Kaist

Breakthrough in Intractable Intestinal Disease Tre..

  < (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.    

KAIST, AI judges manufacturing beyond craftsmanshi..

  <(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.  

Where did this fish come from？ Securing World-Clas..

  < (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 >    

AI Gets a Private Tutor, Learning Human Preference..

  < 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).  

Harry Potter–Style ‘Moving Invisibility Cloak’ Tec..

  <(Top row, left) Ph.D candidate Hyeonseung Lee, Professor Wonho Choe, (Second row, left) Professor Hyoungsoo Kim, Professor Sanghoo Park,(Top) First author Dr. Jeongsu Pyeon>     What do Harry Potter’s invisibility cloak and stealth fighter jets that evade radar have in common? They both make objects invisible despite their physical presence. Building upon this concept, our research team has taken it one step further by developing a “smart invisibility cloak” like technology that hides electromagnetic waves even better as it stretches and moves. This technology is expected to open new possibilities for moving robots, body-mounted wearable devices, and next-generation stealth technologies. On December 16th, research teams led by Professor Hyoungsoo Kim of the Department of Mechanical Engineering and Professor Sanghoo Park of the Department of Nuclear and Quantum Engineering from KAIST announced that they have developed a core enabling technology for next-generation stretchable cloaking＊ based on Liquid Metal Composite Ink (LMCP), which can absorb, modulate, and shield electromagnetic waves. ＊ Cloaking: A technology that makes an object appear as if it does not exist to detection equipment such as radar or sensors, even though it is physically present. To realize cloaking technology, it is necessary to freely control light or electromagnetic waves on the surface of an object. However, conventional metallic materials are rigid and do not stretch well, and when forcibly stretched, they easily break. For this reason, there have been significant difficulties in applying such materials to body-conforming electronic devices or robots that freely change shape. The liquid metal composite ink developed by the research team maintains electrical conductivity even when stretched up to 12 times its original length (1200％), and it demonstrated high stability with little oxidation or performance degradation even after being left in air for nearly a year. Unlike conventional metals, this ink is rubber-like and soft while fully retaining metallic functionality. These properties are possible because, during the drying process, liquid metal particles inside the ink spontaneously connect with one another to form a mesh-like metallic network structure. This structure functions as a “metamaterial”—an artificial structure in which extremely small patterns are repeatedly printed using ink so that electromagnetic waves interact with the structure in a designed manner. As a result, the material simultaneously exhibits liquid-like flexibility and metal-like robustness. The fabrication process is also simple. Without complex procedures such as high-temperature sintering or laser processing, the ink can be printed using a printer or applied with a brush and then simply dried. In addition, common drying issues such as stains or cracking do not occur, enabling smooth and uniform metal patterns. To verify the performance of the ink, the research team became the first in the world to fabricate a “stretchable metamaterial absorber” whose electromagnetic wave absorption characteristics change depending on the degree of stretching. Simply stretching the rubber-like substrate after printing patterns with the ink changes the type (frequency band) of electromagnetic waves that are absorbed. This demonstrates the potential for cloaking technology that can more effectively hide objects from radar or communication signals depending on the situation. <Figure. Comparison of LMCP ink properties, printing process applicability, mechanical/electrical performance, and versatility on various substrates. (a) Comparison results regarding surface tension, viscosity, wettability, and post-processing requirements between conventional liquid metal-based inks and the LMCP ink in this study. The results demonstrate that LMCP ink possesses the advantage of requiring no post-processing while maintaining relatively high viscosity and excellent wettability. (Right radar chart: Qualitative comparison of key performance indicators, including electrical conductivity, surface tension, viscosity, wettability, and post-processing requirements). (b) Various printing methods based on the self-sintering characteristics of LMCP ink: nozzle-based direct writing, brushing, patterning using shadow masks and doctor blade processes, and large-area electrode fabrication via the roll-to-roll method. (c) Stretchability and electrical stability of LMCP electrodes. Results show resistance changes when samples are stretched from 0％ to 1200％, and stable operation is confirmed under 0％–500％ strain through a 3 V LED driving experiment. (d) Examples of various patterns and devices fabricated using LMCP ink. Applicable structures are presented, including large-area uniform coating, precise grid patterns, crack-free metal paths, LED circuits operating under tension, and stretchable spiral electrodes>   (e) Examples demonstrating stable printing of LMCP ink on various substrates (SIR, NBR, PVC, PET, WPU, PDMS, Latex), indicating excellent pattern reproducibility and adhesion regardless of the substrate type>   This technology is evaluated as a groundbreaking electronic material technology that simultaneously satisfies stretchability, electrical conductivity, long-term stability, process simplicity, and electromagnetic wave control functionality. Professor Hyoungsoo Kim stated, “We have made it possible to implement electromagnetic wave functionality using only printing processes without complex equipment,” adding, “This technology is expected to be utilized in various future technologies such as robotic skin, body-mounted wearable devices, and radar stealth technologies in the defense sector.” This research was recognized as an important fundamental technology in the field of next-generation electronic materials and was published in the October 2025 issue of the international Wiley journal Small on October 16, where it was selected as a cover article. Paper title: J. Pyeon, H. Lee, W. Choe, S. Park, H. Kim, “Versatile Liquid Metal Composite Inks for Printable, Durable, and Ultra-Stretchable Electronics,” Small 2501829 (2025) DOI: https://doi.org/10.1002/smll.202501829 Author information: First author: Dr. Jeongsu Pyeon Co-authors: Doctoral candidate Hyeonseung Lee, Professor Wonho Choe Corresponding authors: Professor Hyoungsoo Kim, Professor Sanghoo Park This work was supported by the National Research Foundation of Korea’s Mid-Career Research Program (MSIT: 2021R1A2C2007835) and the KAIST UP Program.   < Selected as the cover article of the October 2025 issue of the international journal Small > < Invisibility cloak technology image (AI-generated image) >

