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AI, Humanoid Robots, and Space Rovers to Gather: Experience Future Technologies at the Science Festival
<(From left) Photos of the KAIST Science Festival exhibition hall and booths from the previous year>
KAIST announced on April 10th that KAIST will participate in the ‘2026 Korea Science and Technology Festival,’ the largest science festival in the country, to mark Science Month in April. KAIST will operate ‘KAIST Play World,’ an interactive exhibition hall showcasing the pinnacle of AI and robotics. This year’s festival will be held in two parts: ‘2026 Korea Science Festival in Daejeon (April 17–19)’ and ‘2026 Korea Science Festival in Gyeonggi (April 24–26).’ KAIST will host consecutive exhibitions at the Daejeon DCC (Second Exhibition Hall) and KINTEX in Ilsan. Under the ‘Play World’ concept, KAIST plans to offer differentiated interactive content tailored to various generations. In particular, on-site events and souvenirs featuring the KAIST character ‘Nupjuk-i’ will be provided to enhance visitor engagement.
□ [Daejeon] From Humanoid Robots to Space Rovers and AI Semiconductor Friend ‘BROCA’ The exhibition at Daejeon DCC from April 17 to 19 will feature ‘Future Tech Experience Content’ centered on advanced robotics, space technology, and AI semiconductor technology, allowing visitors to experience KAIST's core research achievements firsthand. First, a humanoid robot equipped with control technology developed by Eurobotics Co., Ltd., a startup from Professor Myung Hyun’s research team in the School of Electrical Engineering, will be unveiled on the 17th. This robot is gaining attention as a next-generation platform capable of natural walking in both industrial and urban environments. Additionally, on the 19th, a humanoid robot from Professor Park Hae-won’s team in the Department of Mechanical Engineering will demonstrate high-difficulty human movements such as the duck walk and moonwalk, showcasing its potential for practical industrial use. Professor Lee Dae-young’s team in the Department of Aerospace Engineering will present the world’s first deployable lunar rover wheel based on origami technology. Visitors can touch the transformable wheel model and observe space rover demonstrations and displays by the co-developer, Unmanned Exploration Laboratory (UEL). Educational sessions for folding various space systems using origami will also be available. Along with this, visitors can experience advanced human-machine interaction through ‘BROCA,’ a mobile social AI agent that builds relationships with users beyond simple Q&A, and the voice-capable guide robot ‘On-Newro,’ developed by Professor Yoo Hoi-jun’s team at the AI Semiconductor Graduate School. The student startup ‘Liar Games’ will operate a trial zone for ‘Dual Focus,’ an abstract strategy board game where players compete 1:1 against AI. Similar to the deep strategic play of chess or Go, the rules are intuitive enough to learn in 5 minutes, which is expected to stimulate the challenge-seeking spirit of visitors.
< (Top row from left) Professor Park Hae-won’s humanoid robot, Professor Yoo Hoi-jun’s BROCA, (Bottom row from left) Eurobotics’ humanoid walking technology capable of overcoming any terrain based on a mobile kit, Professor Lee Dae-young’s storable and deployable rover for lunar exploration >
□ [Gyeonggi] ‘Raibo’ the Rough-Terrain Robot and AI-Based Future Experiences The Gyeonggi exhibition at KINTEX from April 24 to 26 will focus on ‘Life-Oriented Experience Content’ centered on AI and everyday technology. ‘Raibo,’ a quadrupedal robot developed by Professor Hwangbo Jemin’s team in the Department of Mechanical Engineering, is capable of high-speed movement on complex terrains such as sand, stairs, and debris, and is expected to be utilized for disaster relief and search missions. Visitors can experience Raibo’s driving technology directly at the site. The ‘Future Memories Studio’ from Professor Nam Tek-jin’s team in the Department of Industrial Design will provide a new experience where visitors can meet and talk to their future selves 10 years later, recreated using AI-generated visuals and voices. Participants will receive a four-cut photo capturing a moment that is the future for their current self but a memory for their future self. Professor Yun Yun-jin’s team at the KAIST Urban AI Research Center will present technology that analyzes the impact of climate change on small business sales through ‘AI-based Sight and Sound for Heatwave Consumption Index.’ They will showcase time-series AI-based sales prediction technology and generative AI technology that expresses this visually and audibly. Furthermore, Professor Yun’s lecture, “City Walk of Artificial Intelligence: Urban AI and the Future of Cities,” will be held on April 24 (Fri) at 15:00 in KINTEX Meeting Room 206. In addition, Professor Yoo Hoi-jun’s team from the AI Semiconductor Graduate School will continue from the Daejeon exhibition to operate an experience zone for various mobile AI agents based on AI semiconductors. Also, the student startup Rabbithole Company will introduce a new type of game where AI NPCs (Non-Player Characters) converse and cooperate to solve given problems. Visitors can participate by observing the process where AI characters create their own stories by being presented with situations or goals instead of being directly controlled.
< (Top row from left) Professor Hwangbo Jemin’s Raibo, Professor Nam Tek-jin’s team: Met My Future Self 10 Years Later, (Bottom row from left) Professor Yun Yun-jin’s Seeing and Hearing Heatwave Consumption Index through AI, Game image from CEO Kim Na-hoon’s Rabbithole Company >
Through the exhibitions in both regions, KAIST plans to operate various participatory programs to make science and technology easy and fun to approach, vividly conveying how technology from the laboratory transforms our lives. KAIST President Lee Kwang-hyung remarked, “This year’s science festival is a large-scale event connecting Daejeon and Gyeonggi, allowing more citizens to experience KAIST’s innovative research achievements firsthand.” He added, “I hope this will be a precious time for people to experience the future created by robots and AI, fostering their dreams and curiosity about science.”
