%73%63%69%65%6e%63%65
-
KAIST Professor Jaekyung Kim Selected as One of Asia's 12 Next-Generation Scientists
KAIST (President Choongsik Bae) announced on September 4 that Professor Jaekyung Kim from the Department of Biological Sciences has been selected as a Fellow of the “2026 Asian Young Scientist Fellowship (AYSF),” a program that supports promising young scientists across Asia.
The Asian Young Scientist Fellowship (AYSF) is a privately funded research fellowship in Asia, established to support young scientists in carrying out creative and challenging research. Since selecting its first cohort of Fellows in 2023, the AYSF selects 12 early-career researchers each year across the fundamental science disciplines of life sciences, physical sciences, and mathematics and computer science. Each selected Fellow receives a total of $100,000 USD over two years to support their research.
The AYSF does more than support young scientists across individual academic disciplines —it actively encourages interdisciplinary research that transcends traditional disciplinary boundaries to open new research directions. It places particular emphasis on supporting young scientists at the critical stage of launching their careers as independent researchers, helping them develop creative ideas and pioneer new areas of research.
Candidates are nominated from among full-time researchers at universities or research institutions in Asia who are within 10 years of completing their terminal degree (Ph.D./M.D.). Among the nominated candidates, a Selection Committee composed of scientists from Asia and around the world conducts a comprehensive evaluation of each candidate’s research achievements and future research potential.
This year, 12 early-career researchers in Asia were selected as 2026 Fellows Professor Kim was named a Fellow in the life sciences category, alongside Professor Mikyung Shin of Sungkyunkwan University, making them the two Fellows affiliated with Korean universities. Previous AYS Fellows from Korea include Professor Kyeongsu Choi of the Korea Institute for Advanced Study (KIAS) in 2023; Professor Jiheong Kang of Seoul National University in 2024; and Professor Seongjun Park of Seoul National University and Professor In-Jee Jeong of KIAS in 2025.
Professor Kim studies how the brain organizes experiences and information into memories during sleep. Using a systems- and computational-neuroscience approach, he focuses on memory consolidation—the process by which information learned during the day becomes stabilized into long-term memory during sleep—and the neural mechanisms involved. He also analyzes biological signals related to dreaming and investigates how sleep affects higher cognitive functions such as creative thinking.
Professor Kim received his bachelor's degree from Hanyang University and his Ph.D. from KAIST, and completed postdoctoral research at the University of California, San Francisco (UCSF) and the San Francisco VA Medical Center. He joined the KAIST Department of Biological Sciences in 2023 and currently leads the Neural Processing Lab.
The 2026 AYS Fellows will attend the 2026 AYSF Annual Conference on November 9, 2026, at the University of Hong Kong to showcase their research work and innovative ideas.
2026.09.04 View 390 -
KAIST and Caltech Build Global Co-Mentoring Model for Next-Gen Researchers
KAIST is building a new global cooperation model with the Caltech — a world-renowned U.S. research institution — that goes beyond joint research to jointly nurture next-generation researchers as well.
KAIST, led by President Choongsik Bae, is holding the 1st KAIST-Caltech Joint Workshop on Molecular Science and Chemical Innovation with the Caltech in the United States from September 1 to 2.
The workshop is designed not merely to share the latest research achievements in advanced molecular science and future chemical technologies, but to build a sustainable framework of cooperation that links joint research and talent development, extending even to the shared use of research facilities.
At this workshop, particular attention is being given to establishing and operating the KAIST-Caltech Global Research Fellow (KCGRF) platform, a joint mentoring program for postdoctoral researchers.
KCGRF is a program in which faculty members from both institutions identify joint research topics and jointly select and mentor postdoctoral researchers. By enabling participating researchers to experience the research environments of both KAIST and Caltech, the program aims to nurture next-generation scientists with strong international research capabilities.
