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KAIST Breaks Ground on 'Innovative Digital Institute of Medical Science' to Cultivate Physician-Scientists and Medical Engineers
<Groundbreaking Ceremony for the Innovative Digital Institute of Medical Science>
The success of the AI and bio-health industries depends on how many convergence-oriented talents, who understand both medicine and science/technology simultaneously, can be secured. While major global universities are accelerating the establishment of medical schools and convergence education, our university has officially commenced the construction of core infrastructure that will determine South Korea's bio-health competitiveness.
KAIST announced on February 19th that the Graduate School of Medical Science and Engineering held a groundbreaking ceremony for the ‘Innovative Digital Institute of Medical Science,’ a key infrastructure that will lead the future of the Korean bio-health industry, and has begun full-scale construction.
The Innovative Digital Institute of Medical Science, to be built at the KAIST Munji Campus, is a project designed to support the national development goal of ‘Realizing a Powerhouse in Medical AI, Pharmaceuticals, and Bio-health’ by fostering key talent and establishing an innovative startup infrastructure. A total project cost of 42.232 billion KRW will be invested through cooperation between the government, Daejeon City, and KAIST. It is being constructed with a total floor area of approximately 10,000 square meters (3,025 pyeong) and is scheduled for completion in November 2027.
Through the establishment of this institute, our university expects to create a foundation to expand the scale of physician-scientist training from the current level of about 20 per year to 50–70 per year, which accounts for approximately 50% of the national demand. Through this, we plan to establish a full-cycle support system so that convergence-type talents, who possess medical and clinical experience as well as science, technology, and AI capabilities, can grow into leading figures in the development of innovative new drugs, vaccines, and medical devices.
This talent cultivation strategy is also in line with global trends. Convergence models of science/engineering and medicine are spreading around global science and technology universities, such as the approval for the new medical school at the Hong Kong University of Science and Technology (November 2025), the merger between Tokyo Institute of Technology and Tokyo Medical and Dental University (October 2024), and the establishment and operation of the medical school at Nanyang Technological University in Singapore. This demonstrates the strategic importance of cultivating physician-scientists and medical engineers who will lead the future bio-health industry.
In contrast, the proportion of medical school graduates in Korea entering the fields of physician-scientists or medical engineers remains below 1%, leading to concerns about a decline in future bio-health competitiveness due to a shortage of manpower.
The Innovative Digital Institute of Medical Science will feature advanced research and support facilities, including an AI Precision Medicine Platform Research Center, a Data-driven Convergence Healthcare R&D Center, an Advanced Biomedical Data Analysis Center, a Digital Medical-Bio Open Lab, and open networking halls and seminar rooms.
In particular, the 6th floor, the top floor, will host the Daejeon Bio-Medical Venture Cluster. Similar to ‘LabCentral’ in Boston, USA, this is planned to be operated as an open innovation space where high-cost research equipment can be shared not only by KAIST researchers but also by researchers from government-funded research institutes in the Daedeok Innopolis and bio-medical startups, allowing them to share research results and technologies and collaborate freely.
The Innovative Digital Institute of Medical Science is expected to serve as an innovation hub that supplements the structural limitations of the Daejeon Bio Cluster, moving beyond being a simple education and research facility. Leading domestic bio companies such as Alteogen, LigaChem Bio, and Peptron are concentrated nearby, and the site is adjacent to the ‘Wonchon-dong Advanced Bio-Medical Innovation District’ being promoted by Daejeon City, providing an ecosystem where industry, academia, research, and hospitals are organically connected.
KAIST plans to use this to vitalize translational research that connects clinical demands from hospitals with basic research from the university, and to promote the development of medical AI and digital data-based technologies to continuously create success stories of physician-scientist startups such as Sovagen and Enocras.
Kwang Hyung Lee, President of KAIST, stated, “The KAIST Innovative Digital Institute of Medical Science will become a core base for the future AI digital health industry, growing science and engineering talents into physician-scientists and medical engineers. Through translational research and startups based on industry-academia-research-hospital cooperation, we will enhance national bio-health industrial competitiveness and contribute to the promotion of human health.”
<Bird’s-Eye View of the Innovative Digital Medical Science Institute>
2026.02.19 View 2195 -
KAIST Overcomes Limitations of Existing Image Sensors… Clear Colors Even Under Oblique Light
<(From Left) Ph.D candidate Chanhyung Park from Electrical Engineering, Jaehyun Jeon from Department of Physics, Professor Min Seok Jang from Electrical Engineering>
Smartphone cameras are becoming smaller, yet photos are becoming sharper. Korean researchers have elevated the limits of next-generation smartphone cameras by developing a new image sensor technology that can accurately represent colors regardless of the angle at which light enters. The team achieved this by utilizing a “metamaterial” that designs the movement of light through structures too small to be seen with the naked eye.
KAIST (President Kwang Hyung Lee) announced on the 12th of February that a research team led by Professor Min Seok Jang of the School of Electrical Engineering, in collaboration with Professor Haejun Chung’s team at Hanyang, has developed a metamaterial-based technology for image sensors that can stably separate colors even when the angle of light incidence varies.
Conventional smartphone cameras capture images by concentrating light into a small lens. However, as camera pixels become extremely small, lenses alone struggle to gather sufficient light. To address this, the Nanophotonic Color Router was introduced. Instead of concentrating light through a lens, this technology uses microscopic structures invisible to the eye to precisely separate incoming light by color. By designing the pathways through which light travels, this metamaterial-based structure accurately divides light into red (R), green (G), and blue (B).