2026.04.13 View 66 -
InnoCORE Research Group Successfully Achieves AI Protein Design with Nobel Laureate David Baker
< (From left) Professor Gyu Rie Lee, Professor David Baker >
Under the foundation of research cooperation established through the Ministry of Science and ICT's InnoCORE (InnoCORE) project, KAIST InnoCORE researchers have derived meaningful research results. Following a visit by Professor David Baker (University of Washington, USA), the 2024 Nobel Laureate in Chemistry, KAIST has revealed research findings on designing proteins that accurately recognize desired compounds using AI through joint research.
KAIST announced on April 9th that Professor Gyu Rie Lee of the Department of Biological Sciences—a researcher participating in the AI-CRED Innovative Drug InnoCORE Research Group—successfully designed artificial proteins that selectively recognize specific compounds using AI through joint research with Professor David Baker.
This research is characterized by using AI to design proteins that recognize specific compounds from scratch (de novo) and implementing them as functional biosensors. While the conventional approach mainly involved searching natural proteins or modifying some of their functions, this research is highly significant in that it ‘custom-built’ proteins with desired functions through AI-based design and even completed experimental verification.
In particular, the research team successfully designed a protein that selectively recognizes the stress hormone cortisol and implemented an AI-designed biosensor based on it. This is evaluated as a case that extends beyond protein design to actual measurable sensor technology, solving the long-standing challenge of small-molecule recognition in the field of protein design.
These research results are expected to be utilized in various fields such as disease diagnosis, new drug development, and environmental monitoring in the future. It can precisely detect biomarkers in the blood to diagnose diseases early and contribute to the development of targeted therapies through the design of proteins that selectively recognize specific molecules. Furthermore, it is expected that the implementation of customized biosensor technology will become possible, such as real-time monitoring of air and water quality through the development of sensors that detect environmental pollutants.
Designing new proteins (de novo proteins) that recognize compounds has been considered a challenge in the field of protein design for a long time because it requires precise calculations at the atomic level. The research team developed an AI model that precisely reflects protein-ligand interactions and successfully designed binding proteins using it.
As a result, artificial binding proteins were designed for six types of compounds, including metabolites and small-molecule drugs, and their functions were verified through experiments. In particular, a cortisol biosensor was developed by designing a chemical-induced dimer based on a new protein that binds with cortisol. A provisional patent for the relevant design technology has been filed in the United States.
Professor Gyu Rie Lee stated, “This research experimentally proves that AI can be used to design proteins that precisely recognize specific compounds,” and added, “We plan to expand this into protein design technology that can be utilized in various fields such as disease diagnosis, new drug development, and environmental monitoring in the future.”
Professor Gyu Rie Lee of the KAIST Department of Biological Sciences participated in this research as the first author, and Professor David Baker as the corresponding author. The study was published in the international academic journal Nature Communications on March 28, 2026. ※ Paper Title: Small-molecule binding and sensing with a designed protein family DOI: https://doi.org/10.1038/s41467-026-70953-8 Authors: Gyu Rie Lee, Samuel J. Pellock, Christoffer Norn, Doug Tischer, Justas Dauparas, Ivan Anishchenko, Jaron A. M. Mercer, Alex Kang, Asim K. Bera, Hannah Nguyen, Evans Brackenbrough, Banumathi Sankaran, Inna Goreshnik, Dionne Vafeados, Nicole Roullier, Hannah L. Han, Brian Coventry, Hugh K. Haddox, David R. Liu, Andy Hsien-Wei Yeh & David Baker
< Image of Research Content Summary >
Professor Gyu Rie Lee is a new professor who joined KAIST in February 2025 and leads the Protein Design Laboratory. She possesses world-class expertise in the field of precise protein complex design at the atomic level and is performing various research projects such as AI-based protein design, artificial enzyme design, and RNA-recognizing protein development. She is also participating as a mentor professor in the AI-CRED Innovative Drug Research Group of the InnoCORE project, conducting research on enzyme and peptide drug design.
Professor Lee conducted research as a postdoctoral researcher and Staff Scientist in Professor David Baker’s laboratory (University of Washington, USA, Howard Hughes Medical Institute) from 2018 to 2024. Professor David Baker is a world-renowned scholar in the field of protein structure prediction and design and was awarded the Nobel Prize in Chemistry in 2024.
Director Do-Heon Lee, a mentor professor of the AI-CRED Innovative Drug Research Group, stated, “This achievement is a meaningful result derived through cooperation between InnoCORE researchers and a global scholar,” and added, “We will further strengthen our research capabilities based on active research collaboration with postdoctoral researchers recruited through the InnoCORE project to continue creating innovative results in the AI drug development and bio-fields.”
Meanwhile, KAIST will host a lecture on Thursday, April 9th at 4 PM in the KI Building Fusion Hall featuring Professor David Baker and Professor Hannele Ruohola-Baker (University of Washington, USA) under the theme of ‘Advances in AI-powered protein design and biomedical science’ to mark Professor David Baker’s visit to Korea. This event is held with the support of the KAIST International Scholar Invitation Program, KAI-X, the InnoCORE AI-CRED Innovative Drug Group, and the Ministry of Science and ICT’s Overseas Excellent Research Institute Cooperation Hub Construction Project.
< Poster for Professor David Baker’s Invited Lecture >
KAIST President Kwang Hyung Lee stated, “Through cooperation with Nobel Laureate Professor David Baker, we have derived a meaningful achievement in AI-based protein design,” and added, “This research is an example showing that KAIST is leading innovative research alongside world-class research institutions.”