This joint initiative represents a concrete practice model of KAIST's Global Connect strategy. The vision goes beyond simple exchange with overseas universities. It aims to realize a collaborative internationalization, in which talent, knowledge, and research ideas flow between the two institutions, leading to joint research and the joint training of next-generation researchers.
Caltech is a world-renowned research institution with a long-standing tradition of excellence in the natural sciences, including chemistry and physics, and has produced numerous Nobel laureates. KAIST plans to combine Caltech's basic science research capabilities with KAIST's strengths in AI-driven and autonomous research to jointly pioneer new research topics in the field of future chemistry.
Collaboration between KAIST and Caltech began in 2024 through the BrainLink program, which supports exchanges among outstanding researchers. Centered on the Nitrogen-Hydrogen Synergy Hub Research Center, led by Professor Hyungjun Kim of the KAIST Department of Chemistry, the two institutions have continued joint research and researcher exchanges. This year, the partnership expanded further after being selected for the Ministry of Science and ICT’s Top-Tier Research Institution Cooperation Platform and Joint Research Support Program. Through this program, KAIST launched the Center for Intelligent Circular Chemical Ecosystem Innovation, led by Professor Sang Woo Han of the KAIST Department of Chemistry.
Building on this cooperation, the KAIST Department of Chemistry and Caltech’s Division of Chemistry and Chemical Engineering signed a memorandum of understanding (MOU) in March 2026, further strengthening their collaborative framework. The two institutions plan to hold joint workshops every year, match faculty members for joint mentoring, identify postdoctoral researchers, promote reciprocal research visits, and establish a sustainable operating structure for the joint mentoring program.
At the workshop, researchers are exploring new opportunities for collaboration in key fields shaping the future of chemistry, including AI for chemistry, autonomous laboratories, computational and theoretical chemistry, molecular science, catalysis, synthesis, electrochemistry, and sustainable and circular chemistry. KAIST is also pursuing plans to jointly utilize its autonomous laboratories in synthesis and electrochemistry with Caltech researchers. By jointly utilizing this advanced research environment, in which AI supports experimental design, execution, and data analysis, researchers from both institutions plan to expand the speed and scope of their joint research.
In addition, the two institutions plan to promote short-term reciprocal visits by graduate students, building a sustainable human and academic exchange system that connects graduate students, postdoctoral researchers, and faculty members. The vision goes beyond one-off, project-centered cooperation, aiming to build a long-term foundation in which next-generation researchers from both institutions naturally interact and create new joint research.
The Center for Intelligent Circular Chemical Ecosystem Innovation aims to build a new chemical technology platform that contributes to carbon neutrality and the circular economy by developing intelligent chemical upcycling technologies that convert chemical industry byproducts into high-value chemicals and materials.
Professor Sang Woo Han of KAIST's Department of Chemistry said, "Through this workshop, we aim to expand the KAIST-Caltech collaboration from joint research to a stage where we jointly nurture next-generation researchers." He added, "By connecting the strengths of both institutions, we will work to create new research topics and achievements in the field of future chemistry."
President Choongsik Bae of KAIST said, "KAIST's international cooperation is about building relationships in which outstanding universities, people, and knowledge from around the world flow back and forth and grow together." He emphasized, "By expanding collaboration with world-class research institutions such as Caltech, we will carry KAIST's 'Global Connect' forward into concrete achievements."
Professor Sarah Reisman from Caltech’s Division of Chemistry and Chemical Engineering, “Caltech and KAIST chemistry faculty have a long history of student exchanges and research collaboration, and this workshop is a wonderful opportunity to bring our faculty together and launch new projects supported by the Center for Intelligent Circular Chemical Ecosystem Innovation.” She added, “We are delighted to continue our strong partnership with KAIST.”