Samsung Electronics has already demonstrated the commercialization potential of this technology by applying it to actual image sensors under the name “Nano Prism.” Theoretically, stacking multiple layers of extremely fine nanostructures enables greater light collection and more accurate color separation.
<Nanophotonic color router technology that works reliably even under oblique incidence conditions (AI-generated image)>
However, existing Nanophotonic Color Routers had limitations. While they functioned well when light entered vertically, their performance deteriorated significantly—or colors mixed—when light entered at an angle, as is common in smartphone cameras. This issue, known as the “oblique incidence problem,” has been considered a critical challenge that must be resolved for real-world product applications.
The research team first investigated the root cause of this issue. They found that previous designs were overly optimized for vertically incident light, causing performance to drop sharply even with slight changes in the angle of incidence. Since smartphone cameras receive light from various angles, maintaining performance under angular variation is essential.
Instead of manually designing the structure, the team adopted an “inverse design” approach, which allows the computer to autonomously determine the optimal structure. Through this method, they derived a color router design capable of stable color separation even when the angle of incoming light changes.
As a result, whereas previous structures nearly failed when light was tilted by about 12 degrees, the newly designed structure maintained approximately 78% optical efficiency within a ±12-degree range, demonstrating stable color separation performance. In other words, the technology reaches a level suitable for practical smartphone usage environments.
<Nanophotonic color router robust to oblique incidence>
The team further analyzed performance variations by considering factors such as the number of metamaterial layers, design conditions, and potential fabrication errors. They also systematically defined the limits of robustness against changes in the angle of incidence. This study is particularly meaningful in that it presents design criteria for color routers that reflect realistic image sensor environments.
Professor Min Seok Jang of KAIST stated, “This research is significant in that it systematically analyzes the oblique incidence problem, which has hindered the commercialization of color router technology, and proposes a clear solution direction,” adding, “The proposed design methodology can be extended beyond color routers to a wide range of metamaterial-based nanophotonic devices.”
In this study, KAIST undergraduate student Jaehyun Jeon and doctoral candidate Chanhyung Park participated as co-first authors. The research findings were published on January 27 in the international journal Advanced Optical Materials.
※ Paper title: “Inverse Design of Nanophotonic Color Router Robust to Oblique Incidence”
DOI: https://doi.org/10.1002/adom.202501697※ Authors: Jaehyun Jeon (KAIST, first author), Chanhyung Park (KAIST, first author), Doyoung Heo (KAIST), Haejun Chung (Hanyang University), Min Seok Jang (KAIST, corresponding author)
This research was supported by the Ministry of Trade, Industry & Energy (Korea Institute for Advancement of Technology, Korea Semiconductor Research Consortium) under the project “Design Technology of Meta-Optical Structures for Next-Generation Sensors,” by the Ministry of Science and ICT (National Research Foundation of Korea) under the projects “Development of Full-Color Micro LED Devices and Panels Based on Beam-Steerable High-Color-Purity Meta Color Conversion Layers” and “Development of a Real-Time Zero-Energy Argos-Eye Metasurface Network Computing with All Properties of Light,” and by the Ministry of Culture, Sports and Tourism (Korea Creative Content Agency) under the project “International Joint Research for Next-Generation Copyright Protection and Secure Content Distribution Technologies.”
2026.02.19 View 1574 -
Professor Kyung-Jin Lee of the Department of Physics Selected for the KAISTian of the Year’ Award
< Professor Kyung-Jin Lee at the ceremony >
KAIST announced on February 12th that it has selected Professor Kyung-Jin Lee from the Department of Physics as the recipient of the ‘KAISTian of the Year’ award in celebration of the university's 55th anniversary. Established in 2001, the ‘KAISTian of the Year’ award is the university’s highest honor, presented to members who have significantly enhanced KAIST's global prestige through exceptional academic and research milestones.
As the 25th recipient of this award, Professor Kyung-Jin Lee was recognized for his groundbreaking work in identifying the phenomenon of ‘Quantum Spin Pumping,’ effectively overturning 30-year-old conventional assumptions in spin transfer theory. While existing theories treated spin as a classical physical quantity, Professor Lee focused on the fact that spins within materials possess intrinsic quantum properties, much like electrons. To verify this, he researched Iron-Rhodium (FeRh), a magnetic material where spin magnitude changes abruptly under specific conditions. He became the first to observe a quantum transition in which the spin magnitude of Rhodium (Rh) atoms increased suddenly rather than gradually, theorizing that this very change serves as a new mechanism for inducing electron movement. Experimental data showed that this effect is more than 10 times greater than what previous theories had predicted. This achievement is hailed as a major breakthrough that redefines the core premises of spin transfer theory and provides a vital theoretical foundation for next-generation ultra-low-power magnetic memory and quantum information devices. The study gained worldwide acclaim following its publication in the journal ‘Nature’ last year.
The anniversary ceremony also honored 58 faculty members for their excellence in education, research, and international cooperation. Professor Wonho Choe of the Department of Nuclear and Quantum Engineering received the ‘Academic Achievement Grand Prize’ for his world-first identification of physical phenomena in low-temperature atmospheric pressure plasma and his contributions to medical and space technologies. The ‘Creative Teaching Grand Prize’ went to Professor Hyung-soo Kim of the Department of Mechanical Engineering for his innovative sports fluid mechanics curriculum. Professor Park Bum-soon of the Graduate School of Science and Technology Policy was awarded the ‘Outstanding Teaching Grand Prize’ for his interdisciplinary ‘Anthropocene Humanities’ courses that bridge science, art, and policy.
