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Professor Yiyun Kang Selected as TED 2026 Main Stage Speaker
< Professor Yiyun Kang (Photo Credit: Ryan Lash / TED) >
KAIST announced on April 17th that Professor Yiyun Kang of the Department of Industrial Design has been selected as a speaker for the Main Stage at TED 2026, the world-renowned knowledge conference.
Founded in 1984 under the motto "Ideas Worth Spreading," TED is an American non-profit knowledge platform where scholars, innovators, and artists from around the globe gather annually to lead global discourse. Previous Korean speakers on the Main Stage include novelist Young-ha Kim (2012) and violinist Ji-hae Park (2013). In 2011, roboticist Professor Dennis Hong stood on the main conference stage as the first Korean-American speaker.
< TED Lecture Photo (Photo Credit: Ryan Lash / TED) >
Professor Kang’s selection is particularly significant as it marks the first time since TED moved its venue to Vancouver, Canada, in 2014 that a Korean national—an artist and scholar actively based in South Korea, rather than an overseas resident or defector—has been invited to the Main Stage. Furthermore, it marks the return of a Korean speaker to the main stage after a 12-year hiatus, serving as a symbolic milestone.
The TED 2026 annual conference is being held from April 13 to 17 at the Vancouver Convention Centre in Canada, under the theme "ALL OF US." Professor Kang took the Main Stage on April 15, the third day of the conference, to present visual insights and philosophical solutions for a future where Artificial Intelligence (AI), humans, and nature must coexist. The lecture video will be edited and released globally via the official TED website and YouTube channel this coming July.
In this talk, Professor Kang defines AI and the climate crisis as "problems we understand intellectually but fail to feel physically," noting that data- and information-centric communication methods often lower our sense of reality. She proposes the potential of art as a means to bridge this gap. Specifically, Professor Kang will demonstrate on stage how to transform complex challenges into visual and sensory experiences through cases from her own projects.
Notably, this presentation transcends traditional lecture formats, structured as an "Immersive Talk" that transforms the entire stage into an artistic space. Rather than just listening, the audience participates by experiencing the content with their entire bodies.
Professor Yiyun Kang is a world-class media artist and researcher who crosses the boundaries between sensation and technology, and materiality (physical forms) and immateriality (elements like light, video, and data). She leads the Experience Design Lab (XD Lab) at KAIST and has consistently explored the convergence of technology and art through collaborations with NASA, Google Arts & Culture, and the Victoria and Albert Museum (V&A).
"Humanity is currently at a critical turning point that will determine the coexistence of technology and nature," Professor Kang stated. "Through this TED stage, I aim to ensure that AI and the climate crisis are perceived not just as mere information, but as realities of our lives. I hope to create a practical opportunity to expand fragmented individual perceptions into collective human solidarity through the creative energy of art."
< TED 2026 Professor Yiyun Kang (Source: TED Website) >
2026.04.18 View 338 -
Breakthrough in Data Processing via Light Control... Enhancing AI Accelerators and Quantum Communication
< (From left) Undergraduate researcher Taewon Kim and Professor Sangsik Kim >
A new technology has been developed that allows light to be "designed" into desired forms, potentially making Artificial Intelligence (AI) and communication technologies faster and more accurate. A KAIST research team has developed an "integrated photonic resonator"—a core component of next-generation optical integrated circuits that process data using light. The research is particularly significant as it was led by an undergraduate student. This technology is expected to serve as a key foundation for next-generation security technologies such as high-speed data processing and quantum communication.
KAIST announced on the 15th that a research team led by Professor Sangsik Kim from the School of Electrical Engineering, in collaboration with Professor Jae Woong Yoon’s team from the Department of Physics at Hanyang University (President Kigeong Lee), has developed a new integrated photonic resonator structure capable of freely controlling optical signals by utilizing light interference (the phenomenon where two light waves meet and influence each other).
Photonic Integrated Circuits (PICs) process data at ultra-high speeds and with low power consumption using light. They are garnering significant attention as a fundamental platform technology for next-generation fields such as AI, data centers, and quantum information processing.
The core of this technology lies in the precision with which light can be controlled. Specifically, the ability to freely adjust the spectrum (color or wavelength distribution) and phase response (timing or wave position) of optical signals is essential for implementing high-performance optical communication and computing. However, conventional methods have faced fundamental limitations.