Jaewook Myung, First Korean Selected as ＇40 Under ..

  < 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."      

Octopus-Inspired 3D Micro-LEDs Pave the Way for Se..

  <(From Left) Professor Keon Jae Lee, Professor Tae-Hyuk Kwon, Ph.D candidate Min Seo Kim, Dr. Jae Hee Lee, Dr. Chae Gyu Lee>   -KAIST and UNIST Researchers Develop Shape-Morphing Device to Overcome Pancreatic Tumor Microenvironment Barriers   Conventional pancreatic cancer treatments face a critical hurdle due to the dense tumor microenvironment (TME). This biological barrier surrounds the tumor, severely limiting the infiltration of chemotherapy agents and immune cells. While photodynamic therapy (PDT) offers a promising alternative, existing external light sources, such as lasers, fail to penetrate deep tissues effectively and pose risks of thermal damage and inflammation to healthy organs   To address these challenges, Professor Keon Jae Lee’s team at KAIST, in collaboration with Professor Tae-Hyuk Kwon at UNIST, developed an implantable, shape-morphing 3D micro-LED device capable of effectively delivering light to deep tissues. The key technology lies in the device’s flexible, octopus-like architecture, which allows it to wrap around the entire pancreatic tumor. This mechanical compliance ensures uniform light delivery to the tumor despite the tumor’s physiological expansion or contraction, enabling continuous, low intensity photostimulation that precisely targets cancer cells while preserving normal tissue.   In in-vivo experiments involving mouse models, the device demonstrated remarkable therapeutic efficacy. Within just three days, tumor fibrous tissue was reduced by 64％, and the pancreatic tissue successfully reverted to normal tissue, overcoming the limitations of conventional PDT.   Prof. Keon Jae Lee said, "This research presents a new therapeutic paradigm by directly disrupting the tumor microenvironment, the primary obstacle in pancreatic cancer treatment." He added, "We aim to expand this technology into a smart platform integrated with artificial intelligence (AI) for real-time tumor monitoring and personalized treatment. We are currently seeking partners to advance clinical trials and commercialization for human application."   <Overall concept of 3D Shape-morphing micro-LEDs (SMLEDs). The 3D long-term, low-intensity photodynamic therapy (PDT) system attaches to the pancreatic surface, ensuring stable and continuous light delivery. Initially maintaining a 2D structure, the system morphs into a 3D structure upon implantation to conform to the shape of the pancreas. In in vivo experiments, the device maintained stable adhesion without detachment for four weeks and reduced the pancreatic tumor size by 64％.> Professor Tae-Hyuk Kwon commented, "While phototherapy is effective for selective cancer treatment, conventional technologies have been limited by the challenges of delivering light to deep tissues and developing suitable photosensitizers." He added, "Building on this breakthrough, we aim to expand effective immune-based therapeutic strategies for targeting intractable cancers."   <Cover Image. The 3D long-term, low-intensity photodynamic therapy (PDT) system, developed by Professor Keon Jae Lee's team at the Department of Materials Science and Engineering at KAIST, was featured as the cover article of the international journal Advanced Materials> The result, titled "Deeply Implantable, Shape-Morphing, 3D MicroLEDs for Pancreatic Cancer Therapy," was featured as the cover article in Advanced Materials (Volume 37) on December 10, 2025.        