2026.09.02 View 382 -
Neural Implant in Korea Remotely Controlled from the United States, Bringing Brain Research into the IoT Era
A researcher in Chicago remotely controls a miniaturized brain implant in Daejeon, Korea — over the internet. Korean researchers have developed a wireless device that can deliver drugs and light to precisely modulate targeted neurons from anywhere in the world. The technology is expected to overcome the constraints of distance and location, supporting long-term studies of brain disorders and the future development of therapeutic devices.
KAIST (President Choongsik Bae) announced on August 27 that a research team led by Professor Jae-Woong Jeong from the School of Electrical Engineering, in collaboration with Professor Wha Young Kim's team at Yonsei University College of Medicine, has developed an IoT-enabled wireless neural implant that integrates drug delivery, optical stimulation, wireless communication, and internet-based remote control into a single miniaturized device.
Conventional studies involving optical stimulation or drug delivery to the brain often required bulky equipment connected by wires, restricting the natural movement of experimental animals. Even wireless devices had their own limitations, often requiring researchers to operate them at close range, thereby restricting experimental flexibility and introducing the so-called “observer effect”.
To overcome these limitations, the research team developed the brain implant with IoT connectivity. Even without being physically present in the laboratory, researchers can remotely administer drugs or stimulate specific brain neurons with light in real time via the internet. The device can also be programmed to operate automatically at a preset time.
The device is about the size of a sugar cube and is designed not to interfere with the animal's natural behavior. Researchers no longer need to repeatedly approach or handle equipment near the animal, reducing the stress caused by a researcher's presence, which can otherwise affect the animal's behavior and bias experimental results.
The implant contains a microfluidic system that precisely delivers drugs to a targeted region of the brain, as well as a micro-LED that enables optical control of specific neurons. Drug delivery and optical stimulation can be controlled independently, or the two functions can be combined.
The drug reservoir is designed to be magnetically detachable. Even after the drug is depleted, researchers can replace or refill the reservoir without the need for additional implantation surgery, enabling long-term, repeated experiments.
The research team implanted the device in rats and verified its performance over a four-week period. In particular, a researcher in Chicago successfully operated the brain implant in Daejeon, Korea, in real time via the internet, demonstrating that the device can operate reliably over intercontinental distances.
The team also conducted an experiment in which cocaine was wirelessly administered to a rat's brain while specific neurons were simultaneously stimulated with light. The results showed that addiction-related behavioral responses could be suppressed, demonstrating the potential of combining drug delivery and optical stimulation for neural circuit research.
By eliminating the need for researchers to operate equipment directly beside experimental animals, this technology enables long-term studies of the relationship between brain circuits and behavior under naturalistic conditions. It is expected to be useful for studying conditions that involve long-term changes in neural circuit function and behavior, such as addiction, depression, and neurodegenerative diseases.
The technology could ultimately pave the way for intelligent implantable medical devices that combine brain-state sensing with AI to deliver drugs or neural stimulation precisely when needed.
Professor Jae-Woong Jeong from KAIST said, “This technology transforms wireless brain implants that use light and drugs from short-range control tools into IoT-based brain engineering platforms capable of long-term, automated, and remote experimentation.” He added, “In the long term, it could contribute to the development of intelligent implantable medical devices for the diagnosis and treatment of brain disorders.”
Professor Wha Young Kim from Yonsei University said, “This platform allows researchers to remotely and precisely control specific brain circuits over extended periods while animals move freely under naturalistic conditions.” She added, “It is expected to become an important tool for identifying causal relationships between neural circuits and behavior in disease models such as addiction, depression, and neurodegenerative disorders.”
Eun Young Jeong, a doctoral student in KAIST's School of Electrical Engineering, and Jong Woo Park, a doctoral student at Yonsei University College of Medicine, served as co-first authors. The study was published on July 29 in the international journal Science Advances.
Paper title: IoT-enabled wireless neural implant for chronic, programmable neuropharmacology and optogenetics,
DOI: 10.1126/sciadv.aee8648
This research was supported by the Mid-Career Researcher Program and Basic Research Laboratory Program of the National Research Foundation of Korea, funded by the Ministry of Science and ICT, as well as the Industrial Technology Alchemist Project of the Ministry of Trade, Industry and Energy.
