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Sharing Failures Makes Challenges Easier, Proposal for a National Campaign for Global Failure Day
KAIST announced that it will launch a national campaign on 'Global Failure Day,' October 13th, to encourage anyone in the nation to share their small, everyday failures.
KAIST President Kwang Hyung Lee emphasized, "A culture unafraid of failure is the foundation of innovation. I hope that for just one day, October 13th, people recall and share the small failures they experienced today. That moment can be the starting point for a new challenge."
'Global Failure Day' is a commemorative day that began in 2010 by students at Aalto University in Finland under the spirit of "Failure is inherent in the nature of challenge; let's respect failure." At the time, amid the collapse of Nokia and job insecurity, it garnered significant social support and spread as a national campaign. It continued in countries like Germany, the UK, and Canada, and has now established itself globally as a day for reflecting on failure.
Since the establishment of the KAIST Failure Lab, there has been a clear shift in the perception of failure. According to a survey conducted by the Failure Lab in December last year, 73.9% of KAIST members responded that the atmosphere encourages new challenges, which is twice the Korean social average (35.6%). Furthermore, 52% responded that it is a "place tolerant of failure," much higher than the Korean average (20.5%).
To spread this shift in perception nationwide, President Lee personally posted a message on social media on the 10th, sharing his own story of a failure where he felt embarrassed after having a donation rejected, and proposed participation. Additionally, the KAIST Failure Lab announced a 'Failure Sharing Action Proposal' that anyone can easily participate in on a daily basis.
The main proposals include: △ Sharing 'Today's Failure' with family and friends; △ Having a 'One-Line Failure Sharing' time at work or in a gathering; △ Posting small failure stories on social media; △ Sharing photos/videos of disastrous cooking or silly mistakes; and △ Creating memes that humorously express failure.
Seongho Cho, Director of the Failure Lab, explained, "Simply sharing failures lightly can change the attitude towards them. The fact that the failure acceptance rate among KAIST members is twice as high as the general public is also thanks to this culture."
Since its establishment in 2021, the KAIST Failure Lab has promoted a culture of failure sharing within the university through various programs, such as the 'Failed Project Bragging Contest,' failure essay contests, and 'Failure Photo Voice.' It has been conducting perception surveys among KAIST members every two years since 2022, and in last year's survey, over 80% of respondents said the lab's activities contributed to improving perception, resilience, and flexibility.
Based on these achievements, the scope of the activities is being expanded nationwide this year. Notably, the top 10 teams in the 'AI × Failure Idea Contest' for university/graduate students are scheduled to present their ideas at the 'Failure Conference' to be held at KAIST on November 7th.
President Lee stated, "KAIST will continue to broaden the culture of reflecting on and sharing failure together with the public."
More details can be found on the KAIST Failure Lab website (https://caf.kaist.ac.kr).
2025.10.13 View 2119 -
AI Nüshu Wins International Award
< (From left) Dr. Yuqian Sun, Professor Chang-Hee Lee of the Department of Industrial Design, and Ali Asadipour, Director of CSRC at the Royal College of Art >
'Nüshu (女書)' is the world's only women's script, a unique writing system created autonomously by women in Hunan Province, China, starting around the 19th century. These women, excluded from Hanzi education, used it to record their lives and communicate with each other. A research team from KAIST participated in the 'AI Nüshu (女书)' project, which combines the script's significance (creation amidst oppression, female solidarity, linguistic experimentation) with modern technology, winning a prestigious international award often called the 'Academy Award of the media art world.'
KAIST announced on the 10th that the 'AI Nüshu' project, jointly conducted by Professor Chang-Hee Lee's research team from the Department of Industrial Design and Ali Asadipour, Director of the Computer Science Research Center at the Royal College of Art (RCA), was selected for the Honorary Mention in the Digital Humanity category at the 'Prix Ars Electronica 2025,' the world's highest-level media art festival.
< Installation image of 'AI Nüshu' >
The 'Prix Ars Electronica,' known as the 'Academy Award of the media art world,' is the premier international media art competition held annually in Linz, Austria. This competition, which discovers innovative works spanning the boundaries of art and science, saw 3,987 submissions from 98 countries this year, with only two works receiving the honor in the Digital Humanity category.
The award-winning work, 'AI Nüshu (女书),' is based on 'Nüshu,' the world's only women's script created by Chinese women who were excluded from literacy education to record and communicate their lives.
The KAIST research team and collaborators combined this script with Computational Linguistics to create an installation that visitors can directly experience.
The artificial intelligence within the artwork learns the communication methods of pre-modern Chinese women and generates its own new language. This is regarded as a symbol of resistance against the patriarchal order and a feminist endeavor that moves beyond Western-centric views on language.
< Example of the same sentence expressed in English, Chinese, Nüshu, and AI Nüshu >
It also received high praise for artistically presenting the possibility of machines creating new languages, going beyond the preconception that 'only humans create language.'
Dr. Yuqian Sun of the Royal College of Art expressed her feelings, saying, "Although there were many difficulties in my life and research process, I feel great reward and emotion through this award."
Professor Chang-Hee Lee of the KAIST Department of Industrial Design stated, "It is very meaningful that this contemplative art, born from the intersection of history, humanities, art, and technology, has led to such a globally prestigious award."
Detailed information about the project can be found on the official Prix Ars Electronica website (https://ars.electronica.art/prix/en/digitalhumanity/).