Meanwhile, the KAIST InnoCORE Research Group aims to accelerate AI-based scientific and technological innovation and promote global joint research by supporting top-tier domestic and international postdoctoral researchers to devote themselves to the development of AI convergence technology in a cutting-edge collective research environment. As the lead institution, KAIST operates the ▲Hyper-scale Large Language Model Innovation Research Group ▲AI-based Intelligent Design-Manufacturing Integration Research Group ▲AI-CRED Innovative Drug Research Group and ▲AI-Transformed Aerospace Research Group.
2026.04.09 View 291 -
KAIST Develops Electrode Technology Achieving 86% Efficiency for Converting CO₂ into Plastic Precursors
<(From Left) Dr. Jonghyeok Park, Ph.D candidate Yunkyoung Han, Professor Hyunjoon Song, Dr. Sungjoo Kim>
KAIST Develops Electrode Technology Achieving 86% Efficiency for Converting CO₂ into Plastic Precursors
In the process of converting carbon dioxide into useful chemicals such as ethylene—a key precursor for plastics—a major challenge has been the flooding of electrodes, where electrolyte penetrates the electrode structure and reduces performance. KAIST researchers have developed a new electrode design that blocks water while maintaining efficient electrical conduction and catalytic reactions, thereby improving both efficiency and stability.
KAIST (President Kwang Hyung Lee) announced on the 6th of April that a research team led by Professor Hyunjoon Song from the Department of Chemistry has developed a novel electrode structure utilizing silver nanowire networks—ultrafine silver wires arranged like a spiderweb—to significantly enhance the efficiency of electrochemical CO₂ conversion to useful chemical products.
In electrochemical CO₂ conversion processes, a long-standing issue has been flooding, where the electrode becomes saturated with electrolyte, reducing the space available for CO₂ to react. While hydrophobic materials can prevent water intrusion, they typically suffer from low electrical conductivity, requiring additional components and complicating the system.
To overcome this, the research team designed a three-layer electrode architecture that simultaneously repels water and enables efficient charge transport. The structure consists of a hydrophobic substrate, a catalyst layer, and an overlaid silver nanowire (Ag NW) network, which acts as an efficient current collector while preventing electrolyte flooding.
< Schematic diagram of a porous polymer–copper oxide catalyst silver nanowire network electrode structure >
A key finding of this study is that the silver nanowires do more than just conduct electricity—they actively participate in the chemical reaction. During CO₂ reduction, the silver nanowires generate carbon monoxide (CO), which is then transferred to adjacent copper-based catalysts, where further reactions occur. This creates a tandem catalytic system, in which two catalysts cooperate sequentially, significantly enhancing the production of multi-carbon compounds such as ethylene.
The electrode demonstrated outstanding performance. It achieved 79% selectivity toward C₂₊ products in alkaline electrolytes and 86% selectivity in neutral electrolytes, representing a world-leading level. It also maintained stable operation for more than 50 hours without performance degradation. These results indicate that most of the converted products are the desired chemicals, while also overcoming the durability limitations of conventional systems.
< Conceptual diagram of a CO₂ electrolysis electrode utilizing a stacked silver nanowire structure (AI-generated image) >
Professor Hyunjoon Song stated, “This study is significant in showing that silver nanowires not only serve as electrical conductors but also directly participate in chemical reactions,” adding, “This approach provides a new design strategy that can be extended to converting CO₂ into a wide range of valuable products such as ethanol and fuels.”
This research, led by Jonghyeok Park (KAIST, first author), was published on March 24, 2026, in the international journal Advanced Science.
※ Paper title: “Overlaid Conductive Silver Nanowire Networks on Gas Diffusion Electrodes for High-Performance Electrochemical CO₂-to-C₂₊ Conversion,” DOI: https://doi.org/10.1002/advs.75003
2026.04.07 View 281 -
Undergraduate Rover Team (MR2) Advances to Finals of 'URC 2026', the World’s Largest Mars Rover Competition
<Photo: KAIST Undergraduate Club MR2 Team Members>
Undergraduate students from KAIST are set to take on the world stage with an exploration rover—a robotic vehicle designed to explore in place of humans—that they built themselves. The team has secured a spot in the finals of the world’s largest Mars rover competition, marking a first-ever achievement for KAIST.
KAIST announced on the 3rd that 'MR2' (Advised by Professor Yong-Hwa Park, Department of Mechanical Engineering), a rover team from the undergraduate robotics club MR (Microrobot Research), has earned a seed in the finals of the '2026 University Rover Challenge (URC)', the premier international Mars rover competition for university students.
The URC is organized by The Mars Society and takes place at the Mars Desert Research Station (MDRS) in Utah, USA, an environment that closely mimics the Martian surface. Participating teams compete in four key missions using rovers they developed: ▲Science Mission, ▲Delivery Mission, ▲Equipment Servicing Mission, and ▲Autonomous Navigation Mission.
This year’s competition saw 116 university teams from 18 countries engage in a fierce preliminary round. Team MR2 secured its place in the top 38 finalists by scoring 95.38 out of 100. This milestone is particularly significant as it is the first time a KAIST team has ever reached the URC finals, proving the excellence of KAIST undergraduates in robot design and control on a global scale.
The next-generation exploration rover 'GAP-1000', independently developed by MR2, is a modular rover designed for stable operation in extreme environments. It features a 6-DOF (Degrees of Freedom) robotic arm capable of precisely controlling objects over 5kg, allowing it to perform complex equipment manipulation tasks.