Robot Valley Project Activation of the Korean styl..

  < 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.

KAIST Predicts Human Group Behavior with AI！ 1st P..

  <(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).      

Four KAIST Scholars Named to the 2025 Highly Cited..

Four members of KAIST including Distinguished Professor Sang Yup LEE, have been selected for the '2025 Highly Cited Researchers (HCR)' list announced by Clarivate Plc, a global academic information analysis company in the United States. HCR is a program that identifies researchers who show top 1％ influence in their respective fields based on the citation frequency of papers included in Web of Science, and it is utilized as an important indicator in the evaluation of world universities and research institutions. Clarivate announced the final list this year after verifying the excellence of research performance and academic influence through rigorous qualitative and quantitative reviews. This year, the following professors from KAIST were selected: Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering and Professor Jin-Soo Kim＊ from the Graduate School of Engineering Biology in the field of Biology and Biochemistry; and Professor Bumjoon Kim and Professor Jangwon Seo from the Department of Chemical and Biomolecular Engineering in the Cross-Field category. ＊ Professor Jin-Soo Kim is currently listed under Edgene on the HCR list, and the affiliation is scheduled to be updated to KAIST at the end of December. < KAIST Faculty List Selected as HCR (The total number of selected researchers is 6,868, but the total number of entries by field is 7,131, as the same researchers were selected simultaneously in multiple Cross-Field categories.) > The Cross-Field category was established to recognize researchers who have demonstrated influence across multiple fields, going beyond a single academic area. Its importance is growing with the spread of convergence research, and it is evaluated as an indicator showing that a researcher has diverse academic impact. This year, a total of 6,868 researchers from over 1,300 institutions in 60 countries worldwide were named HCR, and a total of 76 researchers from 12 fields were selected in South Korea. While several institutions in South Korea produced HCRs, KAIST produced its HCR selectees based on globally recognized research achievements in the fields of Bioengineering, Biotechnology, and Convergence.

KAIST Removes 99.9％ of Ultrafine Dust Using Nano W..