Furthermore, Professor Hyeon-Min Bae of the School of Electrical Engineering received the ‘Distinguished Service Grand Prize’ for his leadership in accelerating deep-tech prototyping and fostering a robust startup ecosystem. Professor Shin-Hyun Kim of the Department of Chemical and Biomolecular Engineering was honored with the ‘International Cooperation Grand Prize’ for establishing the T2KN consortium between Korea, Japan, China, and ASEAN, facilitating global academic exchange for over 120 students.
KAIST President Kwang-Hyung Lee stated, “The true spirit of KAIST lies in the dedication of our members who venture into uncharted territories and strive to transcend existing limits. I hope today serves as a moment for all our members to share in the joy and celebrate the remarkable achievements of our awardees.”
2026.02.12 View 1283 -
KAIST NYU Host AI Governance Summit in New York
< KAIST Professor Kyung Ryul Park delivering a keynote speech >
KAIST announced on February 9th that the KAIST-NYU AI and Digital Governance Summit, co-hosted with New York University (NYU), was held at NYU in New York from February 6 to 7 (local time). Amid the rapidly expanding impact of Artificial Intelligence (AI) across society, this summit was designed to combine private consensus meetings with public discussions to seek practical AI governance solutions that harmonize technological innovation with safety and ethical responsibility.
The summit was attended by 60 global AI governance leaders representing academia, industry, and civil society, including NYU professors Matthew Liao and David Chalmers, Victoria Nash (Director of the Oxford Internet Institute), Professor Vincent Conitzer (Carnegie Mellon University), Iason Gabriel (Principal Scientist at Google DeepMind), and Philip Goldberg (former U.S. Ambassador to South Korea). In particular, the public discussion on the second day drew high interest, with approximately 450 audience members in attendance.
< Brad Carson, U.S. Representative for Responsible Innovation and former U.S. Congressman, delivering a keynote speech >
This event garnered attention as an 'experimental consensus model' aimed at deriving an actionable AI governance framework beyond a simple forum. KAIST’s Global Center for Open Development with Evidence-based Strategies (G-CODEs) and the NYU Center for Bioethics had formed three working groups—Governance Requirements, Institutional Architecture, and Implementation Pathways—since last December to conduct preliminary discussions. At the New York site, practice-oriented recommendations were derived through intensive consensus-style discussions and voting.
In the Governance Requirements session, the need for enhanced oversight and monitoring of high-risk AI systems was discussed. In the ‘Institutional Architecture’ session, principles for designing AI oversight bodies were reviewed, referencing existing high-risk technology oversight models such as the FDA, IRB, and FAA. In the Implementation Pathways session, short-term governance tools and corporate responsibility standards that could be applied even during the current gap in international regulation were addressed as key issues.
Major global Big Tech experts from Meta, Google DeepMind, IBM, Amazon, Anthropic, TikTok and Hugging Face participated in the summit. From KAIST, researchers including Prof. So Young Kim , Prof. Kyung Ryul Park, and Prof. Hyungjun Kim shared Korea’s research achievements in AI governance.his event was conducted with support from the Korea Foundation’s (KF) international collaborative research program.
Professor Kyung Ryul Park of KAIST stated, “This summit was a meaningful attempt to expand AI governance beyond technical regulation into a matter of international cooperation and institutional design. Through the cooperation between KAIST and NYU, we will build a foundation for Korea to lead global AI governance discussions.”
KAIST President Kwang Hyung Lee remarked, “The importance of governance discussions for responsible AI innovation is growing. KAIST will continue to lead interdisciplinary research and policy discussions in the field of AI governance through international partnerships.”
< Sebastien Krier, AI Policy Lead at Google DeepMind, speaking >
2026.02.09 View 1983 -
Capturing the Instant of Electrical Switching, Paving the Way for Next-Gen Memory Material Innovation
< (From left) Ph.D candidate Changhwan Kim, Ph.D candidate Seunghwan Kim , Ph.D candidate Namwook Hur, Professor Joonki Suh, Ph. D candidate Youngseok Cho>
As artificial intelligence advances, computers demand faster and more efficient memory. The key to ultra-high-speed, low-power semiconductors lies in the "switching" principle—the mechanism by which memory materials turn electricity on and off. A South Korean research team has successfully captured the elusive moment of switching and its internal operational principles by momentarily melting and freezing materials within a nanoscale electronic device. This study provides a foundational blueprint for designing next-generation memory materials that are faster and consume less power based on fundamental principles.
On February 8th, the research team led by Professor Joonki Suh from our department (Chemical and Biomolecular Engineering), in collaboration with Professor Tae-Hoon Lee’s team from Kyungpook National University, announced the development of an experimental technique capable of real-time monitoring of electrical switching processes and phase changes within nano-devices—phenomena that were previously difficult to observe.
To verify the electrical switching, the team applied a method of instantaneous melting followed by rapid cooling (quenching). Through this, they succeeded in stably implementing amorphous tellurium (a-Te)—a state where tellurium is disordered like glass—within a nano-device much smaller than a human hair. Tellurium is typically sensitive to heat and changes properties easily when current is applied; however, in its amorphous state, it is garnering significant attention as a core material for next-generation memory due to its speed and energy efficiency. *Tellurium (Te): A metalloid element possessing properties of both metals and non-metals.
< Illustration of the experiment involving instantaneous melting and freezing in a memory electronic device (AI-generated image) >
Through this study, the team specifically identified the threshold voltage and thermal conditions at which switching begins, as well as the segments where energy loss occurs. Based on these findings, they observed stable and high-speed switching even while reducing heat generation. This enables "principle-based" memory material design, allowing researchers to understand exactly why and when electricity starts to flow.