2026.08.27 View 1900 -
KAIST Uncovers the “Hidden Key” to Immunotherapy for Intractable Brain Tumors
Researchers have uncovered a clue to why immune checkpoint inhibitors—cancer therapies that release the immune “brakes” exploited by tumors to evade attack—show limited efficacy in some brain tumors. A KAIST research team found that B cell and antibody responses initiated in tumor-draining lymph nodes, rather than T cells alone, are critical to the antitumor effects of anti-CTLA-4 therapy, opening a new avenue for treating intractable brain tumors.
KAIST (President Choongsik Bae) announced on the 19th of July that a research team led by Professor Heung Kyu Lee from the Department of Biological Sciences has identified a previously unrecognized immune mechanism through which anti-CTLA-4, a type of immune checkpoint inhibitor, promotes B-cell responses in tumor-draining lymph nodes, thereby helping the immune system attack brain tumors.
Glioblastoma is one of the most aggressive malignant brain tumors, with frequent recurrence and a poor prognosis even after surgery and radiation therapy. Immune checkpoint inhibitors, which restore the ability of immune cells to attack cancer cells, have produced substantial therapeutic benefits in various cancers. However, their effectiveness in glioblastoma has remained limited because of the highly immunosuppressive environment surrounding the tumor.
Researchers have traditionally regarded T cells—immune cells that can directly attack cancer cells—as the primary target of immune checkpoint inhibitors. B cells, meanwhile, are well known for producing antibodies following infection or vaccination, but their role in brain tumor immunotherapy has remained largely unexplored. The research team therefore investigated whether anti-CTLA-4 could influence B-cell responses as well as T-cell responses.
The findings challenged the prevailing T-cell-centered view. In mouse glioma models, anti-CTLA-4 treatment reduced tumor burden and significantly prolonged survival. However, these therapeutic effects were largely lost in mice lacking B cells, demonstrating that B cells are required for the efficacy of anti-CTLA-4 treatment in these models.
The team also identified where B cells played their key role. Rather than being prominent in the brain, where the tumor cells were located, the response increased markedly in the Deep Cervical Lymph Nodes, which are located deep in the neck and receive lymphatic drainage from the brain. In particular, germinal center B cells and T follicular helper cells, both of which are important for antibody formation, increased together in these lymph nodes. This was accompanied by an increase in immunoglobulin G, or IgG, responses. IgG is a major class of antibody that can recognize cancer cells as targets and help immune cells eliminate them.
The resulting IgG antibodies bound to the surface of glioma cells, helping macrophages—immune cells that engulf foreign substances and cancer cells—remove the tumor cells more effectively.
The research team also examined this process directly in vivo. Using a specialized dual-reporter glioma model expressing the red fluorescent protein mCherry and the green fluorescent protein EGFP, the researchers successfully visualized tumor-infiltrating phagocytes actively engulfing glioma cells following anti-CTLA-4 treatment.
The study provides the first functional evidence that B-cell immune responses—previously known mainly for their roles in infection and vaccination—can be a key factor determining the effectiveness of immunotherapy for hard-to-treat brain tumors. It also expands the conventional T-cell-centered framework of cancer immunotherapy by showing that treatment efficacy can be strongly shaped by immune responses originating not only within the tumor, but also in tumor-draining lymph nodes outside it.
Yumin Kim, a postdoctoral researcher in the KAIST Department of Biological Sciences, served as the first author of the study, with Professor Heung Kyu Lee serving as the corresponding author. Professor Ji Eun Oh from the KAIST Graduate School of Medical Science and Engineering also contributed to the research. The findings were published on July 10 in Science Immunology.