2025.10.13 View 5514 -
City AI Research Institute Selected for Ministry of Science and ICT's Brain Pool (BP) Institutional Recruitment Program
<Professor Yoonjin Yoon from the Department of Civil and Environmental Engineering at KAIST>
KAIST's City AI Research Institute (Director: Professor Yoonjin Yoon) has been selected for the Ministry of Science and ICT's Brain Pool (BP) Institutional Recruitment Program. This achievement is the culmination of a joint proposal spearheaded by Institute Director Professor Yoonjin Yoon, along with Professor Soyoung In of the Department of Civil and Environmental Engineering and Professor Sujin Han of the School of Electrical Engineering. It is the result of high praise for the institute's research capabilities in the field of Urban AI and its potential for international collaboration.
This BP project, with a total budget of 2.1 billion KRW, will be carried out over 28 months. It plans to actively pursue AI research focused on solving urban problems by inviting renowned overseas scholars to focus on three core areas: Geospatial AI, Climate AI, and Physical AI. Through this, the institute aims to develop core AI technologies based on a collaboration system involving industry, academia, research institutions, and government. This will lead the way in sustainable urban growth and the transition to an 'Cognitive City,' continuing research to proactively diagnose and respond to various issues that citizens can experience firsthand.
This project is particularly significant as it is a female-centered institutional Brain Pool project. KAIST plans to systematically support the growth of early-career female researchers and actively expand the participation of next-generation female scientists and engineers in international research networks. This is expected to significantly contribute to the development of female research personnel and the strengthening of research leadership, areas that are relatively lacking in domestic science and engineering fields.
Furthermore, through long-term joint research with researchers from world-leading universities such as MIT, NYU, UIUC, UBC, USF, and the University of Toronto, the City AI Research Institute is set to become a leading Urban AI research hub in Korea and Asia.
Moving forward, the institute will continue to dedicate itself to core research for responding to the complex challenges of future cities and advancing innovative technology through artificial intelligence, based on global cooperation.
2025.10.10 View 2744 -
Physics Informed AI Excels at Large Scale Discovery of New Materials!
<(From left) Ph.D candidates Songho Lee, Donggeun Park, and Hyeonbin Moon, and Professor Seunghwa Ryu from the Department of Mechanical Engineering; (top) Professor Jae Hyuk Lim from Kyung Hee University and Dr. Wabi Demeke from KAIST>
One of the key steps in developing new materials is “property identification,” which has long relied on massive amounts of experimental data and expensive equipment, limiting research efficiency. A KAIST research team has introduced a new technique that combines “physical laws,” which govern deformation and interaction of materials and energy, with artificial intelligence. This approach allows for rapid exploration of new materials even under data-scarce conditions and provides a foundation for accelerating design and verification across multiple engineering fields, including materials, mechanics, energy, and electronics.
KAIST (President Kwang Hyung Lee) announced on the 2nd of October that Professor Seunghwa Ryu’s research group in the Department of Mechanical Engineering, in collaboration with Professor Jae Hyuk Lim’s group at Kyung Hee University (President Jinsang Kim) and Dr. Byungki Ryu at the Korea Electrotechnology Research Institute (President Namkyun Kim), proposed a new method that can accurately determine material properties with only limited data. The method uses Physics-Informed Machine Learning (PIML), which directly incorporates physical laws into the AI learning process.
<Schematic Diagram of a Physics-Based Machine Learning Methodology for Understanding Material Properties>
In the first study, the researchers focused on hyperelastic materials, such as rubber. They presented a Physics-Informed Neural Network (PINN) method that can identify both the deformation behavior and the properties of materials using only a small amount of data obtained from a single experiment. Whereas previous approaches required large, complex datasets, this research demonstrated that material characteristics can be reliably reproduced even when data is scarce, limited, or noisy.
In the second study, the team turned to thermoelectric materials—new materials that convert heat into electricity and electricity into heat. They proposed a PINN-based inverse inference technique that can estimate key indicators, such as thermal conductivity (how well heat is transferred) and the Seebeck coefficient (how efficiently electricity is generated), from just a few measurements.
Going further, the researchers introduced a Physics-Informed Neural Operator (PINO), an AI model that understands the physical laws of nature, and showed that it can generalize to previously unseen materials without requiring retraining.
In fact, after training the system on 20 materials, they tested it on 60 entirely new materials, and in all cases it predicted their properties with high accuracy. This breakthrough points to a future where large-scale, high-speed screening of countless candidate materials becomes possible.
This achievement goes beyond simply reducing the need for experiments. By intricately combining physical laws with AI, the researchers provided the first example of improving experimental efficiency while preserving reliability.
Professor Seunghwa Ryu, who led both studies, stated, “This is the first case of applying AI that understands physical laws to real material research. It enables reliable identification of material properties even when data availability is limited, and it is expected to expand into various engineering fields.”
The first paper, co-first-authored by KAIST Mechanical Engineering PhD candidates Hyeonbin Moon and Donggeun Park, was published on August 13 in Computer Methods in Applied Mechanics and Engineering.
※ Paper title: “Physics-informed neural network-based discovery of hyperelastic constitutive models from extremely scarce data”
※ DOI: https://doi.org/10.1016/j.cma.2025.118258
The second paper, co-first-authored by KAIST Mechanical Engineering PhD candidates Hyeonbin Moon and Songho Lee, and Dr. Wabi Demeke, was published on August 22 in npj Computational Materials.