The integrated photonic resonator (optical resonator) focused on by the research team is a key optical device that traps light in a specific space to amplify it or select specific colors (wavelengths), similar to how the body of a musical instrument amplifies sound. However, existing single-bus resonators have had limitations in precisely adjusting the phase and spectrum of optical signals.
To overcome these challenges, the research team introduced a "dual-bus" structure. This design allows light that has passed through the resonator to recombine with light that has not, enabling precise control over interference. This allows for the free design of optical signals into desired forms, making it possible to control various types of light signals that were previously difficult to implement.
By applying this technology, the research team secured new characteristics for more precise control of wavelength properties and presented new possibilities for non-linear frequency conversion research (changing the color of light). Utilizing this technology enables faster and more accurate data processing, which is expected to provide the groundwork for performance enhancements in future high-speed data centers, AI accelerators, and quantum communication systems.
This research is especially meaningful as it was led by an undergraduate student. Taewon Kim, an undergraduate student who conducted the study through the KAIST Undergraduate Research Program (URP), stated, "I was able to develop the resonator principles I learned in the Introduction to Integrated Optics class into actual device designs and a published paper."
< Research Image of the Dual-bus Resonator >
Professor Sangsik Kim remarked, "This study goes beyond proposing a new device; it demonstrates that by precisely analyzing previously overlooked optical characteristics, physical limitations can be overcome. We expect this to contribute broadly to the development of optics-based AI accelerators and optical communication technologies."
KAIST undergraduate student Taewon Kim participated as the lead author of this study, and the results were published on March 6th in the international optics journal, Laser & Photonics Reviews.
Paper Title: Dual-bus resonator for multi-port spectral engineering DOI: 10.1002/lpor.202502935 Authors: Taewon Kim, Mehedi Hasan, Yu Sung Choi, Jae Woong Yoon, and Sangsik Kim
This research was supported by the KAIST URP Program, the Institute of Information & Communications Technology Planning & Evaluation (IITP), the U.S. Asian Office of Aerospace Research and Development (AOARD), and the National Research Foundation of Korea (NRF).
2026.04.16 View 277 -
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 485 -
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 713 -
KAIST, Developing National Positioning Infrastructure with Wi-Fi-Based Precision Technology… A Step Toward “Location Sovereignty”
<(From Left) Prof. Dong-Soo Han, Dr. Kyuho Son, Dr. Byeongcheol Moon, Dr. Sumin Ahn, Ph.D candidate Seungwoo Chae>
A Korean research team has developed a technology that enables precise indoor positioning using only a smartphone. Developed over eight years by KAIST researchers, this technology is expected to help secure critical time in missing-person searches and is being recognized as a “location sovereignty” solution that could reshape the current location service ecosystem dominated by global big tech companies such as Google and Apple.
KAIST (President Kwang Hyung Lee) announced on the 2nd pf April that a research team led by Professor Dongsoo Han of the School of Computing has developed a core technology that can build a nationwide high-precision positioning infrastructure in a short time and at low cost by combining smartphone Wi-Fi signals with real-world address data. This achievement is the result of eight years of research, during which the team filed around ten patents to enhance the technology’s completeness.
The key feature of this technology is its use of Wi-Fi signals collected by smartphones in everyday life. It can provide precise location information anywhere in the country without requiring large-scale equipment or additional infrastructure. It also maintains high accuracy in environments where GPS is weak, such as indoors, underground, or in dense high-rise areas.
In particular, this research is seen as a challenge to the location service ecosystem currently led by global platform companies. Today, most location data worldwide is accumulated and managed by a small number of big tech firms, and Korea also relies heavily on these platforms.
Most importantly, this research establishes a foundation for independently building and managing location data generated domestically. Amid ongoing debates over exporting high-resolution national maps (1:5,000 scale spatial data detailing buildings and roads), the importance of data sovereignty is growing. This technology is drawing attention as an alternative that could reduce dependence on global big tech and realize “location sovereignty.”
The research team proposed a method that automatically combines Wi-Fi signals collected during smartphone app usage with the actual address of the location. This allows the construction of a unique “signal pattern map” (signal fingerprint) for each place, with accuracy improving as more data accumulates.
In a real-world demonstration in Daejeon, using a gas meter reading app, an average of about 30 Wi-Fi signals were detected per household in apartment complexes. This confirmed that city-scale location data can be rapidly built using this approach.