Paper title: The efficacy of immunotherapy in glioma requires distal B-cell responses in tumor-draining lymph nodes
DOI: 10.1126/sciimmunol.adz2494
Authors: Yumin Kim, In Kang, Byeong Hoon Kang, Won Hyung Park, Chae Won Kim, Hyun-Jin Kim, Jeongwoo La, Myoung Seung Kwon, Sang Hee Park, Seo Hyeon Im, Hyeon Cheol Kim, Keun Bon Ku, Minji Kim, and Ji Eun Oh from KAIST, with Heung Kyu Lee from KAIST as the corresponding author.
This research was supported by National Research Foundation of Korea grants RS-2023-NR077244 (to H.K.L.), RS-2024-00439735 (to H.K.L.), RS-2024-00411928 (to Y.K.), RS-2025-00517107 (to J.E.O.), and RS-2026-25509011 (to H.K.L.). This study was also supported by Samsung Science and Technology Foundation grants SSTF-BA1902-05 (to H.K.L.) and SSTF-BA2201-11 (to J.E.O.).
2026.07.20 View 2068 -
KAIST Professor S. Josephine Suh Receives the 2026 Frontiers of Science Award
<Professor S. Josephine Suh>
Professor S. Josephine Suh wins the Frontiers of Science Award for the second consecutive year following last year - Honored for her paper published in November 2017, targeting research papers that have achieved significant results within the last 10 years - Recognized internationally for leading research achievements in the fields of quantum gravity and quantum field theory
KAIST announced on June 12th that a co-authored research paper by Professor S. Josephine Suh of the Department of Physics was selected as a winning paper for the '2026 Frontiers of Science Award' presented by the International Congress of Basic Science (ICBS). Professor Suh has won this award for two consecutive years, following her win in 2025.
The Frontiers of Science Award is presented to papers published within the last 10 years in the fields of mathematics, physics, and information science that have achieved outstanding academic originality and impact. The award ceremony will take place during the ICBS event to be held in Beijing, China, in August 2026.
The award-winning paper is "The soft mode in the Sachdev-Ye-Kitaev model and its gravity dual," a joint research project between Professor Alexei Kitaev of the California Institute of Technology (Caltech) and Professor S. Josephine Suh.
※ Paper Title: The soft mode in the Sachdev-Ye-Kitaev model and its gravity dual, DOI: https://doi.org/10.1007/JHEP05(2018)183)
The SYK (Sachdev-Ye-Kitaev) model is a quantum physics model in which a large number of Majorana fermions (special quantum particles whose particles and antiparticles have identical properties) interact randomly and strongly. Despite being a highly complex quantum many-body system (a system where many particles entangle and interact simultaneously), it allows for mathematically exact analysis. Furthermore, because its characteristics of quantum chaos (chaotic phenomena occurring in quantum systems) are remarkably similar to those of black holes, it has drawn attention as a core theory for understanding the microscopic structure (the fine quantum states that make up a black hole) of black holes.
The award-winning paper demonstrated that the physical properties displayed by the SYK model in a low-energy state precisely connect with two-dimensional gravity theory (a gravity model simplified by leaving only one dimension each for space and time). This research has since become a core theoretical foundation for black hole and quantum gravity research, establishing itself as one of the most widely cited representative papers in the relevant field.
In addition, the SYK model is utilized as a representative theoretical model to explain how information is stored and disappears inside a black hole, drawing attention as a key research topic for solving conundrums in modern physics.
The 'Frontiers of Science Award' is an international academic award that the International Congress of Basic Science (ICBS) has been presenting since 2023. The Global Committee makes the final selection of winning works through recommendations and evaluations from experts worldwide.
In its official notification of selection, the ICBS stated, "Professor Suh's research has made an outstanding contribution to the field of Formal Quantum Field Theory*," adding, "The researcher's dedication to expanding the boundaries of human knowledge provides great inspiration to the scientific community."