※ Paper title: “Physics-informed neural operators for generalizable and label-free inference of temperature-dependent thermoelectric properties” ※ DOI: https://doi.org/10.1038/s41524-025-01769-1
Meanwhile, the first study was supported by the Korea Research Foundation and the Ministry of Science and ICT’s INNOCore Program, as well as by a research project from the Ministry of Food and Drug Safety. The second study was carried out with support from the Korea Research Foundation and the Ministry of Science and ICT’s INNOCore Program.
2025.10.10 View 3780 -
Next Generation Robots Roaming Shipyards and City Centers
< Diden Robotics Research Team Co., Ltd (Leftmost person in the front row is CEO Joon-Ha Kim)>
KAIST announced on the September 30th that domestic robot startups, founded on KAIST research achievements, are driving new innovation at shipyards and urban worksites.
An industrial walking robot that freely climbs walls and ceilings and a humanoid walking robot that walks through downtown Gangnam are attracting attention as they enter the stage of commercialization. The stars are DIDEN Robotics Co., Ltd. and Eurobotics Co., Ltd.
Diden Robotics is providing a new breakthrough in the industrial automation market, including the shipbuilding industry, by commercializing its innovative 'Seungwol (Ascend and Cross) Robot' technology, which allows it to move freely and work on steel walls and ceilings. Eurobotics is commercializing world-class humanoid walking technology, and this achievement is scheduled to be officially presented at the international humanoid robot conference, 'Humanoids 2025,' to be held on October 1st.
< Diden Robot's Outer Plate (Longi) and Welding Test >
Diden Robotics is a robotics startup jointly founded in March 2024 by four alumni from the KAIST Mechanical Engineering Hu-bo Lab DRCD research team (Professor Hae-Won Park). Its flagship product, 'DIDEN 30,' is a quadrupedal robot designed for use in high-risk work environments that are difficult for humans to access, combining autonomous driving technology, a foot-shaped leg structure, and magnetic feet.
The 'DIDEN 30' successfully completed the 'Longitudinal (longi) Overcoming Test,' in which it stepped over steel stiffeners (longitudinals) densely installed as part of the structure at a ship construction site, proving its potential for field deployment. Currently, the company is conducting research to enhance its functionality so it can stably pass through access holes, the narrow entryways inside ships. It is also pushing for performance improvements so it can be deployed for real tasks such as welding, inspection, and painting starting in the second half of 2026.
A next-generation bipedal walking robot, 'DIDEN Walker,' is also under development. Targeting the completion of a prototype in the fourth quarter of 2025, it is being designed for stable walking in cramped and complex industrial environments. Plans are also underway to equip it with an upper-body manipulator for automated welding in the shipbuilding industry.
Diden Robotics is accelerating the advancement of its proprietary 'Physical AI' technology. The core is the self-developed AI learning platform, 'DIDEN World,' which applies an offline reinforcement learning method where the AI generates optimal motion data in a virtual simulation beforehand and learns without trial and error, increasing learning efficiency and stability.
< Diden Robot (DIDEN 30) >
Furthermore, to actually implement the AI technology, the company is internalizing its hardware and advancing its 3D recognition technology, which serves as the robot's 'eyes.' It is aiming for a completely autonomous walking system that requires no worker intervention by 2026, using technology such as 3D mapping based on four cameras.
In addition to this technological development, Diden Robotics successfully performed the longitudinal overcoming, Seungwol test, and welding work on blocks under construction through a joint development with Samsung Heavy Industries in September. This is a significant achievement, meaning Diden Robotics' technology has been validated in actual industrial settings, moving beyond the laboratory level.
Meanwhile, Diden Robotics is collaborating with major domestic shipyards, including Samsung Heavy Industries, HD Hyundai Samho, Hanwha Ocean, and HD Korea Shipbuilding & Offshore Engineering, to develop site-customized robots.
Joon-Ha Kim, CEO of Diden Robotics, stated, "The successful tests at the Samsung Heavy Industries site proved the practicality and stability of our technology. We will establish ourselves as a leading company in solving labor shortages and driving automation in the shipbuilding industry."
< (Eurobotics Research Team Co., Ltd.)(Leftmost person in the top row is CEO Byung-ho Yoo) >
Eurobotics is an autonomous walking startup jointly founded by three alumni from Professor Hyun Myung's research team at KAIST. It is promoting the commercialization of autonomous walking technology for indoor and outdoor industrial sites, including rough terrain. In a recently released video, a humanoid equipped with control technology developed by Eurobotics attracted attention by walking naturally through the crowd in downtown Gangnam.
The core technology is the 'Blind Walking Controller.' It determines locomotion based only on internal information without external sensors like cameras or LiDAR, enabling stable walking regardless of day, night, or weather. The robot performs locomotion by 'imagining' the terrain without precise terrain modeling, demonstrating robust performance with the same controller across various environments such as sidewalks, downhill slopes, and stairs.
This technology originated from the quadrupedal walking competition at the 2023 International Conference on Robotics and Automation (ICRA), where Professor Myung's lab participated, and proved its world-class capability by winning, beating MIT by a large margin. At the time, Byungg-ho Yoo, CEO of Eurobotics, led the team, and Co-CTOs Min-ho Oh and Dong-kyu Lee directly participated in developing the core autonomous walking technology. Based on this, they continued further development tailored to the humanoid environment and have entered the commercialization stage.
< Eurobotics' Humanoid Walking >
Byung-ho Yoo, CEO of Eurobotics, emphasized, "This video is the first step toward complete humanoid autonomous walking. We will develop KAIST's research achievements into technologies that can be immediately utilized in industrial settings."