The results confirmed that microscopic defects within amorphous tellurium play a crucial role in electrical conduction. When the voltage exceeds a certain threshold, the corresponding current does not rise all at once; instead, it follows a two-step switching process: initially, a rapid current increase along the defects occurs primarily during the abrupt electrical switching, followed by heat accumulation that causes the material to melt.
Furthermore, the team successfully implemented a "self-oscillation" phenomenon—where voltage spontaneously increases and decreases—by conducting experiments that maintained the amorphous state without excessive current flow. This demonstrates that stable electrical switching is possible using only the single element of tellurium, without the need for complex material combinations.
< Electrical characteristics of amorphous tellurium created through rapid cooling from a liquid state within an electronic device >
This research is a significant achievement as it implements amorphous tellurium—a next-generation memory material—within an actual electronic device and systematically elucidates the fundamental principles of electrical switching. These findings are expected to serve as essential guidelines for designing semiconductor materials to realize faster and more energy-efficient memory in the future.
"This is the first study to implement amorphous tellurium in a real-world device environment and clarify the switching mechanism," said Professor Joonki Suh. "It sets a new standard for research into next-generation memory and switching materials."
The study, with Namwook Hur as the first author and Seunghwan Kim as the second author, and Professor Joonki Suh (KAIST) as the corresponding author, was published online on January 13th in the international academic journal Nature Communications.
Paper Title: On-device cryogenic quenching enables robust amorphous tellurium for threshold switching
DOI: 10.1038/s41467-025-68223-0
Meanwhile, this research was supported by the National Research Foundation of Korea (NRF) through the PIM (Processor-in-Memory) AI Semiconductor Core Technology Development Project, the Excellent Young Researcher Program funded by the Ministry of Science and ICT, and Samsung Electronics.
2026.02.09 View 1214 -
Distinguished Professor Sang Yup Lee Receives the AIBN Translational Research Award from the University of Queensland, Australia
<Distinguished Professor Sang Yup Lee immediately after receiving the AIBN Medal (AIBN Translational Research Award)>
KAIST announced on February 9th that Sang Yup Lee, Distinguished Professor of Chemical and Biomolecular Engineering (and Vice President for Research), was presented with the AIBN Medal (AIBN Translational Research Award) on February 3rd (local time) at the Australian Institute for Bioengineering and Nanotechnology (AIBN), located at the University of Queensland (UQ) in Brisbane, Australia.
The AIBN Medal is awarded to recognize translational research achievements that extend biotechnological research into industrial and social value. It is often described as an award for "achievements that do not let research end in the laboratory." Rather than focusing solely on the number of papers or citations, the award prioritizes industrial applicability, technology dissemination, international cooperation, and social impact. It is a symbolic global award in the field of translational research presented by AIBN, a world-class research hub for synthetic biology, metabolic engineering, and biomanufacturing. The medal was personally presented by Professor Sue Harrison, Deputy Vice-Chancellor (Research) at the University of Queensland.
<Professor Sue Harrison, Deputy Vice-Chancellor of UQ, personally presenting the medal>
During his commemorative lecture, Distinguished Professor Sang Yup Lee spoke on the topic of "Systems Metabolic Engineering for Chemical Production," presenting a future vision for sustainable biomanufacturing and synthetic biology technologies.
<Vice President for Research giving the award lecture on Systems Metabolic Engineering for Chemical Production>
For approximately 32 years at KAIST, Distinguished Professor Sang Yup Lee has pioneered research in metabolic engineering, synthetic biology, and systems biotechnology. To date, he has accumulated world-class research achievements, including 798 papers in international journals, 868 patents (registered and filed), over 3,000 presentations at domestic and international conferences, and approximately 690 keynote and invited lectures.
Furthermore, he has contributed to establishing the academic framework of the field through numerous publications, such as Metabolic Engineering, Systems Biology and Biotechnology of Escherichia coli, and Systems Metabolic Engineering.
In its official announcement, AIBN stated the background for the award: "Distinguished Professor Sang Yup Lee is a world-renowned scholar in the field of systems metabolic engineering who has made continuous and meaningful contributions not only to academic influence but also to the University of Queensland and the Australian research ecosystem." Notably, Professor Lee played a key role in establishing research strategies during the early days of AIBN (2006–2007). His collaboration has since expanded from sugar-based biomanufacturing to synthetic aviation fuels and waste-gas fermentation-based bioprocessing.
This collaboration led to global joint research with entities such as Amyris (a US-based bio-chemical and fuel company), UC Berkeley, LanzaTech (a global leader in waste-gas fermentation), and SkyNRG (a Dutch company leading the development of Sustainable Aviation Fuel, SAF). These efforts served as a vital foundation for the University of Queensland to become Australia’s representative research hub in synthetic biology and systems metabolic engineering.
Professor Lee is an International Member of the National Academy of Sciences (NAS) and the National Academy of Engineering (NAE) in the US, a Foreign Member of The Royal Society in the UK, and a Foreign Member of the Chinese Academy of Engineering. He also serves as the Co-Chair of the Global Future Council on Biotechnology for the World Economic Forum (WEF), continuing his international activities across academia, policy, and industry.
In his acceptance speech, Vice President Sang Yup Lee remarked, "I believe this AIBN Medal is not just an individual achievement, but the fruit of long-standing cooperation between researchers from KAIST, UQ, and Korea and Australia. It is a meaningful award that demonstrates how research in systems metabolic engineering and synthetic biology can lead to solutions for sustainable industry and social issues." He added, "Moving forward, I will continue to strengthen global research cooperation and translational research to ensure that biotechnology provides tangible value to human life."