<Status of Radio Map Construction in Daejeon Using a Gas Meter Reader App>
<Address-Based Automation of Wireless Signal Collection and AI-Based Location Labeling Techniques for Collected Wireless Signals>
This technology is expected to significantly reduce location errors—previously up to hundreds of meters—in emergency situations such as missing-person searches, helping secure critical response time. It can also be applied to “location-based authentication,” allowing payments only at specific locations, thereby helping prevent financial crimes such as identity theft or unauthorized remote transactions.
Furthermore, precise location data is a key infrastructure for future AI industries, including autonomous driving, robotics, and logistics. This achievement is expected to enhance competitiveness across these sectors.
<Research Use Image (AI-Generated Image)>
Professor Dongsoo Han stated, “Positioning infrastructure is not just a convenience technology but a core asset directly linked to national data sovereignty,” adding, “It is time for the government, telecom companies, and platform providers to collaborate in building an independent national positioning infrastructure.”
This research was supported by the Ministry of Science and ICT, the National Research Foundation of Korea, the National Fire Agency, and the Korea Evaluation Institute of Industrial Technology (KEIT) (Grant No. RS-2025-02313957).
2026.04.03 View 534 -
KAIST, Making Pharmaceuticals with Light and Air… Solving a Long-Standing Challenge in Chemical Synthesis
<(From Left) Professor Sang Woo Han, Researcher Jin Wook Baek>
In chemical processes for producing pharmaceuticals, catalysts are the key to determine production speed and cost. However, until now, there has been a trade-off between “precise but disposable catalysts” and “reusable catalysts.” A KAIST research team has developed an eco-friendly catalytic technology that combines these two types, operating with light and air. This opens a pathway to producing pharmaceutical ingredients more cheaply and cleanly, with expected reductions in carbon emissions and environmental pollution.
KAIST (President Kwang Hyung Lee) announced on the 30th of March that a research team led by Professor Sang Woo Han of the Department of Chemistry has succeeded in combining two different types of catalysts into one system. One is a silver (Ag)-based catalyst that operates in a solid state, and the other is an organic photocatalyst, DDQ (a substance that triggers chemical reactions upon absorbing light), which operates in solution. By enabling these two catalysts to function together, the team made it possible to carry out previously difficult reactions more efficiently.
< Schematic diagram of the operation of a heterogeneous–homogeneous hybrid photocatalytic system >
Using this technology, the researchers successfully produced amines—key raw materials for pharmaceuticals—through an environmentally friendly process using light and air. This demonstrated that the desired substances can be synthesized without additional chemical reagents, proving the practicality of the technology.
Conventional organic photocatalysis required additional chemicals to reuse catalysts after reactions, or suffered from reduced efficiency due to slow reaction rates when using oxygen from air.
To address this, the research team proposed a method of reusing byproducts generated during the reaction. These byproducts restore the catalyst to a reusable state, while oxygen in the air helps sustain this cycle. In other words, instead of being used once and discarded, the catalyst regenerates itself and continues operating in a “cyclic system.”
As a result, they established a “cyclic catalytic system” that continues functioning without the need for additional chemical inputs. Notably, this system operates with light and air. Light activates the catalyst to initiate the reaction, while air restores the used catalyst to its active state. In essence, the catalyst continuously “recharges” and operates repeatedly. Since air leaves only water as a byproduct in this process, the environmental burden is significantly reduced.
In addition, to solve the issue of reduced performance when different catalysts interact, the team introduced lithium salt (LiClO₄). This substance helps regulate interactions between the two catalysts, significantly improving their stability and lifespan.
< A hybrid catalyst powered by light and air as energy sources >
Professor Sang Woo Han stated, “This research is the first to successfully integrate an inorganic photochemical loop system—where a metal-based catalyst reacts under light and returns to its original state—into the field of organic synthesis,” adding, “It represents an important advancement that combines the advantages of different catalytic systems to dramatically reduce the carbon footprint of the chemical industry.” He further noted, “It opens a new pathway for producing high-value compounds, such as pharmaceutical ingredients, in the most environmentally friendly way.”
This research was conducted with Jin Wook Baek of the KAIST Department of Chemistry as the first author, and the results were published on March 18 in the Journal of the American Chemical Society (JACS), a leading journal in chemistry.
※ Paper title: “Merger of heterogeneous and homogeneous photocatalysis for arene C–H Amination”
※ DOI: 10.1021/jacs.5c20824
This research was supported by the National Research Foundation of Korea’s Mid-career Researcher Program.