Hyeonmin Bae, Head of the KAIST Startup Center, said, "We will provide close support from the initial stages to help the on-campus robotics industry grow actively and assist them in settling down stably."
Kwang Hyung Lee, President of KAIST, stated, "This achievement is a representative case showing that KAIST's fundamental technologies are rapidly spreading to industrial fields through startups. KAIST will continue to actively support innovative entrepreneurship based on challenging research and help lead the global robotics industry."
※ https://2025humanoids.org https://www.seoulairobot.com/
2025.09.30 View 7190 -
3D Printing Becomes Stronger and More Economical with Light and AI
<(Front) Ph.D. candidate Jisoo Nam, (Back row, from left) Ph.D. candidate Boxin Chen, Professor Miso Kim>
Photocurable 3D printing, widely used for everything from dental treatments to complex prototype manufacturing, is fast and precise but has the limitation of being fragile and easily broken by impact. A KAIST research team has developed a new technology to overcome this weakness, paving the way for the more robust and economical production of everything from medical implants to precision machine parts.
KAIST (President Kwang Hyung Lee) announced on the 29th that Professor Miso Kim's research team in the Department of Mechanical Engineering has developed a new technology that fundamentally resolves the durability limitations of photocurable 3D printing.
Digital Light Processing (DLP)-based 3D printing is a technique that uses light to solidify liquid resin (polymer) to rapidly manufacture precise structures, used in various fields such as dentistry and precision machinery. While traditional injection molding offers excellent durability, it requires significant time and cost for mold fabrication. In contrast, photocurable 3D printing allows for flexible shape realization but has a durability drawback.
Professor Kim's team solved this problem by combining two key elements:
A new photocurable resin material that absorbs shock and vibration while allowing for a wide range of properties from rubber to plastic.
A machine learning-based design technology that automatically assigns optimal strength to each part of the structure.
<Figure 1. Schematic of a new manufacturing technology for high-durability photocurable 3D printing using light-controlled gradient structures. This approach integrates the development of stiffness-controllable viscoelastic polyurethane acrylate (PUA) materials, machine learning-based property gradient optimization, and grayscale DLP 3D printing. The technology enhances damping performance and alleviates stress concentration, providing an integrated solution for high reliability, durability, and customized manufacturing. It demonstrates potential applications in structural components subjected to repetitive loads such as joints, automotive interior parts, and precision machinery components>
The research team developed a Polyurethane Acrylate (PUA) material incorporating dynamic bonds, which significantly increases shock and vibration absorption capability compared to existing materials. Furthermore, they successfully applied 'grayscale DLP' technology, which controls the light intensity to achieve different strengths from a single resin composition, thereby assigning customized strength to specific areas within the structure. This concept is inspired by the harmonious and different roles played by bone and cartilage in the human body.
A machine learning algorithm automatically proposes the optimal strength distribution by analyzing the structure and load conditions. This organically connects material development and structural design, enabling customized strength distribution.
The economic efficiency is also noteworthy. Previously, expensive 'multi-material printing' technology was required to achieve diverse material properties, but this new technology yields the same effect with a single material and a single process, significantly reducing production costs. It eliminates the need for complex equipment or material management, and the AI-based structural optimization shortens research and development time and product design costs.
Professor Miso Kim explained, "This technology simultaneously expands the degrees of freedom in material properties and structural design. Patient-specific implants will become more durable and comfortable, and precision machine parts can be manufactured more robustly." She added, "The fact that it secures economic viability by realizing various strengths with a single material and single process is highly significant," and "We anticipate its utilization across various industrial fields such as biomedical, aerospace, and robotics."
The research was spearheaded by Professor Miso Kim's team at the KAIST Department of Mechanical Engineering, with Ph.D. candidate Jisoo Nam as the first author. Boxin Chen, a student from Sungkyunkwan University, also contributed to the collaborative research. The findings were published online on July 16 in the world-renowned journal in materials science, Advanced Materials (IF 26.8). Recognizing the research's excellence, it was also selected for the journal's Frontispiece.
Paper Title: Machine Learning-Driven Grayscale Digital Light Processing for Mechanically Robust 3D-Printed Gradient Materials
DOI: 10.1002/adma.202504075
The achievements of this research have brought Professor Miso Kim significant international attention, as she simultaneously received the 'Wiley Rising Star Award' and the 'Wiley Women in Materials Science Award' in July 2025, hosted by the international academic publisher Wiley.
The Wiley Rising Star Award is given to emerging researchers with the potential for academic leadership, and the Wiley Women in Materials Science Award is a prestigious honor established to celebrate outstanding female scientists in the field of materials science.
<Figure 2. Frontispiece image (scheduled for Issue 42). Multi-property structure fabricated using a photocurable 3D printer. By varying the projector light intensity by location, stronger light creates rigid regions while weaker light forms flexible ones. AI designs an optimized pattern for the structural shape to prevent fracture and reinforce the overall strength.>
This research was supported by the National Research Foundation of Korea (NRF) grants funded by the Korean government (MSIT) (Nos. NRF-2021R1A2C2095767, RS-2023-00254689, and RS-2024-00433654).