KAIST President Kwang Hyung Lee commented, "This award goes beyond the personal excellence of Distinguished Professor Sang Yup Lee; it is a case where KAIST’s research capabilities and international cooperation strategies have been recognized globally. KAIST will continue to lead translational research where results spread to industry and society, contributing to the sustainable bio-industry and the resolution of global challenges through cooperation with global partners."
Meanwhile, Distinguished Professor Sang Yup Lee was originally named the inaugural recipient of the 1st AIBN Medal in 2016. However, the official ceremony was delayed due to scheduling conflicts and the COVID-19 pandemic, leading to his attendance and formal receipt of the award nearly 10 years later.
2026.02.09 View 1477 -
KAIST Develops Cap-Like OLED Wearable to Prevent Hair Loss, Replacing Bulky Helmet Devices
<Professor Kyung Cheol Choi, (Upper Left) Dr. Eun Hae Cho>
A new solution that could overcome the limitations of conventional hair-loss treatments is emerging. Heavy and rigid helmet-type phototherapy devices may soon become a thing of the past. A joint research team has developed a hat-like, wearable OLED-based phototherapy device and demonstrated that it can suppress hair-follicle cell aging by up to 92%, a key factor in hair-loss progression.
KAIST (President Kwang Hyung Lee) announced on the 1st of February that a research team led by Professor Kyung Cheol Choi of the School of Electrical Engineering, in collaboration with Professor Yun Chi’s group at the Hong Kong University of Science and Technology, has developed a non-invasive* hair-loss treatment technology using a textile-like, flexible wearable platform integrated with specially designed OLED light sources.*Non-invasive treatment refers to therapies that do not involve skin incisions or direct physical damage to the body.
Although drug-based treatments for hair loss have been known to be effective, concerns over side effects from long-term use have driven interest in safer alternatives such as phototherapy. However, existing phototherapy devices for hair loss are typically bulky, rigid helmet-type systems, limiting their use to indoor environments. Moreover, because they rely on point light sources such as LEDs or lasers, it has been difficult to deliver uniform light irradiation across the entire scalp.
To address these challenges, the researchers replaced point light sources with area-emitting OLEDs, which emit light uniformly over a wide surface. In particular, they integrated near-infrared (NIR) OLEDs into a soft, fabric-like material that can be worn as a cap. This design allows the light source to naturally conform to the contours of the scalp, delivering even optical stimulation over the entire scalp.
Beyond wearable design, the study focused on suppressing hair-follicle cell aging, a central driver of hair-loss progression. The key achievement of this work lies not only in realizing a wearable device, but also in precisely tailoring the wavelength of light to maximize therapeutic efficacy.
Recognizing that cellular responses vary depending on light wavelength, the team extended wavelength-control techniques originally developed for display OLEDs to therapeutic applications. As a result, they fabricated customized OLEDs that selectively emit near-infrared light in the 730–740 nm range, which is optimal for activating dermal papilla cells—critical cells located at the base of hair follicles that regulate hair growth.
The effectiveness of the developed NIR OLEDs was validated through experiments using human dermal papilla cells (hDPCs). Cellular aging analysis showed that NIR OLED irradiation suppressed cell aging by approximately 92% compared with the control group, outperforming conventional red-light irradiation conditions.
< Schematic diagram of phototherapy using a textile-based near-infrared OLED cap >
First author Dr. Eun Hae Cho commented, “Instead of rigid, helmet-type point-light devices, we propose a wearable phototherapy platform that can be used in daily life by implementing soft, textile-based OLEDs in a cap form. A key outcome of this study is demonstrating that precisely engineered light wavelengths can effectively suppress hair-follicle cell aging.”
Professor Kyung Cheol Choi added, “Because OLEDs are thin and flexible, they can closely conform to the curved surface of the scalp, delivering uniform light stimulation across the entire area. Going forward, we plan to verify safety and efficacy through preclinical studies and progressively evaluate the potential for real therapeutic applications.”
This research was led by Dr. Eun Hae Cho of the KAIST School of Electrical Engineering as first author and was published online on January 10 in the international journal Nature Communications.
※ Paper title: “Wearable Textile-Based Phototherapy Platform With Customized NIR OLEDs Toward Non-Invasive Hair Loss Treatment", DOI: https://doi.org/10.1038/s41467-025-68258-3, Co-authors: Eun Hae Cho, Jingi An, Yun Chi, Kyung Cheol Choi
< Prototype of a textile-based near-infrared OLED and its phototherapeutic efficacy >
This research was conducted with the support of the Ministry of Science and ICT through the National Research Foundation of Korea (NRF) under the National R&D Program (Future-Oriented R&D Convergence Science and Technology Development Program (Bridge Convergence Research): Development of a skin patch for wound treatment integrating bio-tissue adhesive patches with drug delivery and phototherapy OLED therapy, the Technology Innovation Program supported by the Ministry of Trade, Industry and Energy (development of substrate materials stretchable by more than 50% for stretchable displays), and the BK21 FOUR Program of the Ministry of Science and ICT (Connected AI Education & Research Program for Industry and Society Innovation, School of Electrical Engineering, KAIST). (2021M3C1C3097646, 20017569, 4120200113769)
2026.02.04 View 2817 -
Reading the Optical Fingerprint of Materials in Real-Time with AI
< (From Left) KAIST Dr. Jongchan Kim, Professor Sanghoo Park >
Just as every person has a unique fingerprint, every material has its own unique ‘optical fingerprint.’ Spectroscopy, which has identified materials without contact in fields ranging from semiconductor processes to environmental monitoring, disease diagnosis, and space research, has been called the ‘eyes of science.’ A KAIST research team has implemented spectroscopic analysis, which previously relied on the experience of experts, into AI-based automatic and real-time interpretation technology, greatly expanding its applicability in various industrial fields such as semiconductors, environment, and medicine.