2026.03.30 View 513 -
World’s First AI-Managed Unmanned Factory Implemented... Construction of Physical AI KAIROS
< Integrated Operation of Heterogeneous Logistics Robot Systems >
KAIST announced on March 23rd that Professor Young Jae Jang's team from the Department of Industrial and Systems Engineering has constructed ‘KAIROS’ (KAIST AI Robot Orchestration Systems), a physical AI testbed that integrates and controls heterogeneous robots, sensors, facilities, and digital twins into a single system.
KAIROS is a 100% unmanned factory platform based on physical AI and is the first integrated testbed of its kind in Korea, developed with support from the Ministry of Science and ICT (MSIT). It is particularly noteworthy as a domestic integrated solution aimed at exporting "Dark Factories" in the future.
The most significant feature of KAIROS is its structure, which integrates and controls various factory equipment through a single AI agent-based Operating System (OS). While existing factory automation was operated around individual devices, KAIROS integrates Autonomous Mobile Robots (AMR), humanoid robots, collaborative robots, and automation facilities into a single intelligent platform. Through this, the concept of ‘Physical AI-based factory operation’—where the entire factory is operated like a single AI system—has been realized.
The core of this testbed is the 100% domestic integration of the entire process from sensors and control to data processing. By integrating key elements of a Dark Factory—including logistics robots (AMR), OHT, 3D shuttles, humanoid robots, collaborative robots, industrial sensors and PC controllers, wireless charging systems, digital twins and simulations, and AI-based integrated control and safety management systems—using domestic technology, the project has replaced factory automation equipment and software that were heavily dependent on foreign technology and laid the foundation for a ‘K-Manufacturing Factory Export Model.’
As part of the Physical AI Pre-verification Project, the MSIT has supported the establishment of a demonstration lab within the KAIST Industrial Management Building. On March 23, Vice Minister Bae Gyeong-hoon (Minister of Science and ICT) visited KAIST to announce the National Physical AI Strategy (Draft) and unveil the KAIROS-based Dark Factory demonstration site.
At the event, the factory operating system of the KAIST demonstration lab, joint physical AI demonstration results with Chonbuk National University, and the direction of the ‘Team Korea Physical AI (TK-PAI)’ alliance—a cooperative structure of domestic companies—were discussed.
< KAIROS Operation Plan Announcement >
< KAIROS Demonstration >
< KAIROS Factory Site >
KAIST plans to further advance the next-generation factory operating system (OS), covering the design, construction, and operation of Dark Factories through KAIROS, and to develop simulation and virtual verification environments.
In addition, the university intends to utilize the platform as a testing and evaluation site where domestic robot and automation companies can pre-verify highly reliable equipment, thereby increasing industrial applicability. Furthermore, the goal is to develop physical AI-based Dark Factory solutions capable of competing with global companies such as Siemens (Germany), FANUC (Japan), and Yaskawa (Japan) to pursue entry into the global market.
Kwang Hyung Lee, President of KAIST, stated, “KAIROS is the beginning of a new industrial paradigm where AI directly operates factories. KAIST will lead manufacturing innovation based on physical AI and contribute to ensuring South Korea’s leadership in global industrial competition.”
Professor Young Jae Jang, who led the construction of KAIROS, explained, “KAIROS goes beyond individual automation technologies to implement the concept of a factory operating system (OS) that integrates diverse robots and facilities into one system. It will serve as a foundation for domestic companies to verify physical AI technologies applicable to actual industrial sites and expand into the global market.”
2026.03.23 View 1680 -
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 725 -
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 1003 -
Student Entrepreneur Inseo Chung Donates 1 Billion Won to Foster Inclusive AI Talent
< Photo of the Donation Agreement Ceremony >
KAIST announced on March 11th that Inseo Chung (28), an undergraduate student in the School of Interdisciplinary Studies and CEO of the global music-tech startup MPAG, donated 1 billion won in development funds on the 10th to foster ‘Inclusive AI’ talent. Inclusive AI talent refers to experts who research and develop AI technologies so that the socially vulnerable, including people with disabilities and the technologically marginalized, can also enjoy the benefits of AI technology.
Inseo Chung is a student entrepreneur who has dedicated himself to “solving social problems through technology” while balancing startup activities and research during his studies. Alongside his academic advisor, Professor Hyunwook Ka of the School of Interdisciplinary Studies, he has consistently researched how technology can embrace those who are marginalized.