2025.09.30 View 4519 -
KAIST Develops Semiconductor Neuron that Remembers and Responds Like the Brain
<(From left, clockwise) Professor Kyung Min Kim, Min-Gu Lee, Dae-Hee Kim, Dr. Han-Chan Song, Tae-Uk Ko, Moon-Gu Choi, and Eun-Young Kim>
The human brain does more than simply regulate synapses that exchange signals; individual neurons also process information through “intrinsic plasticity,” the adaptive ability to become more sensitive or less sensitive depending on context. Existing artificial intelligence semiconductors, however, have struggled to mimic this flexibility of the brain. A KAIST research team has now developed next-generation, ultra-low-power semiconductor technology that implements this ability as well, drawing significant attention.
KAIST (President Kwang Hyung Lee) announced on September 28 that a research team led by Professor Kyung Min Kim of the Department of Materials Science and Engineering developed a “Frequency Switching Neuristor” that mimics “intrinsic plasticity,” a property that allows neurons to remember past activity and autonomously adjust their response characteristics.
“Intrinsic plasticity” refers to the brain’s adaptive ability- for example, becoming less startled when hearing the same sound repeatedly, or responding more quickly to a specific stimulus after repeated training. The “Frequency Switching Neuristor” is an artificial neuron device that autonomously adjusts the frequency of its signals, much like how the brain becomes less startled by repeated stimuli or, conversely, increasingly sensitive through training.
The research team combined a “volatile Mott memristor,” which reacts momentarily before returning to its original state, with a “non-volatile memristor,” which remembers input signals for long periods of time. This enabled the implementation of a device that can freely control how often a neuron fires (its spiking frequency).
<Figure 1. Conceptual comparison between a neuron and a frequency-tunable neuristor. The intrinsic plasticity of brain neurons regulates excitability through ion channels. Similarly, the frequency-tunable neuristor uses a volatile Mott device to generate current spikes, while a non-volatile VCM device adjusts resistance states to realize comparable frequency modulation characteristics>
In this device, neuronal spike signals and memristor resistance changes influence each other, automatically adjusting responses. Put simply, it reproduces within a single semiconductor device how the brain becomes less startled by repeated sounds or more sensitive to repeated stimuli.
To verify the effectiveness of this technology, the researchers conducted simulations with a “sparse neural network.” They found that, through the neuron’s built-in memory function, the system achieved the same performance with 27.7% less energy consumption compared to conventional neural networks.
They also demonstrated excellent resilience: even if some neurons were damaged, intrinsic plasticity allowed the network to reorganize itself and restore performance. In other words, artificial intelligence using this technology consumes less electricity while maintaining performance, and it can compensate for partial circuit failures to resume normal operation.
Professor Kyung Min Kim, who led the research, stated, “This study implemented intrinsic plasticity, a core function of the brain, in a single semiconductor device, thereby advancing the energy efficiency and stability of AI hardware to a new level. This technology, which enables devices to remember their own state and adapt or recover even from damage, can serve as a key component in systems requiring long-term stability, such as edge computing and autonomous driving.”
This research was carried out with Dr. Woojoon Park (now at Forschungszentrum Jülich, Germany) and Dr. Hanchan Song (now at ETRI) as co-first authors, and the results were published online on August 18 in Advanced Materials (IF 26.8), a leading international journal in materials science.
※ Paper title: “Frequency Switching Neuristor for Realizing Intrinsic Plasticity and Enabling Robust Neuromorphic Computing,” DOI: 10.1002/adma.202502255
This research was supported by the National Research Foundation of Korea and Samsung Electronics.
2025.09.30 View 3919 -
Thinking outside the box to Fabricate Customized 3D Neural Chips
<(From Left) Professor Yoonkey Nam, Dr. Dongjo Yoon from the Department of Bio and Brain Engineering>
Cultured neural tissues have been widely used as a simplified experimental model for brain research. However, existing devices for growing and recording neural tissues, which are manufactured using semiconductor processes, have limitations in terms of shape modification and the implementation of three-dimensional (3D) structures.
By "thinking outside the box," a KAIST research team has successfully created a customized 3D neural chip. They first used a 3D printer to fabricate a hollow channel structure, then used capillary action to automatically fill the channels with conductive ink, creating the electrodes and wiring. This achievement is expected to significantly increase the design freedom and versatility of brain science and brain engineering research platforms.
On the 25th, KAIST announced that a research team led by Professor Yoonkey Nam from the Department of Bio and Brain Engineering has successfully developed a platform technology that overcomes the limitations of traditional semiconductor-based manufacturing. This technology allows for the precise fabrication of "3D microelectrode array" (neural interfaces with multiple microelectrodes arranged in a 3D space to measure and stimulate the electrophysiological signal of neurons) in various customized forms for in vitro culture chips.
Existing 3D microelectrode array fabrication, based on semiconductor processes, has limited 3D design freedom and is expensive. While 3D printing-based fabrication techniques have recently been proposed to overcome these issues, they still have limitations in terms of 3D design freedom for various in vitro neural network structures because they follow the traditional sequence of "conductive material patterning → insulator coating → electrode opening."
The KAIST research team leveraged the excellent 3D design freedom provided by 3D printing technology and its ability to use printed materials as insulators. By reversing the traditional process, they established an innovative method that allows for more flexible design and functional measurement of 3D neuronal network models for in vitro culture.
<Schematic Diagram of an Integrated Cell Culture Substrate-Microelectrode Array Platform for In Vitro Cultured 3D Neural Network Models>
First, they used a 3D printer to print a hollow 3D insulator with micro-tunnels. This structure was designed to serve as a stable scaffold for conductive materials in 3D space while also supporting the creation of various 3D neuronal networks. They then demonstrated that by using capillary action to fill these internal micro-tunnels with conductive ink, they could create a 3D scaffold-microelectrode array with more freely arranged microelectrodes within a complex 3D culture support structure.