<Photo: Operation of GAP-1000's Manipulator and Science Module Integration>
The rover also boasts strong autonomous driving capabilities. By combining RTK-GNSS (precision satellite positioning), IMU (Inertial Measurement Units) for motion sensing, and odometry based on wheel rotation, it can autonomously navigate optimal paths through complex terrain. Additionally, a drone relay system has been integrated to ensure stable exploration even in areas with communication dead zones.
For the science mission, the rover can collect soil from 10cm underground, remove impurities via centrifugation, and analyze traces of life using protein detection reagents such as Biuret and Bradford. This is paired with spectroscopic analysis technology that identifies material composition by analyzing light wavelengths, creating an integrated system for real-time life detection.
"We experienced a lot of trial and error while managing everything from design to production ourselves, but I am thrilled that we achieved KAIST’s first-ever advancement to the finals," said Myung-woo Jung (Department of Mechanical Engineering), the team leader of MR2. "We will prepare thoroughly in the remaining time to achieve a great result on-site."
<Photo: Scenery of MDRS in Utah, USA, where the competition will be held (Photo Credit: The Mars Society)>
Advising Professor Yong-Hwa Park noted, "It is impressive that the students independently implemented a rover for extreme environments. This competition will serve as an opportunity to showcase KAIST’s technological prowess to the world."
KAIST President Kwang-Hyung Lee added, "It is a very meaningful achievement for our undergraduates to reach the finals of the world’s largest competition with a rover they designed and built themselves. I hope this experience serves as a catalyst for our students to challenge themselves and grow on the global stage."
Team MR2 consists of 13 undergraduate students from various majors, including Mechanical Engineering, Electrical Engineering, and Industrial Design. Having completed long-distance operation tests in outdoor environments, they are currently conducting final checks for the finals. The main competition will be held from May 27th to 30th at the MDRS in Utah, USA.
※ Related Links
MR2 Official Website: https://urc-kaist.github.io/
MR2 Instagram: https://www.instagram.com/urc_mr2/
MR2 YouTube: https://www.youtube.com/@MR2KAISTRoverTeam
2026.04.03 View 303 -
KAIST Researchers Unveil Technical Principles Behind Antibacterial Graphene Toothbrushes with 10 Million Units Sold
< (From left) Professor Hyun Jung Chung , Ph.D candidate Ju Yeon Chung, Ph.D candidate Sujin Cha, Professor Sang Ouk Kim >
Hygiene in everyday items that touch the body—such as clothing, masks, and toothbrushes—is critically important. The underlying principle of how graphene selectively eliminates only bacteria has now been revealed. A KAIST research team has presented the potential for a next-generation antibacterial material that is safe for the human body and capable of replacing antibiotics.
KAIST announced on March 25th that a joint research team, led by Professor Sang Ouk Kim from the Department of Materials Science and Engineering and Professor Hyun Jung Chung from the Department of Biological Sciences, has identified the mechanism by which Graphene Oxide (GO) exhibits powerful antibacterial effects against bacteria while remaining harmless to human cells. Graphene oxide is a nanomaterial consisting of an atomic level carbon layer (graphene) with oxygen attached; it is characterized by its ability to mix well with water and implement various functions.
This study is highly significant as it provides molecular-level proof of graphene's antibacterial action, which had not been clearly understood until now.
The research team confirmed that graphene oxide performs "selective antibacterial action" by attaching to and destroying only the membranes of bacteria, much like a magnet attaches only to specific metals, while leaving human cells untouched. This occurs because the oxygen functional groups on the surface of graphene oxide selectively bind with a specific component (POPG) found only in bacterial cell membranes. Simply put, it recognizes a "target" present only in bacterial membranes to attach and destroy the structure. In this context, phospholipids are fatty components that make up the membrane surrounding a cell, and POPG is a component primarily present in bacteria.
< Schematic diagram of the selective interaction between graphene oxide and cell membranes >
< Identification of selective interaction mechanisms at the molecular level through microscopic and chemical analysis of artificial lipid vesicles mimicking cell membranes >
Nanofibers applying this principle effectively inhibited the growth of various pathogenic bacteria, including superbugs resistant to antibiotics. Animal experiments also confirmed its effectiveness in promoting wound healing without inducing inflammation.
< Verification of antibacterial and wound healing enhancement effects in a porcine infected wound model >
Furthermore, fibers using this material maintained their antibacterial functions even after multiple washes, showing potential for use in various industrial fields such as apparel and medical textiles.
This technology is already being applied to consumer products. The graphene antibacterial toothbrush, released through the original patents of the faculty-led startup 'Materials Creation Co., Ltd.,' has sold over 10 million units, proving its commercial viability. Additionally, GrapheneTex—textile materiala incorporating this technology—was used in the uniforms of the Taekwondo demonstration team at the 2024 Paris Olympics and is expected to play an active role in functional sportswear at upcoming international sporting events like the 2026 Asian Games.
< Commercially available graphene toothbrush >
< Graphene material image (AI-generated image) >
Professor Sang Ouk Kim explained, "This study is an example of scientifically uncovering why graphene can selectively kill bacteria while remaining safe for the human body." He emphasized, "By utilizing this principle, we can expand beyond safe clothing without harsh chemicals to an infinite range of applications, including wearable devices and medical textile systems."
Sujin Cha (PhD program, Department of Materials Science and Engineering) and Ju Yeon Chung (Integrated MS/PhD program, Department of Biological Sciences) participated as first authors. Professor Hyun Jung Chung participated as a co-corresponding author. The research was published on March 2nd in the prestigious materials science journal, Advanced Functional Materials.