*Formal Quantum Field Theory: A field of theoretical physics that explores the mathematical principles and structures of quantum field theory, which explains the fundamental particles and forces of the universe.
Professor S. Josephine Suh said, "The research in this paper was a work showing how a specific quantum many-body system and gravity theory correspond at a microscopic level," and added, "The research currently underway seeks to obtain a physical understanding of how spacetime is generated from a quantum many-body system based on this correspondence."
The total prize money for this award is $25,000 (approximately 33 million KRW), which is shared jointly among the authors of the winning paper.
Reference: Official website of the Frontiers of Science Award: https://www.icbs.cn
2026.06.15 View 2843 -
AI, Humanoid Robots, and Space Rovers to Gather: Experience Future Technologies at the Science Festival
<(From left) Photos of the KAIST Science Festival exhibition hall and booths from the previous year>
KAIST announced on April 10th that KAIST will participate in the ‘2026 Korea Science and Technology Festival,’ the largest science festival in the country, to mark Science Month in April. KAIST will operate ‘KAIST Play World,’ an interactive exhibition hall showcasing the pinnacle of AI and robotics. This year’s festival will be held in two parts: ‘2026 Korea Science Festival in Daejeon (April 17–19)’ and ‘2026 Korea Science Festival in Gyeonggi (April 24–26).’ KAIST will host consecutive exhibitions at the Daejeon DCC (Second Exhibition Hall) and KINTEX in Ilsan. Under the ‘Play World’ concept, KAIST plans to offer differentiated interactive content tailored to various generations. In particular, on-site events and souvenirs featuring the KAIST character ‘Nupjuk-i’ will be provided to enhance visitor engagement.
□ [Daejeon] From Humanoid Robots to Space Rovers and AI Semiconductor Friend ‘BROCA’ The exhibition at Daejeon DCC from April 17 to 19 will feature ‘Future Tech Experience Content’ centered on advanced robotics, space technology, and AI semiconductor technology, allowing visitors to experience KAIST's core research achievements firsthand. First, a humanoid robot equipped with control technology developed by Eurobotics Co., Ltd., a startup from Professor Myung Hyun’s research team in the School of Electrical Engineering, will be unveiled on the 17th. This robot is gaining attention as a next-generation platform capable of natural walking in both industrial and urban environments. Additionally, on the 19th, a humanoid robot from Professor Park Hae-won’s team in the Department of Mechanical Engineering will demonstrate high-difficulty human movements such as the duck walk and moonwalk, showcasing its potential for practical industrial use. Professor Lee Dae-young’s team in the Department of Aerospace Engineering will present the world’s first deployable lunar rover wheel based on origami technology. Visitors can touch the transformable wheel model and observe space rover demonstrations and displays by the co-developer, Unmanned Exploration Laboratory (UEL). Educational sessions for folding various space systems using origami will also be available. Along with this, visitors can experience advanced human-machine interaction through ‘BROCA,’ a mobile social AI agent that builds relationships with users beyond simple Q&A, and the voice-capable guide robot ‘On-Newro,’ developed by Professor Yoo Hoi-jun’s team at the AI Semiconductor Graduate School. The student startup ‘Liar Games’ will operate a trial zone for ‘Dual Focus,’ an abstract strategy board game where players compete 1:1 against AI. Similar to the deep strategic play of chess or Go, the rules are intuitive enough to learn in 5 minutes, which is expected to stimulate the challenge-seeking spirit of visitors.