The new platform can be used to create various chip shapes, such as probe-type, cube-type, and modular-type, and supports the fabrication of electrodes using different materials like graphite, conductive polymers, and silver nanoparticles. This allows for the simultaneous measurement of multichannel neural signals from both inside and outside the 3D neuronal network, enabling precise analysis of the dynamic interactions and connectivity between neurons.
Professor Nam stated, "This research, which combines 3D printing and capillary action, is an achievement that significantly expands the freedom of neural chip fabrication." He added that it will contribute to the advancement of fundamental brain science research using neural tissue, as well as applied fields like cell-based biosensors and biocomputing.
Dr. Dongjo Yoon from KAIST's Department of Bio and Brain Engineering participated as the first author of the study. The research findings were published online in the international academic journal Advanced Functional Materials (June 25th issue).
※Paper Title: Highly Customizable Scaffold-Type 3D Microelectrode Array Platform for Design and Analysis of the 3D Neuronal Network In Vitro
This research was supported by the Consolidator Grants Program and the Global Basic Research Laboratory Program of the National Research Foundation of Korea.
2025.09.26 View 3328 -
KAIST team links early life epigenetic memory to adult brain inflammation
<(From left) Professor Won-Suk Chung, Ph.D. Ph.D candidate Hyeonji Park Dr. Seongwan Park, Professor Inkyung Jung>
Why do some people remain healthy through childhood yet become more vulnerable to brain disorders such as dementia later in life? A KAIST (President Kwang Hyung Lee) -led team has uncovered a key part of the answer: a developmental ‘switch’ in astrocytes—the brain’s most abundant support cells that shapes how strongly the brain’s immune system reacts in adulthood. The study identifies a gene, NR3C1 (encoding the glucocorticoid receptor), as a master regulator of this switch and shows how early-life epigenetic ‘memory’ can predispose the adult brain to excessive inflammation.
The work was carried out by a joint team led by Professor Inkyung Jung (Department of Biological Sciences, KAIST) and Associate Director Won-Suk Chung (Center for Vascular Research, Institute for Basic Science; Professor, KAIST Biological Sciences). Using mouse models, the researchers mapped gene-regulatory programs across multiple stages of astrocyte development and found that NR3C1 acts during a brief early-postnatal window to enforce long-term immune restraint.
<The schematic illustrates how the NR3C1 gene (glucocorticoid receptor) suppresses the immune response of astrocytes. In normal (control) astrocytes, NR3C1 binds to specific regulatory regions of DNA (nGRE) to inhibit the expression of immune-related genes, thereby maintaining brain homeostasis even under immune stimulation. In contrast, in NR3C1-deficient astrocytes (KO), this suppression is lost, leading to excessive activation of inflammation-related genes such as Gfap, Il6st, Stat2, and Cxcl10. As a result, in an autoimmune encephalomyelitis (EAE) model, pronounced neuroinflammation and clinical symptoms (paralysis and severe debilitation) are observed>
To build this map, the team combined state-of-the-art 3D epigenome profiling with RNA sequencing and chromatin accessibility analyses, capturing how DNA folds and which regulatory elements contact target genes. They identified 55 stage-specific transcription factors that guide astrocyte maturation; among them, NR3C1 emerged as the critical ‘switch’ in early life. Notably, deleting NR3C1 in astrocytes did not disrupt normal development. However, when the adult mice were challenged with an autoimmune model of multiple sclerosis, animals lacking astrocytic NR3C1 mounted exaggerated inflammatory responses and developed more severe disease.
Mechanistically, the study shows that early loss of NR3C1 epigenetically primes immune genes - keeping their regulatory elements open and ready - so that later in life these genes respond too strongly to inflammatory cues. In effect, NR3C1 serves as an early ‘brake’ that prevents over-activation of astrocyte immune programs in adulthood.
“This is the first demonstration that astrocyte immune functions are governed by epigenetic memory,” said Professor Won-Suk Chung. “Our findings offer new clues to the origins of degenerative brain disorders, including Alzheimer’s disease.”
“We reveal a temporal regulatory window in astrocyte development that can set the stage for disease vulnerability in adulthood,” added Professor Inkyung Jung. “Understanding the 3D genome logic behind these programs could open paths to therapies for immune-related brain disorders such as multiple sclerosis.”
<The figure shows the three-dimensional genome structure of astrocytes at specific gene loci, illustrating how NR3C1 regulates their expression. In normal cells, NR3C1 binds to DNA and maintains the chromatin in a closed state, thereby preventing unnecessary activation between distal regulatory elements (enhancers) and gene promoters. In contrast, when NR3C1 is absent, the chromatin becomes open, creating a state in which enhancers and genes can be more easily activated. As a result, genes such as Mxi1 are overexpressed, triggering inflammatory responses. This clearly demonstrates that NR3C1 plays an essential role in maintaining immune homeostasis by stabilizing three-dimensional gene regulatory mechanisms.>
The results of this study were published online on September 22 in the international journal Nature Communications (IF 15.7), with Dr. Seongwan Park and PhD student Hyeonji Park of KAIST’s Department of Biological Sciences as co-first authors.