His research, including software for the hearing impaired, studies for users requiring linguistic support in media, and bidirectional assistive technology devices for the visually and hearing impaired, has garnered attention at domestic and international conferences. This work has also led to several patent applications filed under the name of KAIST.
He founded the global music-tech startup MPAG, which operates a sheet music sales platform and AI music education service with over 4 million members worldwide, and is also developing features to provide braille sheet music for the visually impaired.
The donation will be used to establish a Master’s and Doctoral Education & Research Program in ‘AI-based Assistive Technology’ for the disabled and the technologically and socially vulnerable within the newly established KAIST AI College. This program aims to conduct research on AI-based rehabilitation assistive technology, nurture Master’s and Doctoral-level experts in the field, and build an inclusive technology ecosystem. Professor Hyunwook Ka, an expert in this field, will lead the operation and guidance of the degree program to ensure research continuity and expertise.
Inseo Chung emphasized, “As AI technology advances exponentially, it is absolutely necessary to expand into ‘Inclusive AI’ so that its benefits reach the disabled and the technologically marginalized. I am confident that through a formal graduate program, the number of experts in this field will grow, and KAIST’s specialized AI research capabilities will serve as the catalyst.”
This is not Inseo Chung’s first donation. He previously donated through the KAIST Development Foundation in 2024 and 2025 before contributing an additional 1 billion won this year. The 2024 donation was used to create the ‘Creative Workshop’ for junior students in the School of Interdisciplinary Studies to realize their creative ideas, and the 2025 donation was allocated to the School of Computing.
President Kwang Hyung Lee stated, “The decision by student Inseo Chung to donate the fruits of his startup efforts for the future of his alma mater and the realization of social values serves as a great inspiration to all members of KAIST. We will do our best to nurture inclusive AI talent so that the benefits of technology can spread throughout society, honoring the donor’s intent.”
2026.03.11 View 1035 -
Secret to Drug Addiction Relapse Found: Brain's Addiction Circuit Identified
<(From Left) Dr. Minju Jeong,(UCSD), Prof. Byung Kook Lim (UCSD), Prof. Se-Bum Paik (KAIST)>
Drug addiction carries an extremely high risk of relapse, as cravings can be reignited by minor stimuli even long after one has stopped using. Previously, this phenomenon was attributed to a decline in the function of the prefrontal cortex (PFC), which regulates impulses. However, a joint international research team has recently revealed that the cause of addiction relapse is not a simple decline in brain function, but rather an imbalance in specific neural circuits.
KAIST announced on March 9th that a research team led by Prof. Se-Bum Paik from the Department of Brain and Cognitive Sciences and Prof. Byung Kook Lim from the University of California, San Diego (UCSD) has identified the core principle by which specific inhibitory neurons in the prefrontal cortex regulate cocaine-seeking behavior.
In particular, the research team focused on parvalbumin-positive (PV) inhibitory neurons, which regulate the balance of neural signals by suppressing the activity of other neurons in the brain. They confirmed that these cells act as a "brake gate" that controls excitatory signals in the brain and serve as a crucial factor in determining drug-seeking behavior that emerges after withdrawal.
The prefrontal cortex (PFC) of our brain can properly perform its "braking" function to suppress impulses when excitatory and inhibitory signals are in balance. To investigate how chronic drug exposure disrupts this balance, the research team conducted cocaine administration experiments on mice. During this process, they tracked when inhibitory neurons in the PFC were activated and how they sent signals to downstream brain regions.
The experimental results showed that parvalbumin (PV) cells, which account for about 60-70% of the inhibitory neurons in the PFC, were highly active when the mice attempted to seek cocaine. However, when "extinction training"—training to stop seeking the drug—was conducted, the activity of these cells significantly decreased. This demonstrates that the activity patterns of PV cells are not permanently fixed by addiction but can be readjusted through the extinction process.
<Figure 1. Experimental design illustrating cocaine self-administration and longitudinal tracking of prefrontal cortical neural activity during cocaine-seeking behavior>
The research team confirmed that artificially suppressing PV cell activity significantly reduced cocaine-seeking behavior in mice. Conversely, activating these cells caused the drug-seeking behavior to persist even after the extinction process. This effect was specifically observed in drug-addiction behavior and did not appear with general rewards like sugar water. Furthermore, this phenomenon was not observed in somatostatin (SOM) cells—another type of inhibitory neuron—indicating that PV cells selectively regulate drug addiction behavior.