  <(From Left) Ph.D candidate Sungyoon Woo, Professor Il-Doo Kim, Professor Seung S.Lee, Ph.D candiate Jihwan Chae, Researcher Jiyeon Yu, (Upper Right) Dr. Yujang Cho>   A KAIST research team has drawn attention by developing a new water-based air purification technology that combines “nano water droplets that capture dust” with a “nano sponge structure that autonomously draws up water,” enabling dust removal using nano water droplets without filters, self-supplied water operation, and long-term, quiet, and safe performance.   KAIST (President Kwang Hyung Lee) announced on the December 8 that a joint research team led by Professor Il-Doo Kim of the Department of Materials Science and Engineering and Professor Seung S. Lee of the Department of Mechanical Engineering developed a new water electrospray–based air purification device that rapidly removes ultrafine dust without filters, generates no ozone, and operates with ultra-low power consumption.   The research team confirmed that this device overcomes the limitations of conventional air purifiers by eliminating the need for filter replacement, producing no ozone, and removing even extremely fine ultrafine dust as small as PM0.3 (diameter 0.3 μm), which is about 1/200 the thickness of a human hair, within a short time. In addition, it demonstrated high stability and durability without performance degradation even during long-term use.   This device was created by combining Professor Seung S. Lee’s “ozone-free water electrospray” technology with Professor Il-Doo Kim’s “hygroscopic nanofiber Emitter” technology.   Inside the device are a high-voltage electrode, a nanofiber absorber that autonomously draws up water, and polymer microchannels that transport water via capillary action. Thanks to this structure, a self-pumped configuration is achieved in which water is automatically supplied without a pump, enabling stable long-term water electrospray operation.   Tests conducted by the research team in a 0.1 m3 experimental chamber showed that the device removed 99.9％ of various particles in the PM0.3–PM10 range within 20 minutes. In particular, it exhibited outstanding performance by removing 97％ of PM0.3 ultrafine dust, which is difficult to eliminate using conventional filter-based air purifiers, within just 5 minutes.   Even after 30 consecutive tests and 50 hours of continuous operation, the device operated stably without performance degradation, and its power consumption was approximately 1.3 W, which is lower than that of a smartphone charger and only about 1/20 that of conventional HEPA (High Efficiency Particulate Air) filter–based air purifiers.   In addition, because there is no filter, there is no pressure loss in airflow and almost no noise is generated.   This technology maintains high-efficiency purification performance while generating no ozone at all, presenting the potential for a next-generation eco-friendly air purification platform.   In particular, with advantages such as elimination of filter replacement costs, ultra-low power operation, and secured long-term stability, it is expected to expand into various fields including indoor environments as well as automotive, cleanroom, portable, and wearable air purification modules.   Commercialization of this technology is currently underway through A2US Co., Ltd., a university spin-off company from Professor Seung S. Lee’s laboratory.   A2US Co., Ltd. won a CES 2025 Innovation Award and plans to launch a portable air purifier product in 2026. The product is equipped not only with fine dust removal using nano water droplets but also with odor removal and pathogen sterilization functions.     <Figure1.Design and Operating Mechanism of a Miniature Air-Purification Device Based on Cone-Jet Water Electrospray Using a Self-Pumping Hygroscopic (PVA–PAA–MMT) Nanofiber Membrane (PPM-NFM) Emitter.>     <Figure 2. (a) Schematic of the Self-Pumping Hygroscopic Nanofiber Membrane (PPM-NFM) Emitter, and (b) Corresponding Photograph and Surface Scanning Microscopy Images.>          

KAIST, Production Temperature ↓ by 500°C, Power Ou..