The research team led by Professor Sanghoo Park of our university's Department of Nuclear and Quantum Engineering announced on the 3rd that they have developed ‘AI-based deep spectral interpretation technology’ that allows artificial intelligence to automatically interpret various spectral data in real-time, overcoming limitations such as noise, contamination, defects, and complex overlapping signals.
A spectrum is a graph that spreads out light emitted or absorbed by a material like a rainbow. Existing spectroscopic analysis had to manually analyze signals appearing as numbers in this spectrum by comparing them one by one with well-known reference data. Instead of this method, the research team enabled the artificial intelligence to recognize the entire spectrum as a single ‘image’ and learn its patterns.
< Deep learning-based spectrum technology >
As a result, even in situations where noise was mixed in the data or some parts were lost, the AI accurately identified material information as if it were recognizing an object in a photo. Furthermore, it equipped a function to self-check whether the prediction results are scientifically valid, significantly increasing the reliability of the analysis.
The research team verified this technology by applying it to absorption spectroscopy data widely used in atmospheric and plasma chemistry. As a result, they succeeded in predicting the concentrations of eight chemical substances, including ozone and nitrogen oxides, with very high accuracy even among complexly mixed signals. It was not only more accurate than existing manual analysis but also showed stable performance even in environments with poor data quality.
This research is expected to be a turning point in converting vast amounts of spectroscopic data, which were previously discarded due to the difficulty of analysis, into ‘immediately usable information.’ In particular, it has high potential for use in various high-tech industrial fields, such as improving yield in semiconductor plasma processes, stable control of nuclear fusion plasma, environmental monitoring in smart cities, and non-contact disease diagnosis.
< Research Image >
Professor Sanghoo Park said, “This technology is an achievement that significantly lowers the entry barrier for spectroscopic data analysis, which used to rely on the experience of experts,” and added, “It can be immediately applied to overall industries requiring spectral analysis, such as environmental monitoring, healthcare, and plasma diagnosis.”
In this study, doctoral students Jongchan Kim and Seong-Cheol Huh participated as co-first authors, and Jin Hee Bae and Su-Jin Shin also contributed to the research. The results were published online on January 12th in the prestigious international academic journal in the field of measurement and analytical chemistry, ‘Sensors and Actuators B: Chemical.’
※ Paper title: Deep spectral deconvolution for image-based broadband spectral data analysis DOI: https://doi.org/10.1016/j.snb.2025.139369
Meanwhile, this research was conducted with support from the Ministry of Science and ICT’s Global TOP Strategic Research Group Support Program, the KAIST Leap Research Project, and the Korea Institute of Materials Science (KIMS).
2026.02.03 View 1089 -
KAIST Team Wins Grand Prize at Kakao AI Incubation Project
<(From Left) Professor Jongse Park, Professor youngjin Kwon, Professor Jaehyuk Huh, Professor Knunle Olukotun>
Currently, Large Language Model (LLM) services like ChatGPT rely heavily on expensive GPU servers. This structure faces significant limitations, as costs and power consumption skyrocket as service scales increase. Researchers at KAIST have developed a next-generation AI infrastructure technology to address these challenges.
KAIST announced on January 30th that the ‘AnyBridge AI’ team, led by Professor Jongse Park from the School of Computing, has developed a next-generation AI infrastructure software. This software allows for efficient LLM services by integrating various AI accelerators instead of relying solely on GPUs. The technology won the Grand Prize at the "4 ISTs (Science & Tech Institutes) × Kakao AI Incubation Project" hosted by Kakao.
This project is a joint industry-academic collaboration between Kakao and the four major science and technology institutes (KAIST, GIST, DGIST, and UNIST). It selected outstanding teams by evaluating the technical prowess and business viability of preliminary startup teams based on AI technology. The Grand Prize winning team receives a total of 20 million KRW in prize money and up to 35 million KRW in Kakao Cloud credits.
AnyBridge AI is a technical startup team led by Professor Jongse Park (CEO), with Professors Youngjin Kwon and Jaehyuk Huh from KAIST's School of Computing participating. Based on research achievements in AI systems and computer architecture, the team aims to develop technology applicable to actual industrial sites. Furthermore, Professor Kunle Olukotun of Stanford University—co-founder of the Silicon Valley AI semiconductor startup SambaNova—is participating as an advisor to push for global technology and business expansion.
The AnyBridge team noted that most current LLM services are dependent on expensive GPU infrastructure, leading to structural limits where operating costs and power usage surge as services scale. The researchers analyzed that the root cause of this issue lies not in the performance of specific hardware, but in the absence of a system software layer capable of efficiently connecting and operating various AI accelerators, such as NPUs (AI-specialized chips) and PIMs (next-gen chips that process AI within memory), alongside GPUs.
<Technical diagram of AnyBridge: Enhancing LLM performance by flexibly utilizing various AI accelerators>
In response, the AnyBridge team proposed an integrated software stack that can service LLMs across the same interface and runtime environment, regardless of the accelerator type. Specifically, they received high praise for pointing out the limitations of existing GPU-centric LLM serving structures and presenting a "Multi-Accelerator LLM Serving Runtime Software" as their core technology.
This technology enables the implementation of a flexible AI infrastructure where the most suitable AI accelerator can be selected and combined based on the task's characteristics, without being tied to a specific vendor or hardware. This is evaluated as a major advantage that can reduce costs and power consumption while significantly increasing scalability for LLM services.
