of imaging solutions. He is recognized as a "field-oriented innovator" who has pioneered global niche markets with world-first technologies and driven long-term growth by prioritizing people and organizational culture as core competencies. While working professionally, he enrolled in the KAIST Master’s program to strengthen his theoretical and practical expertise in optics. Later, he played a leading role in co-founding a venture company with fellow alumni, successfully growing Vieworks into a prominent global mid-sized enterprise. In his inauguration remarks, President Kim stated, “I feel a profound sense of responsibility to give back to the nation and the community for the benefits I have received. I will do my best to ensure that the values of innovation and entrepreneurship are realized through our alumni network, and that the alumni association and our alma mater can prosper together.” President Kim’s term will span two years starting from January 2026. The inauguration ceremony will be held during the "2026 New Year’s Greeting Ceremony" on January 16, 2026, at the El Tower in Seoul.

< KAIST Professor Insik Shin > KAIST announced on December 21st that Professor Insik Shin from the School of Computing has received the Influential Paper Award 2025 at the IEEE Real-Time Systems Symposium (RTSS), the world's most prestigious international conference in the field of real-time systems. This honor is a "Test of Time Award," presented to papers that have exerted a sustained and significant influence on both academia and industry for more than 10 years after publication. This marks the first time a Korean researcher has received this prestigious award. The ceremony took place at IEEE RTSS 2025 in Boston, USA, on December 4th (local time). Professor Shin’s award-winning research is the "Periodic Resource Model," co published in 2003 with Professor Insup Lee of the University of Pennsylvania. Rather than trying to verify a complex machine or system all at once, this study developed a method to verify individual components—much like LEGO blocks—to ensure each meets its designated timing requirements. It mathematically guarantees that when these components are assembled, the entire system will operate safely. Paper Title: Periodic Resource Model for Compositional Real-Time Guarantees DOI: 10.1109/REAL.2003.1253249 Thanks to this research, it has become possible to design real-time systems that cannot tolerate even a moment of delay—such as autonomous vehicles, aircraft, and industrial robots—with greater precision and safety. This breakthrough overcame the limitations of existing methods that required analyzing an entire system at once, which had become nearly impossible as the complexity of modern real-time systems increased rapidly. Professor Shin presented a method to divide a system into small modules, verify that each module satisfies its time constraints, and mathematically prove that the safety of the entire system is guaranteed upon integration. This work is credited with establishing the foundation for modern compositional real-time scheduling theory. At the time of its initial publication in 2003, this paper won the 'Best Paper Award' at RTSS—another first for a Korean researcher. Now, 20 years later, its academic and industrial value has been officially recognized once again. This is because the theory has transcended academic boundaries to become a core analytical tool in various safety-critical industries, including autonomous driving, aerospace control, and industrial automation. The IEEE Technical Committee stated, "This model has established itself as a core language for modern real-time system design and has guided the direction of research and industry for the past 20 years." The paper is currently featured in textbooks at major universities in the United States and Europe, serving as a standard theory in the field. "As a scholar, this is the award I have wanted most in my life," said Professor Shin. "I am honored to have it recognized that research from 20 years ago has truly had a major impact on the world. This was made possible by the many researchers and companies who applied this theory to actual systems." Meanwhile, Professor Shin is expanding his research beyond real-time systems into the field of Artificial Intelligence (AI). He founded the faculty-led startup Fluiz and developed FluidGPT, a mobile AI agent technology that allows users to execute smartphone apps via voice commands. This technology recently won the AI Champion Competition hosted by the Ministry of Science and ICT. Experts evaluate Professor Shin as achieving rare success by bridging basic theory and applied technology, effectively linking research to industry.

< 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 >  

< Professor Jaewook Myung of KAIST Department of Civil and Environmental Engineering > KAIST announced on December 12th that Professor Jaewook Myung of the Department of Civil and Environmental Engineering was selected as the first Korean recipient of the '40 Under 40 Recognition Program' for Next Generation Environmental Engineering Leaders, organized by the American Academy of Environmental Engineers and Scientists (AAEES). < The '40 Under 40 Recognition Program' is an international award program selecting next-generation leaders in the field of Environmental Engineering and Science > This award is presented annually by AAEES to select next-generation environmental engineering researchers who demonstrate innovative research achievements, social contribution, and educational leadership. Professor Myung's selection is particularly significant as he is the first Korean to be chosen since the program's inception. The award ceremony is scheduled to be held in Washington D.C. in April 2026. AAEES is the world's highest-authority professional organization leading the global environmental engineering sector through operating the Professional Environmental Engineer (PEE) certification system, policy consultation, and international academic exchange. This award is highly regarded for greatly enhancing the international standing of domestic environmental engineering and sustainability research. Amid the deepening problems of plastic waste increase and greenhouse gas emissions, where existing technologies are showing limitations in providing solutions, Professor Jaewook Myung has garnered significant attention from academia and industry by developing technology to convert greenhouse gases such as methane ($CH_4$) and carbon dioxide ($CO_2$) into biodegradable plastics. His research is highly praised for presenting a new industrial paradigm that fuses environmental microbiology and materials science to convert greenhouse gases into high-value bio-materials. Professor Myung's research team secured microbial metabolic control technology to transform greenhouse gases into materials, an accelerated process that simultaneously enhances the synthesis and decomposition efficiency of plastics, and pilot process design and engineering technology applicable in industrial settings. This established a sustainable circular technology model capable of simultaneously addressing greenhouse gas reduction and plastic pollution issues. Furthermore, the research team expanded these foundational technologies to develop various application products, such as biodegradable coating materials that naturally decompose in the ocean, biocompatible bio-based electronic materials, and industrial 3D printing filaments, realizing full-cycle innovation from basic research to application and industrialization. These achievements are recognized as world-class sustainable technology alternatives that can simultaneously overcome the problems of plastic downcycling and the economic limitations of greenhouse gas utilization technology. Professor Myung also shows excellent performance in nurturing talent. His advised students are growing into next-generation environmental and sustainability researchers, having won major awards both domestically and internationally, including the American Chemical Society (ACS) Environmental Chemistry Graduate Student Award, the Presidential Science Scholarship, the Merck Innovation Cup Prize, and the Republic of Korea Talent Award. He is also establishing himself as a leading researcher in the commercialization of sustainable technology by expanding his research achievements into the social and industrial ecosystem through technology collaboration with industries, patents, and consultation with public institutions. The AAEES Selection Committee evaluated Professor Jaewook Myung as "a researcher possessing technical excellence, social responsibility, and educational leadership, and an innovator who has pioneered new areas of environmental engineering." Professor Myung expressed his thoughts, saying, "This award is a result made possible by the students who researched and challenged alongside me and the collaborative research culture of KAIST," and added, "I will contribute to brightening the future of humanity and the planet through sustainable resource circulation technology."

From Ordering Goods to Booking Trains: An AI That Does Everything With Just a Word, Not a Touch / Prof. Insik Shin, Researcher Youngmin Im, Researcher Jaeyoung Wi

What If KAIST Students Try to Solve the 2026 CSAT Science Section?

From a duck walk to moonwalk, a humanoid with the strongest stability is coming / Professor Hae-Won Park from Mechanical Engineering