※ Paper Title: Biocompatible but Antibacterial Mechanism of Graphene Oxide for Sustainable Antibiotics, DOI: 10.1002/adfm.202313583
Additionally, Nanowerk (http://www.nanowerk.com/), a global portal for nanotechnology, featured these findings as a 'Spotlight' titled "Graphene oxide destroys bacteria without harming human tissue."
This research was conducted with support from the 'Nano/Material Technology Development (R&D)' program, the 'Individual Basic Research' program, and the 'Mid-Career Researcher Support Program' funded by the Ministry of Science and ICT.
2026.03.26 View 1980 -
KAIST Reveals the Formation Mechanism of Skyrmions Inside Magnets… A Clue to Solving AI Power Consumption
<(From Left) Prof.Se Kwon Kim, Dr. Gyungchoon Go>
“Skyrmions,” in which electron spins inside a magnet are arranged like vortices, are a key structure in next-generation spintronics technology. KAIST researchers have shown that skyrmions can form using only the fundamental physical interactions within magnets, without requiring special physical conditions. This finding expands the possibility of realizing skyrmions in a wide range of magnetic materials and suggests new potential for developing next-generation ultra-low-power information devices with data storage densities tens to hundreds of times higher than current technologies.
KAIST (President Kwang Hyung Lee) announced on the 19th of March that a research team led by Professor Se Kwon Kim from the Department of Physics has proposed a new theoretical framework showing that vortex-like magnetic structures can naturally emerge solely through magnetoelastic coupling—the interaction between magnetism and lattice structure.
The team demonstrated that the interaction between spins (the intrinsic magnetic property of electrons) and lattice deformation (the slight distortion of atomic arrangements) alone can lead to the spontaneous formation of vortex-like magnetic structures.
In particular, skyrmions—vortex-like spin structures found inside magnetic materials—are extremely small and highly stable, making them promising candidates for ultra-high-density, low-power information devices. However, until now, forming such structures was believed to require specific physical conditions such as crystal asymmetry or strong spin–orbit coupling.
The researchers theoretically showed that even without such special conditions, magnetoelastic coupling, which naturally occurs in most magnetic materials, is sufficient to generate a structure in which skyrmions and antiskyrmions are alternately arranged.
Magnetoelastic coupling refers to the phenomenon in which magnetism (spin) and lattice deformation influence each other, and it is a fundamental physical property present in nearly all magnetic materials. The team showed that when this coupling becomes sufficiently strong, the original ground state—where magnetization is uniformly aligned—becomes unstable and transitions into a new vortex-like ordered state.
In this process, they proposed a new mechanism in which spin tilting and lattice distortion occur simultaneously, forming a chiral spin texture composed of alternating skyrmions and antiskyrmions.
Professor Se Kwon Kim explained, “This study demonstrates that skyrmion-like magnetic structures can form even without specific or exotic interactions. It is particularly meaningful in that it suggests the possibility of realizing such structures in two-dimensional magnetic materials, where research is currently very active.”
This study was led by Gyungchoon Go, who participated as the first author. The research was published on February 11 in the internationally renowned journal Physical Review Letters, recognizing its significance in the field of physics.
※ Paper title: “Magnetoelastic Coupling-Driven Chiral Spin Textures: A Skyrmion-Antiskyrmion-like Array,” DOI:https://doi.org/10.1103/5csz-pw7x
※ Main Authors: Gyungchoon Go (first author), Se Kwon Kim (corresponding author)
This research was supported by the Samsung Science and Technology Foundation, the Brain Pool Plus Program by the National Research Foundation of Korea, and the Sejong Science Fellowship.
2026.03.19 View 606 -
Longevity mediated by suppressing age-associated circRNA
< (Back row from left) Prof. Yoon Ki Kim, Prof. Seung-Jae V. Lee, and Gwangrog Lee; (Front row from left) Dr. Sung Ho Boo, Sieun S. Kim, Seokjin Ham, and (top) Donghun Lee >
Cells in our bodies produce RNA based on genetic information stored in DNA, and RNA serves as a blueprint for making proteins. Researchers at our university have discovered a new phenomenon: removing 'circular RNA' that accumulates in cells as we age can slow down aging and extend lifespan. This study provides crucial clues for uncovering the principles of aging and developing treatment strategies for related diseases.
Professor Seung-Jae V. Lee’s research team (RNA-Mediated Healthspan and Longevity Research Center) from the Department of Biological Sciences, in collaboration with research teams led by Professors Yoon Ki Kim and Gwangrog Lee, announced on the 18th that they discovered the RNASEK protein—an enzyme that degrades circular RNA—plays a vital role in slowing aging and extending lifespan.
Until now, circular RNA has been regarded mainly as an aging marker because of its stability, which allows it to accumulate over time. However, the molecular mechanism for removing this RNA and its direct link to aging had not been clearly identified. The research team conducted this study to determine how the accumulation of circular RNA affects aging and whether an intracellular management system exists to regulate it.
Using Caenorhabditis elegans (C. elegans), a short-lived roundworm widely used in aging research, the team first confirmed that the circular RNA-degrading enzyme RNASEK is essential for longevity. They also discovered that as aging progresses, the amount of RNASEK decreases, resulting in an abnormal accumulation of circular RNA within cells.
Conversely, artificially increasing the levels of RNASEK (overexpression) extended the lifespan and allowed the organisms to survive longer in a healthy state. This implies that the process of appropriately removing cellular circular RNA is critical for maintaining health and longevity.
The research team also found that RNASEK prevents the toxic aggregation of circular RNAs in aged organisms. . When RNASEK is deficient and circular RNA accumulates, "stress granules" form abnormally inside the cell, which can impair cellular functions and accelerate aging.