  <(Top row, from left) Professor Kang Taek Lee, Ph.D candidate Yejin Kang, Dr. Dongyeon Kim, (Bottom row, from left) M.S candidate Mincheol Lee, Ph.D candidate Seeun Oh, Ph.D candidate Seungsoo Jang, Ph.D candidate Hyeonggeun Kim>     As power demand surges in the AI era, the “protonic ceramic electrochemical cell (PCEC),” which can simultaneously produce electricity and hydrogen, is gaining attention as a next-generation energy technology. However, this cell has faced the technical limitation of requiring an ultra-high production temperature of 1,500°C. A KAIST research team has succeeded in establishing a new manufacturing process that lowers this limit by more than 500°C for the first time in the world. KAIST (President Kwang Hyung Lee) announced on the 4th of December that Professor Kang Taek Lee’s research team in the Department of Mechanical Engineering developed a new process that enables the fabrication of high-performance protonic ceramic electrochemical cells at temperatures more than 500°C lower than before, using “microwave ＋ vapor control technology” that leverages microwave heating principles and the diffusion environment of chemical vapor generated from specific chemical components. The electrolyte—the key material of protonic ceramic electrochemical cells—contains barium (Ba), and barium easily evaporates at temperatures above 1,500°C, which has been the main cause of performance degradation. Therefore, the ability to harden the ceramic electrolyte at a lower temperature has been the core issue that determines cell performance. As power demand surges in the AI era, the “protonic ceramic electrochemical cell (PCEC),” which can simultaneously produce electricity and hydrogen, is gaining attention as a next-generation energy technology. However, this cell has faced the technical limitation of requiring an ultra-high production temperature of 1,500°C. A KAIST research team has succeeded in establishing a new manufacturing process that lowers this limit by more than 500°C for the first time in the world. KAIST (President Kwang Hyung Lee) announced on the 4th of December that Professor Kang Taek Lee’s research team in the Department of Mechanical Engineering developed a new process that enables the fabrication of high-performance protonic ceramic electrochemical cells at temperatures more than 500°C lower than before, using “microwave ＋ vapor control technology” that leverages microwave heating principles and the diffusion environment of chemical vapor generated from specific chemical components. The electrolyte—the key material of protonic ceramic electrochemical cells—contains barium (Ba), and barium easily evaporates at temperatures above 1,500°C, which has been the main cause of performance degradation. Therefore, the ability to harden the ceramic electrolyte at a lower temperature has been the core issue that determines cell performance. To solve this, the research team devised a new heat-treatment method called “vapor-phase diffusion.” This technique places a special auxiliary material (a vapor source) next to the cell and irradiates it with microwaves to quickly diffuse vapor. When the temperature reaches approximately 800°C, the vapor released from the auxiliary material moves toward the electrolyte and tightly bonds the ceramic particles. Thanks to this technology, a process that previously required 1,500°C can now be completed at just 980°C. In other words, a world-first ceramic electrochemical cell fabrication technology has been created that produces high-performance electricity at a “low temperature” without damaging the electrolyte. A cell fabricated with this process produced 2 W of power stably from a 1 cm² cell (roughly the size of a fingernail) at 600°C and generated 205 mL of hydrogen per hour at 600°C (about the volume of a small paper cup, among the highest in the industry). It also maintained stability without performance degradation during 500 hours of continuous operation. In other words, this technology reduces the production temperature (−500°C), lowers the operating temperature (600°C), doubles performance (2 W/cm²), and extends the lifespan (500-hour stability), achieving world-class performance in ceramic cell technology. The research team also enhanced the reliability of the technology by using digital twins (virtual simulations) to analyze gas-transport phenomena occurring in the microscopic internal structure of the cell − phenomena that are difficult to observe in actual experiments. <Figure 1. (a) Schematic of the vapor-diffusion-based process; (b) Surface microstructure of the electrolyte; (c) Internal barium composition ratio of the electrolyte according to processing conditions; (d) Comparison of power-generation performance with previous studies> < Figure 2. (a) Three-dimensional reconstructed image of the protonic ceramic electrochemical cell fuel electrode according to processing conditions (b) Pore structure (c) Gas-transport simulation results > Professor Kang Taek Lee emphasized, “This study is the world’s first case of using vapor to lower the heat-treatment temperature by more than 500°C while still producing a high-performance, high-stability cell.” He added, “It is expected to become a key manufacturing technology that addresses the power challenges of the AI era and accelerates the hydrogen society.” Dongyeon Kim (KAIST PhD) and Yejin Kang (KAIST PhD candidate) participated as co–first authors. The research results were published in Advanced Materials (IF: 26.8), one of the world’s leading journals in energy and materials science, and were selected as the Inside Front Cover article on October 29.  (Paper title: “Sub-1000°C Sintering of Protonic Ceramic Electrochemical Cells via Microwave-Driven Vapor Phase Diffusion,” DOI: https://doi.org/10.1002/adma.202506905) This research was supported by the MSIT’s Mid-career Researcher Program and the H2 Next Round Program.