※ Paper title: “NR3C1-mediated epigenetic regulation suppresses astrocytic immune responses in mice,” DOI: https://www.nature.com/articles/s41467-025-64088-5
In addition, on September 17, the journal published a commentary article introducing this research: https://www.nature.com/articles/s41467-025-64102-w
This research was supported by the Suh Kyungbae Science Foundation, the Ministry of Health and Welfare, the Ministry of Science and ICT, and IBS.
Glossary - Epigenetic priming: preparing genes for rapid future activation by altering chromatin without changing DNA sequence
2025.09.25 View 4368 -
MICCAI 2025 Eve KAIST Day Successfully Held
< Scene of the KAIST Day Symposium Lectures >
KAIST announced on the September 23rd that the 'KAIST Day' special symposium, held on the eve of 'MICCAI 2025' at the Jeong Geun-mo Conference Hall of the KAIST Academic and Cultural Center on September 22, was successfully held with the attendance of more than 30 overseas scholars and 200 domestic researchers and students.
This event was a special program prepared to commemorate the hosting of MICCAI 2025 (The 28th International Conference on Medical Image Computing and Computer Assisted Intervention, Conference Chair: Professor Jina Park of KAIST School of Computing), the world's largest medical imaging conference. It was sponsored by the KAIST College of Engineering and Daejeon City, and was held under the theme of "From Insight to Intervention: Intelligent Imaging in Biomedicine."
KAIST and world-class scholars gathered to share the latest research results combining medical imaging and artificial intelligence, and to have an in-depth discussion on the future direction of next-generation medical technology, encompassing diagnosis and treatment.
Seven world-renowned scholars from the Americas, Europe, and Asia introduced their latest research, and about 30 overseas scholars toured KAIST's advanced medical imaging infrastructure and sought possibilities for collaboration by interacting with domestic researchers. In addition, attending domestic researchers and students had the opportunity for collaboration and international joint research through a networking session.
< A group photo from KAIST Day with President Kwang Hyung Lee and Conference Chair Jina Park >
This event provided an opportunity for domestic researchers to meet world-class scholars ahead of the opening of MICCAI 2025 and served as a starting point and symbolic place for KAIST and Daejeon City to foster Korea as a global hub for medical AI research. The event was planned and moderated by Professor Seungryong Cho and Associate Vice President Hyunju Lee, and was composed of four sessions. First, Professor Hyunwook Park introduced the history and development of medical imaging research at KAIST. Following this, in the "AI for Diagnosis & Disease Understanding" session, Professors Anne Martel, Kenji Suzuki, Hayit Greenspan, and Dimitris Metaxas presented their latest research on AI-based medical imaging, including cancer diagnosis, early detection, rare disease analysis, and multi-modal fusion.
In the next "Imaging Intelligence for Intervention" session, Professors Nasir Navab, Yongkwan Park, James Ji, Leo Joskowicz, and Hyunmin Bae shared clinical application cases such as AR/VR surgical assistance, ultra-high-resolution imaging, atlas-based analysis, surgical planning support, and personalized treatment with neuroimaging.
Each presentation demonstrated the possibilities of future medical imaging expanding beyond diagnosis to treatment and personalized medicine, and active exchanges continued through discussions and Q&A. After the lectures, overseas researchers toured KAIST's advanced infrastructure and conducted in-depth discussions with domestic researchers.
In addition, with the support of NVIDIA, the "NVIDIA Isaac for Healthcare Hands-on Lab" was held, allowing researchers and students to directly experience the latest AI medical platform.
< Invited speakers and attendees of the symposium >
Professor Jina Park of the KAIST School of Computing and Conference Chair of MICCAI 2025 said, "MICCAI is the world's top-level medical AI conference with a focus on clinical application. We organized this event to introduce KAIST's challenging research to the international community and to create new synergy through academic exchange. We expect MICCAI 2025, which will be held from the 23rd to the 27th at the Daejeon Convention Center, to become a representative international academic event for Daejeon, with more than 3,200 people registered."
KAIST President Kwang Hyung Lee said, "The hosting of MICCAI 2025 is an achievement that shows the international status of Korean science and technology. In particular, this pre-conference symposium held at KAIST was a meaningful event where world-class scholars gathered to discuss the future of medical imaging and AI, and it was an opportunity to once again confirm KAIST's status. KAIST will continue to take the lead in research and education that contributes to the promotion of human health by expanding global cooperation."
※ MICCAI 2025 Website: https://conferences.miccai.org/2025/en/
2025.09.23 View 3247 -
A Breakthrough in Parkinson's Research: Precision Diagnosis and Treatment with AI and Optogenetics
<Research team photo (from top left) Dr. Bobae Hyeon, Professor Daesoo Kim, Director Chang-joon Lee, (right) Professor Won Do Heo>
Globally recognized figures like Muhammad Ali and Michael J. Fox have long suffered from Parkinson's disease. The disease presents a complex set of motor symptoms, including tremors, rigidity, bradykinesia, and postural instability. However, traditional diagnostic methods have struggled to sensitively detect changes in the early stages, and drugs targeting brain signal regulation have had limited clinical effectiveness.
Recently, Korean researchers successfully demonstrated the potential of a technology that integrates AI and optogenetics as a tool for precise diagnosis and therapeutic evaluation of Parkinson's disease in mice. They have also proposed a strategy for developing next-generation personalized treatments.