RNASEK works alongside the chaperone protein HSP90 (which helps proteins avoid misfolding or clumping) to inhibit the formation of these stress granules and help cells maintain a normal state. Notably, this phenomenon was observed not only in C. elegans but also in human cells. In mammals, RNASEK also functions to directly degrade circular RNA; a deficiency of RNASEK in human cells and mouse models led to premature aging.
< Diagram showing progress toward longevity or aging depending on circular RNA and the removal enzyme RNASEK >
The researchers explained that this study is significant as it identifies a mechanism for regulating aging at the RNA level. They suggested that research using RNASEK to control circular RNA could lead to the development of treatment strategies for human aging and degenerative diseases.
Professor Seung-Jae V. Lee of KAIST, who led the study, explained, "Until now, circular RNA was merely regarded as a marker of aging that accumulates over time due to its stability. This study proves that circular RNA accumulated during aging actually induces aging, and that RNASEK, which removes it, is a key regulator that slows aging and induces healthy longevity."
< (AI-generated image) Longevity induced by the circular RNA-removing enzyme RNASEK >
Drs. Sieun S. Kim, Seokjin Ham, Sung Ho Boo, and Donghun Lee from the KAIST Department of Biological Sciences participated as joint first authors. The research results were published on February 24 in the world-renowned scientific journal Molecular Cell.
Paper Title: Ribonuclease $\kappa$ promotes longevity by preventing age-associated accumulation of circular RNA in stress granules
DOI: 10.1016/j.molcel.2026.01.031
This research was conducted with support from the Leader Researcher Program of the National Research Foundation of Korea.
2026.03.18 View 1065 -
World’s First SoulMate AI Semiconductor: A Personalized Digital Soulmate Developed
< (From left) KAIST Professor Hoi-Jun Yoo and PhD candidate Seongyon Hong >
While Large Language Models (LLMs) like ChatGPT are adept at answering countless questions, they often remain unaware of a user's minor habits or previous conversational contexts. This is why AI, despite being deeply integrated into our daily lives, can still feel like a "stranger." Overcoming these limitations, researchers at KAIST have developed the world’s first AI semiconductor, dubbed "SoulMate," which learns and adapts to a user’s speech style, preferences, and emotions in real-time—becoming a true "digital soulmate."
KAIST announced on March 17th that a research team led by Professor Hoi-Jun Yoo from the Graduate School of AI Semiconductors has developed SoulMate, a personalized LLM accelerator that evolves according to the specific characteristics of the user.This technology is being hailed as a core semiconductor breakthrough that will accelerate the era of "Hyper-Personalized AI"—moving beyond "AI for everyone" to an AI that learns and responds to an individual's unique conversational style and preferences.
The core of SoulMate lies in On-Device AI technology, which processes data directly on the device without going through external servers (the cloud). The team directly implemented Retrieval-Augmented Generation (RAG), which generates customized answers based on remembered conversations, and Low-Rank Adaptation (LoRA), which immediately reflects and learns from user feedback, within the semiconductor itself.
< SoulMate AI Semiconductor Chip >
Through this, SoulMate has realized a real-time personalized AI system that responds to the user at a staggering speed of 0.2 seconds (216.4 ms) while simultaneously performing learning tasks.
< SoulMate Application Demo >
Furthermore, the team applied a Mixed-Rank architecture that optimizes processing methods based on the importance of information, drastically reducing power consumption. The semiconductor operates at an ultra-low power of just 9.8 milliwatts (mW)—approximately 1/500th of a typical smartphone processor's power consumption—allowing it to handle complex learning and inference simultaneously on mobile devices without battery concerns.
In particular, SoulMate features a "Security-Complete AI" structure where all personal data is processed internally within the device rather than being transmitted to external servers, fundamentally blocking any risk of personal information leaks. The research team expects this technology to pair with next-generation platforms such as smartphones, wearables, and personal AI devices to open a true era of personalized AI services.
< SoulMate Demo Screen >
"This research mimics the process of people building friendships, providing the technical foundation for AI to evolve into a true companion for the user," said Professor Hoi-Jun Yoo. "Future AI will move beyond being a mere tool to become a 'Best Friend' that understands me best anytime, anywhere, while perfectly protecting personal privacy."
The study, with PhD student Seongyon Hong as the first author, was selected as a "Highlight Paper" at the International Solid-State Circuits Conference (ISSCC) held in San Francisco this past February, garnering significant attention from the global academic community.
Paper Title: SoulMate: A 9.8mW Mobile Intelligence System-on-Chip with Mixed-Rank Architecture for On-Device LLM Personalization Authors: Seongyon Hong, Jiwon Choi, Jeonggyu So, Nayeong Lee, Wooyoung Jo, Zhamaliddin Kalzhan Link: https://ieeexplore.ieee.org/document/11409048
At the conference, the research team successfully demonstrated how the AI's response style changes in real-time according to user reactions using the actual semiconductor chip, proving the excellence of Korean AI semiconductor technology. The SoulMate AI semiconductor is planned for commercialization around 2027 through the faculty-led startup "OnNeuro AI."
< SoulMate Demonstration Photo >
This research was conducted with support from the Information and Communication Broadcast Innovation Talent Cultivation Program of the Ministry of Science and ICT and the Institute of Information & Communications Technology Planning & Evaluation (IITP).