<Illustration of the Multi-Accelerator LLM Service Platform - AI-generated image>
Additionally, based on years of accumulated research in LLM serving system simulation, the AnyBridge team possesses a research foundation that can pre-verify various hardware/software design combinations without building a large-scale physical infrastructure. This point demonstrated both the technical maturity and the industrial feasibility of their work.
"This award is a result of recognizing the necessity of system software that integrates various AI accelerators, moving beyond the limits of GPU-centric AI infrastructure," said Professor Jongse Park. He added, "It is meaningful that we could expand our research results into industrial fields and entrepreneurship. We will continue to develop this into a core technology for next-generation LLM serving infrastructure through cooperation with industrial partners."
This award is seen as a prime example of KAIST's research moving beyond academic papers toward next-generation AI infrastructure technology and startups. AnyBridge AI plans to advance and verify its technology through future collaborations with Kakao and related industrial partners.
<Photo of the Grand Prize ceremony: Left - Kakao Investment CEO Do-young Kim; Right - KAIST Prof. Jongse Park>
2026.01.30 View 1984 -
World-Renowned Masters Rodin and Chagall Meet at KAIST Museum
KAIST announced that its museum has received a donation of works by world-renowned masters Auguste Rodin and Marc Chagall from an anonymous donor, and has opened a permanent exhibition starting on the 29th. This donation is expected to not only cultivate the cultural and artistic sensibilities of the KAIST community but also contribute to the qualitative expansion of the museum's permanent collection.
The donation was made possible through the wishes of a donor who chose to remain anonymous. The donor expressed, "I hope that the members of KAIST will expand their sensibilities and imagination through art, beyond their scientific and technological research. I want the KAIST Museum to become a cultural landmark on campus and a space that provides inspiration to students."
The donated pieces consist of one bronze sculpture by Auguste Rodin, often called the "Saint of Sculpture," and one lithograph by Marc Chagall, a master of 20th-century modern art.
Rodin’s <Study for Adam Near a Column> is a preparatory piece created while conceiving "Adam," a figure featured in his immortal masterpiece, The Gates of Hell. Based on a plaster mold created around 1912 during Rodin's lifetime, this is the fourth (4/12) of twelve official casts produced posthumously by the Musée Rodin in France. It captures the essence of Rodin’s sculptural art, delicately expressing inner human agony through muscular detail and a twisted posture.
<Rodin’s Study for Adam Near a Column (45-degree side view, post-installation)]
Chagall’s <Circus with a Yellow Clown> is a lithograph produced in 1967 at the Mourlot lithography studio in France. Throughout his life, Chagall used the theme of the "circus" to express the joys and sorrows of humanity and a surreal world of dreams. This work combines the dynamism of circus performers with a fantastical atmosphere through vibrant colors and a free-form composition, capturing a unique worldview akin to a piece of poetry. It is the 104th piece of a total of 150 (104/150) and is regarded as a masterpiece that maximizes Chagall's signature lyrical imagination.
<Chagall’s Circus with a Yellow Clown (unframed)>
KAIST President Kwang-Hyung Lee stated, "It is very meaningful to acquire masterpieces of such high value in global art history. Through these works, which contain diverse perspectives on humanity and the world, I look forward to the KAIST Museum establishing itself as a cultural space where intelligence and emotion coexist."
The donated works by Rodin and Chagall will be on permanent display at the KAIST Museum starting today. While currently open to students and the general public, the museum plans to expand its public accessibility through special exhibitions and educational programs starting in April.
2026.01.30 View 880 -
AI Enters the Experienced Hire Era... Teaching Learned Knowledge with Ease
< (From left) KAIST Professor Hyunwoo J. Kim, Postdoctoral Researcher Sanghyeok Lee, M.S candidate Taehoon Song, Korea University Ph.D candidate Jihwan Park >
How inconvenient would it be if you had to manually transfer every contact and photo from scratch every time you switched to a new smartphone? Current Artificial Intelligence (AI) models face a similar predicament. Whenever a superior new AI model—such as a new version of ChatGPT—emerges, it has to be retrained with massive amounts of data and at a high cost to acquire specialized knowledge in specific fields. A Korean research team has developed a "knowledge transplantation" technology between AI models that can resolve this inefficiency.
KAIST announced on January 27th that a research team led by Professor Hyunwoo J. Kim from the School of Computing, in collaboration with a research team from Korea University, has developed a new technology capable of effectively "transplanting" learned knowledge between different AI models.
Recently, Vision-Language Models (VLM), which understand both images and text simultaneously, have been evolving rapidly. These are easily understood as multimodal AIs, like ChatGPT, which can provide explanations when a user shows them a photo and asks a question. These models have the advantage of adapting relatively quickly to new fields using small amounts of data by pre-learning large-scale image and language data.
However, the need to repeat this "adaptation process" from scratch every time a new AI model is released has been pointed out as a major inefficiency. Existing adaptation techniques also faced limitations: they were difficult to use if the model structure changed even slightly, or they significantly increased memory and computational costs because multiple models had to be used simultaneously.
To solve these problems, the research team proposed "TransMiter," a transferable adaptation technique that allows learned knowledge to be reused regardless of the model's structure or size. The core of this technology is directly transferring the "adaptation experience" accumulated by one AI as it learns to another AI model.
< TransMiter: A transferable adaptation technique reusable regardless of model structure, size, etc. >
The researchers' technology does not overhaul the complex internal structure of the AI; instead, it adopts a method of passing on "know-how" learned by observing only the prediction results (output) to another AI. Even if the AI models have different architectures, if the know-how learned by one AI is organized based on the answers given to the same questions, another AI can utilize that knowledge immediately. Consequently, there is no need to undergo the complex and time-consuming retraining process, and there is almost no slowdown in speed.