KAIST (President Kwang Hyung Lee) announced on the 22nd of September that a collaborative research team—comprising Professor Won Do Heo's team from the Department of Biological Sciences, Professor Daesoo Kim's team from the Department of Brain and Cognitive Sciences, and Director Chang-Jun Lee's team from the Institute for Basic Science (IBS) Center for Cognition and Sociality—achieved a preclinical research breakthrough by combining AI analysis with optogenetics. Their work simultaneously demonstrated the possibility of early and precise diagnosis and treatment in an animal model of Parkinson's disease.
The research team created a Parkinson's disease mouse model with two stages of severity. These were male mice with alpha-synuclein protein abnormalities, a standard model used to simulate human Parkinson's disease for diagnostic and therapeutic research.
In collaboration with Professor Kim's team at KAIST, they introduced AI-based 3D pose estimation for behavioral analysis. The team analyzed over 340 behavioral features—such as gait, limb movements, and tremors—from the Parkinson's mice and condensed them into a single metric: the AI-predicted Parkinson's disease score (APS).
The analysis showed that the APS exhibited a significant difference from the control group as early as two weeks after the disease was induced. It also proved more sensitive in assessing the disease's severity than traditional motor function tests. The study identified key diagnostic features, including changes in stride, asymmetrical limb movements, and chest tremors. The top 20 behavioral features included hand/foot asymmetry, changes in stride and posture, and an increase in high-frequency chest movement.
To confirm that these behavioral indicators were not just general motor decline but specific to Parkinson's, the team applied the same analysis to a mouse model of Amyotrophic Lateral Sclerosis (ALS), also known as Lou Gehrig's disease, in collaboration with Director Lee's team at IBS. Since both Parkinson's and ALS cause motor function problems, if the APS simply reflected poor motor skills, a high score should have appeared in both diseases.
However, the analysis of the ALS animal model showed that despite a decline in motor function, the mice did not exhibit the high APS seen in the Parkinson's model. Instead, their scores remained low, and their behavioral changes were distinctly different. This demonstrates that APS is directly related to specific, characteristic changes that only appear in Parkinson's disease.
For treatment, the research team used optoRET, an optogenetics technology that precisely controls neurotrophic signals with light. This technique proved effective in the animal model, leading to smoother gait and limb movements and a reduction in tremors.
Specifically, a regimen of shining light on alternate days was found to be the most effective, and it also showed a tendency to protect dopamine-producing neurons in the brain.
Professor Won Do Heo of KAIST stated, "This is the first time in the world that a preclinical framework has been implemented that connects early diagnosis, treatment evaluation, and mechanism verification of Parkinson's disease by combining AI-based behavioral analysis with optogenetics." He added, "This lays a crucial foundation for future personalized medicine and customized treatments for patients."
The study, with Dr. Bobae Hyeon, a postdoctoral researcher at the KAIST Institute for Biological Science, as the first author, was published online in the international journal Nature Communications on August 21st. Dr. Hyeon is conducting follow-up research to advance Parkinson's cell therapy at McLean Hospital, Harvard Medical School, supported by the "Global Physician-Scientist Training Program" of the Korea Health Industry Development Institute.
This research was supported by the KAIST Global Singularity Project, the Ministry of Science and ICT/National Research Foundation of Korea, the IBS Center for Cognition and Sociality, and the Ministry of Health and Welfare/Korea Health Industry Development Institute.
Paper Title: Integrating artificial intelligence and optogenetics for Parkinson's disease diagnosis and therapeutics in male mice
DOI: https://doi.org/10.1038/s41467-025-63025-w
2025.09.22 View 3342 -
KAIST Seoul Campus Dormitory Remodeling Completed, Improving Student Housing
< President Kwang Hyung Lee, Booyoung Group Chairman Joong Keun Lee, and executives >
KAIST held a completion and donation ceremony for the newly remodeled Pajeongsa and Sojeongsa dormitories at the Seoul Campus on the 18th. The event was attended by key figures including President Kwang Hyung Lee, Booyoung Group Chairman Joong Keun Lee, and students.
Booyoung Group is a company that has consistently engaged in various social contribution activities, including housing rental, construction, and support for education and culture. With a deep interest in the field of education, the company is taking the lead in improving student welfare by enhancing university dormitory environments.
This remodeling project was carried out as part of a KRW 20 billion donation agreement signed by Booyoung Group last year to create a safe and comfortable learning environment for KAIST students.
< President Kwang Hyung Lee, Booyoung Group Chairman Joong Keun Lee, and executives >
This remodeling project is being conducted on a total of four dormitory buildings across the Daejeon and Seoul campuses. Three of these buildings, including Pajeongsa and Sojeongsa, have been completed, providing students with newly improved living spaces. The remaining one building is also expected to be completed soon.
Through this remodeling, the aging facilities of Pajeongsa and Sojeongsa on the Seoul Campus have been upgraded, including exterior construction and overall mechanical and electrical systems. The two buildings will be named "Ujeong Pajeongsa" and "Ujeong Sojeongsa," taking their names from the donor's pen name.
< Group photo of attendees at the Seoul Campus dormitory remodeling completion ceremony >
Chairman Joong Keun Lee said, "The dormitory remodeling project, which began with the hope that Korea's scientific talents would be able to devote themselves to their studies and research in a more stable home, has now come to fruition. I hope this will serve as the foundation for KAIST to develop into a world-class university for science and technology innovation." At the completion ceremony, President Kwang Hyung Lee said, "I am very happy to be able to introduce these buildings, which have been reborn through the chairman's donation. KAIST will engrave the chairman's great will in our hearts and dedicate ourselves to nurturing the world's best talent."
2025.09.18 View 2794