<Figure 2. Comparison of single-neuron activity, population activity patterns, and behavioral modulation of prefrontal inhibitory neurons across different stages of cocaine-seeking behavior>
The team also identified the specific brain circuit through which these PV cells operate. Signals originating from the prefrontal cortex are transmitted to the reward circuit of the Ventral Tegmental Area (VTA), a key brain region related to reward. This pathway emerged as the central channel for regulating addiction behavior, determining whether or not to seek the drug again. In this process, PV neurons act as a "regulatory switch," controlling the flow of signals to influence dopamine signaling and deciding whether to maintain or suppress addictive behavior.
In short, the study revealed that addiction relapse is not due to an overall functional decline of the prefrontal cortex, but is determined by whether PV neurons regulate the neural pathway connecting the PFC to the reward circuit.
<Figure 3. Schematic illustrating the prefrontal–reward circuit mechanism that determines drug-seeking behavior>
Prof. Se-Bum Paik stated, "This research shows that drug addiction is a circuit-level problem arising from a collapse in the regulatory balance of specific neurons and downstream neural circuits. The discovery that parvalbumin (PV) cells act as a 'gate' for addictive behavior will provide a crucial lead for developing precision-targeted treatment strategies in the future."
This study was led by Dr. Minju Jeong (UCSD) as the first author, with Prof. Byung Kook Lim (UCSD) and Prof. Se-Bum Paik (KAIST) serving as co-corresponding authors. The findings were published online on February 26 in Neuron, a premier journal in the field of neuroscience.
Paper Title: Distinct Interneuronal Dynamics Selectively Gate Target-Specific Cortical Projections in Drug Seeking
DOI: 10.1016/j.neuron.2026.01.002
Full Author List: Minju Jeong, Seungdae Baek, Qingdi Wang, Li Yao, Eun Ji Lee, Arturo Marroquin Rivera, Joann Jocelynn Lee, Hyeonseok Jang, Dhananjay Bambah-Mukku, Christine Hyun-Seung Mun, Tyler Boesen, Sumit Nanda, Cheol Ryong Ku, Hong-wei Dong, Benoit Labonté, Se-Bum Paik, and Byung Kook Lim.
This research was conducted with the support of the Basic Research Program in Science and Engineering of the National Research Foundation of Korea.
2026.03.10 View 981 -
KAIST Team Led by Dong-won Lee Wins Grand Prize at the 2nd Global Quantum AI Competition
< (From Left) M.S candidate Dongwon Lee from School of Electrical Engineering, Ph.D candidate Jaehun Han from Graduate School of Quantum Science and Technology >
"Team Yangja-jorim," consisting of Dongwon Lee, Gyungjun Kim and Jaehun Han , has been honored with the Grand Prize at the '2026 2nd Global Quantum AI Competition.' The event was hosted and organized by NORMA, a specialized quantum computing company.
This global competition was designed to expand hands-on experience with quantum cloud services and to discover next-generation talent in the field of quantum artificial intelligence. The event spanned approximately 70 days, beginning with the preliminary opening ceremony held at Korea University’s Hana Square on December 17 last year. The final winners were announced during an awards ceremony held at NORMA's headquarters on the 27th of last month.
The competition attracted significant interest from quantum technology talent worldwide, including university students, developers, and researchers. A total of 137 teams participated in the preliminaries, with the top 10 teams advancing to the finals—a competitive ratio of approximately 13.7 to 1.
< An acquaintance attended the awards ceremony of the 2nd Global Quantum AI Competition to accept the prize on behalf of the team. >
In the final round, participants were presented with four generative problems utilizing the Quantum Circuit Born Machine (QCBM) model. To overcome the current limitations of quantum machine learning, the contestants were tasked with designing and validating Quantum-Classical Hybrid Generative AI models that integrate classical techniques. Notably, the final problem provided an opportunity to verify the proposed methods using a real Quantum Processing Unit (QPU) from Rigetti Computing, a leading global quantum computing firm.
The judging process employed a double-blind system, where the identities of both evaluators and participants remained undisclosed to ensure maximum fairness and credibility.
"Through this competition, we were able to explore the research potential of the quantum AI field more deeply," said KAIST's Team Yangja-jorim in their acceptance speech. "We hope to continue contributing to the advancement of quantum technology through consistent research and new challenges."
2026.03.10 View 1060