This study is highly significant as it is the first to prove that AI adaptation knowledge—previously considered almost impossible to reuse if model structures or sizes differed—can be precisely transplanted regardless of the model type. This is expected to not only reduce repetitive learning costs but also be utilized as a so-called "knowledge patch" technology that updates Large Language Models (LLMs) in real-time according to specific needs.
Professor Hyunwoo J. Kim explained, "By extending this research, we can significantly reduce the cost of post-training that had to be performed repeatedly whenever a rapidly evolving hyper-scale language model appears. It will enable 'model patches' that easily add expertise in specific fields."
The study involved Taehoon Song (Master's student, KAIST School of Computing), Sanghyeok Lee (Postdoctoral researcher), and Jihwan Park (Doctoral student, Korea University) as co-authors, with Professor Hyunwoo J. Kim serving as the corresponding author. The research results were accepted for oral presentation (4.6% acceptance rate as of 2025) at AAAI 2026 (Association for the Advancement of Artificial Intelligence), the most prestigious international conference in the field of AI, and were presented on January 25th.
Paper Title: Transferable Model-agnostic Vision-Language Model Adaptation for Efficient Weak-to-Strong Generalization
DOI: https://doi.org/10.48550/arXiv.2508.08604
Meanwhile, Professor Hyunwoo J. Kim's laboratory presented a total of three papers at the conference, including this paper and "TabFlash," a technology developed in collaboration with Google Cloud AI to enhance the understanding of tables within documents.
2026.01.27 View 2071 -
Discovery of a Switch to Halt Adipocyte Generation
< (From left) Dr. Ju-Gyeong Kang, Ph.D candidate TaeJun Seol, Professor Dae-Sik Lim >
Metabolic diseases such as obesity, fatty liver, and insulin resistance are rapidly increasing worldwide, but fundamental methods to regulate the process of fat formation remain limited. In particular, once adipocytes (fat cells) are formed, they are difficult to reduce, making treatment challenging. Amidst this, a research team from our university has discovered the existence of a ‘switch’ that prevents fat formation. This discovery elucidates how an ‘epigenetic switch’—which regulates gene activity without altering the DNA sequence itself—functions during the process of adipogenesis, presenting new possibilities for the precise control of obesity and metabolic diseases in the future.
The research team, led by Professor Dae-Sik Lim and Professor Ju-Gyeong Kang from KAIST’s Department of Biological Sciences, announced on January 25th that they have identified ‘YAP/TAZ,’ key regulators of the Hippo signaling pathway*, as playing the role of an ‘epigenetic differentiation inhibition switch’ during the process of adipocyte differentiation**. The team proposed a new mechanism in which YAP/TAZ extensively inhibits the activation of genes responsible for adipocyte formation through its downstream target, ‘VGLL3.’ *Hippo signaling pathway: A cellular control system that regulates when cells grow, stop dividing, and differentiate. **Adipocyte differentiation: The process by which preadipocytes (or stem cells) transform into mature adipocytes.
Cell differentiation is not a simple matter of a single gene turning on or off; it is a complex, organic process involving multiple genes and DNA regulatory regions. The research team tracked the entire process of preadipocytes* differentiating into adipocytes using Next-Generation Sequencing (NGS), which allows for the simultaneous analysis of gene expression changes and epigenetic modifications. *Preadipocyte: A developing intermediate-stage cell whose direction as to which cell it will become has already been determined.
As a result, they confirmed that under conditions where YAP/TAZ is activated, the genetic program that establishes adipocyte identity fails to operate, and the overall adipocyte differentiation network—centered around PPARγ*—is suppressed. *PPARγ: The ‘metabolic master switch’ regulator that controls energy storage and utilization in the body.
Specifically, through single-cell analysis of adipose tissue, the research team identified VGLL3 as a novel target gene of YAP/TAZ. While it was previously known that YAP/TAZ directly binds to and inhibits PPARγ, this study revealed that VGLL3 indirectly controls the entire adipocyte differentiation program by suppressing ‘enhancers,’ which are the DNA regulatory regions of adipocyte genes. This signifies that the Hippo signaling pathway plays a crucial role in regulating the core timing that determines when and how robustly fat cells are created.
Dysfunction of adipose tissue is deeply linked to various metabolic diseases such as obesity, insulin resistance, and fatty liver. The research team expects that further studies on how the YAP/TAZ–VGLL3–PPARγ axis regulatory principle involves adipocyte formation and functional abnormalities will provide new clues for regulating or treating metabolic diseases.
< Schematic Diagram of Adipocyte Gene Regulation >
Professor Dae-Sik Lim stated, “This study is the first to establish that adipocyte differentiation is precisely controlled at the epigenetic level, beyond simple gene regulation. It has laid an important foundation for a more sophisticated understanding of the mechanisms behind adipocyte identity changes and, in the long term, for developing personalized treatment strategies for patients with metabolic diseases.”
This research, with Ph.D. student TaeJun Seol and Dr. Ju-Gyeong Kang as co-first authors, was published on January 14th in the world-renowned international academic journal, Science Advances. ※ Paper Title: YAP/TAZ-VGLL3 governs adipocyte fate via epigenetic reprogramming of PPARγ and its target enhancers, DOI: 10.1126/sciadv.aea7235
Meanwhile, this research was conducted with support from the Leader Researcher Support Program and the Overseas Excellent Scientist Recruitment Program of the National Research Foundation of Korea, funded by the Ministry of Science and ICT.
2026.01.26 View 1658