2026.03.17 View 913 -
Professor Jihyeon Yeom Selected as Early Career Advisory Board Member for Top Chemistry and Materials Journal
< Professor Jihyeon Yeom >
KAIST announced on the 13th that Professor Jihyeon Yeom from the Department of Materials Science and Engineering has been selected as a member of the Early Career Advisory Board (ECAB) for Chemical Reviews, widely considered the world's most prestigious academic journal in the field of chemistry.
Published by the American Chemical Society (ACS), Chemical Reviews is a flagship review journal that comprehensively organizes and surveys the most influential research achievements across all areas of chemistry and materials science. It is evaluated as a top-tier international journal in the field.
The journal boasts an Impact Factor (IF) of 56, ranking it among the highest of all scientific journals worldwide. Its authority is particularly significant because it is a review journal that analyzes global research trends to suggest future academic directions, rather than simply publishing individual experimental data.
The ECAB, which began its term in January 2026, consists of 10 researchers selected from among rising global science leaders. Candidates are evaluated based on academic originality, research impact, and contributions to the scientific community. Members provide advisory roles for the journal's academic direction and strategic planning, contributing to the discovery of next-generation research trends and the expansion of global research networks.
This selection highlights that Professor Yeom’s research achievements are receiving high international acclaim.
Professor Yeom is conducting research on applying "chirality"—a property where objects, like DNA or proteins, are mirror images of each other but cannot be perfectly superimposed—to nanomaterials. Her core work involves precisely controlling atomic arrangements to realize artificial materials that can interact naturally with biological signals.
In particular, she is gaining attention for developing next-generation smart healthcare technology that combines light-responsive chiral materials with Artificial Intelligence (AI) to detect and analyze minute changes in the human body in real time. Professor Yeom explained that these chiral characteristics offer new possibilities for expanding information transmission and processing capabilities beyond simple structural properties.
Building on this foundation, she plans to expand her research into various fields, including precision medical diagnostic technology, next-generation optoelectronic devices utilizing circularly polarized light, and AI-based platforms.
Professor Yeom has established herself as a global leader in chiral materials research, recently publishing results in world-renowned journals such as Nature Communications, Advanced Materials, ACS Nano, and Accounts of Chemical Research.
"Chirality is not just a structural characteristic, but a new degree of freedom that expands the functional and information-processing capabilities of matter," said Professor Yeom. "I plan to expand my research into chiral-based electronic and optical devices, bio-diagnostic technologies, and AI-based spectroscopic platforms in the future."
This ECAB selection once again demonstrates the research competitiveness and international standing of the KAIST Department of Materials Science and Engineering. It is expected to further strengthen KAIST's role as a global research hub in the field of next-generation materials research.
2026.03.13 View 884 -
KAIST Explores Solutions for African Youth Employment with World Bank and African Union
< Group photo of meeting participants >
KAIST announced on the 6th that the 'Jobs for Youth in Africa Knowledge Exchange' platform was held in Nairobi, Kenya, from March 3 to 5 (local time). The event was hosted by the Kenyan government and co-organized by the World Bank Group, the African Union, and the KAIST Global Center for Development and Strategy (G-CODEs).
As a high-level policy implementation platform dedicated to addressing youth employment challenges in Africa, the event drew approximately 200 participants, including government officials from over 20 African nations, international organizations, the private sector, academia, and development cooperation partners. KAIST participated as a key global partner linking technology and policy, presenting innovation models for employment systems based on digital and Artificial Intelligence (AI) technologies.
< Scene from the meeting hosted by the Kenyan government >
With Africa’s youth population projected to double by 2050, the continent faces significant hurdles such as high unemployment rates and informal employment. This event marked the second face-to-face meeting of the 'Jobs for Youth in Africa Community of Practice (CoP),' which was launched in Kigali, Rwanda, in 2025. The meeting aimed to share policy experiences among member states and materialize scalable implementation models. Salim Mvurya, Kenya's Cabinet Secretary for Youth Affairs, Creative Economy, and Sports, attended the opening ceremony and emphasized that youth job creation is a critical priority at both national and continental levels.
The program focused on several key themes:
Evidence-based youth employment strategies
Innovation in employment systems through digital and AI technologies
Improving labor market outcomes through Recognition of Prior Learning (RPL)
Business environment reforms and strengthening value chain linkages
Notably, in the session titled "Digital and AI-based Employment System Innovation," Professor Kyung Ryul Park of KAIST shared Korea’s digital transformation experiences and AI application cases, proposing directions for data-driven policy design and the development of technology-based employment platforms. Additionally, KAIST Professor Ga-young Park facilitated mutual learning and connected cases of scalable youth employment projects across countries during the "Global Cafe Session."
< Professor Kyung Ryul Park of KAIST delivering a presentation >
Participants visited the project site of "National Youth Opportunities Towards Advancement (NYOTA)," an initiative pursued by the Kenyan government and the World Bank. There, they observed a comprehensive youth employment model that integrates vocational training, job matching, and entrepreneurship support. The site visit served as a practical learning opportunity to share the processes of policy design and execution.
Since last year, KAIST has been involved in digital innovation projects for youth employment in East Africa through the Korea-World Bank Partnership Facility (KWPF). Through this event, the university reaffirmed its status as a global cooperation hub leading technology-based policy innovation.
"The issue of youth employment is a structural challenge that combines digital transformation, industrial strategy, and educational reform," stated Professor Kyung Ryul Park. "KAIST will continue to present actionable policy models based on data and technology while strengthening international cooperation."
This Knowledge Exchange platform is evaluated as a significant milestone that reaffirmed the African youth employment agenda as a core priority of international cooperation and solidified the foundation for enhancing policy implementation capabilities. A follow-up workshop is scheduled to be held early next year at the Kenya Advanced Institute of Science and Technology (Kenya-AIST) campus in Konza, Nairobi, which is modeled after KAIST.
2026.03.10 View 790 -
KAIST Surpasses the Limits of AlphaFold… AI Now Predicts Whether Drugs Actually Work
<(From Left) Ph.D candidate Hyojin Son, Professor Gwan-su Yi>
Proteins in our body function like switches. When a drug binds to a protein, the structure at the binding site changes, and this structural change propagates throughout the protein, turning its function on or off. Google DeepMind’s AlphaFold3 successfully predicted whether drugs bind to proteins and the three-dimensional structure of binding sites. However, it could not predict how signals propagate inside the protein after drug binding, how the entire structure changes, or whether the protein’s function is ultimately activated or inhibited. KAIST researchers have developed an AI that predicts not only whether a drug binds but whether it actually works.
KAIST (President Kwang Hyung Lee) announced on the 4th of March that a research team led by Professor Gwan-Su Yi of the Department of Bio and Brain Engineering has developed an artificial intelligence model called “GPCRact” that predicts whether candidate molecules not only bind to G-protein-coupled receptors (GPCRs)—a major drug target—but also actually activate the protein.
GPCRs act as “signal receivers” on the surface of cells. When hormones, neurotransmitters, or drugs send signals from outside the cell, GPCRs function as gates that receive these signals and transmit them into the cell. There are about 800 types of GPCRs in the human body, and roughly 30–40% of currently marketed drugs target them. They are key proteins involved in numerous physiological functions, including heart rate regulation, blood pressure control, pain sensing, immune responses, and emotional regulation.
However, a drug binding to a GPCR does not always trigger the desired biological function. Structural changes inside the protein and subsequent signal transmission determine whether the drug actually produces an effect. This process is known as allosteric signal propagation.
The research team designed the AI to learn the drug action process in two stages: ① the drug–target binding stage, and ② the intracellular signal propagation stage within the protein. The three-dimensional protein structure was represented as an atom-level graph, and an attention mechanism was applied to enable the model to learn important signaling pathways. Through this approach, the AI analyzes not only the drug binding signal but also the internal signaling pathways of the protein to predict whether the protein becomes activated.
As a result, the model significantly improved the prediction performance of drug activity even in proteins with complex structures that existing models struggled to analyze. Importantly, the model does not simply output “active” or “inactive.” It also presents the key internal signaling pathways that form the basis of its predictions, overcoming the limitations of so-called “black-box AI.”
<Schematic diagram of drug activity prediction and mechanism interpretation using the GPCRact artificial intelligence model>
This represents an important advance, as it allows researchers to interpret and verify predictions while simultaneously improving the reliability and efficiency of drug discovery. In the future, the model is expected to serve as a precision drug discovery AI platform capable of predicting not only whether drugs bind to GPCRs but also whether they truly activate them in various diseases targeting GPCRs.
<AI-generated image to help illustrate the research>
Professor Gwan-Su Yi explained, “Allosteric structural change refers to a phenomenon in which a drug binds to one part of a protein and its influence propagates internally, altering the function of other regions,” adding, “The key contribution of this research is incorporating this operational principle into deep learning.” He further noted, “We plan to expand the model to various proteins and ultimately develop technologies capable of predicting cellular and whole-body responses.”
Ph.D candidate Hyojin Son participated as the first author in this study. The paper was published on January 15 in the international journal Briefings in Bioinformatics, one of the leading journals in the field of bioinformatics.
※ Paper title: “GPCRact: a hierarchical framework for predicting ligand-induced GPCR activity via allosteric communication modeling”
DOI: https://doi.org/10.1093/bib/bbaf719※ Author information: Hyojin Son (KAIST, first author), Gwan-Su Yi (KAIST, corresponding author)
This research was supported by the Basic Research Program for Individual Research funded by the Ministry of Science and ICT and the National Research Foundation of Korea (RS-2025-24533057).
2026.03.09 View 867 -
Professor Kuk-Jin Yoon’s Research Team at the Department of Mechanical Engineering Achieves Landmark Success with 10 Papers Accepted at CVPR 2026
<Professor Kuk-Jin Joon from Department of Mechanical Engineering>
Professor Kuk-Jin Yoon’s research team from our university’s Department of Mechanical Engineering has once again demonstrated its overwhelming academic prowess by having a total of 10 papers accepted as lead authors at the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2026 (CVPR 2026).
CVPR is the most influential international conference in the fields of artificial intelligence and visual intelligence. Since its inception in 1983, it has selected outstanding research through a rigorous peer-review process every year. For CVPR 2026, a total of 16,092 papers were submitted worldwide, with 4,090 accepted, resulting in a competitive acceptance rate of approximately 25.42%. Achieving 10 accepted papers as lead or corresponding authors from a single laboratory is regarded as an exceptionally rare and world-class feat.
Professor Kuk-Jin Yoon’s team conducts extensive research with the ultimate goal of achieving human-level visual intelligence. The papers accepted this year cover cutting-edge topics in computer vision, including:
Event camera-based technologies
Perception technologies for autonomous driving
AI optimization and adaptation techniques
This achievement follows the team's remarkable success at ICCV 2025 last year, where they published 12 papers as lead/corresponding authors. The results at CVPR 2026 further solidify the laboratory's position as a global hub for pioneering computer vision research. The research team plans to continue contributing to the advancement of future AI technologies by tackling challenging research that transcends the limitations of existing methods.
Meanwhile, CVPR 2026 is scheduled to be held in Denver, Colorado, USA, from June 3 to June 7.
<CVPR 2026 (Denver, USA)>
2026.03.06 View 1583