< (Top row from left) Professor Park Hae-won’s humanoid robot, Professor Yoo Hoi-jun’s BROCA, (Bottom row from left) Eurobotics’ humanoid walking technology capable of overcoming any terrain based on a mobile kit, Professor Lee Dae-young’s storable and deployable rover for lunar exploration >
□ [Gyeonggi] ‘Raibo’ the Rough-Terrain Robot and AI-Based Future Experiences The Gyeonggi exhibition at KINTEX from April 24 to 26 will focus on ‘Life-Oriented Experience Content’ centered on AI and everyday technology. ‘Raibo,’ a quadrupedal robot developed by Professor Hwangbo Jemin’s team in the Department of Mechanical Engineering, is capable of high-speed movement on complex terrains such as sand, stairs, and debris, and is expected to be utilized for disaster relief and search missions. Visitors can experience Raibo’s driving technology directly at the site. The ‘Future Memories Studio’ from Professor Nam Tek-jin’s team in the Department of Industrial Design will provide a new experience where visitors can meet and talk to their future selves 10 years later, recreated using AI-generated visuals and voices. Participants will receive a four-cut photo capturing a moment that is the future for their current self but a memory for their future self. Professor Yun Yun-jin’s team at the KAIST Urban AI Research Center will present technology that analyzes the impact of climate change on small business sales through ‘AI-based Sight and Sound for Heatwave Consumption Index.’ They will showcase time-series AI-based sales prediction technology and generative AI technology that expresses this visually and audibly. Furthermore, Professor Yun’s lecture, “City Walk of Artificial Intelligence: Urban AI and the Future of Cities,” will be held on April 24 (Fri) at 15:00 in KINTEX Meeting Room 206. In addition, Professor Yoo Hoi-jun’s team from the AI Semiconductor Graduate School will continue from the Daejeon exhibition to operate an experience zone for various mobile AI agents based on AI semiconductors. Also, the student startup Rabbithole Company will introduce a new type of game where AI NPCs (Non-Player Characters) converse and cooperate to solve given problems. Visitors can participate by observing the process where AI characters create their own stories by being presented with situations or goals instead of being directly controlled.
< (Top row from left) Professor Hwangbo Jemin’s Raibo, Professor Nam Tek-jin’s team: Met My Future Self 10 Years Later, (Bottom row from left) Professor Yun Yun-jin’s Seeing and Hearing Heatwave Consumption Index through AI, Game image from CEO Kim Na-hoon’s Rabbithole Company >
Through the exhibitions in both regions, KAIST plans to operate various participatory programs to make science and technology easy and fun to approach, vividly conveying how technology from the laboratory transforms our lives. KAIST President Lee Kwang-hyung remarked, “This year’s science festival is a large-scale event connecting Daejeon and Gyeonggi, allowing more citizens to experience KAIST’s innovative research achievements firsthand.” He added, “I hope this will be a precious time for people to experience the future created by robots and AI, fostering their dreams and curiosity about science.”
2026.04.13 View 4102 -
Longevity mediated by suppressing age-associated circRNA
< (Back row from left) Prof. Yoon Ki Kim, Prof. Seung-Jae V. Lee, and Gwangrog Lee; (Front row from left) Dr. Sung Ho Boo, Sieun S. Kim, Seokjin Ham, and (top) Donghun Lee >
Cells in our bodies produce RNA based on genetic information stored in DNA, and RNA serves as a blueprint for making proteins. Researchers at our university have discovered a new phenomenon: removing 'circular RNA' that accumulates in cells as we age can slow down aging and extend lifespan. This study provides crucial clues for uncovering the principles of aging and developing treatment strategies for related diseases.
Professor Seung-Jae V. Lee’s research team (RNA-Mediated Healthspan and Longevity Research Center) from the Department of Biological Sciences, in collaboration with research teams led by Professors Yoon Ki Kim and Gwangrog Lee, announced on the 18th that they discovered the RNASEK protein—an enzyme that degrades circular RNA—plays a vital role in slowing aging and extending lifespan.
Until now, circular RNA has been regarded mainly as an aging marker because of its stability, which allows it to accumulate over time. However, the molecular mechanism for removing this RNA and its direct link to aging had not been clearly identified. The research team conducted this study to determine how the accumulation of circular RNA affects aging and whether an intracellular management system exists to regulate it.
Using Caenorhabditis elegans (C. elegans), a short-lived roundworm widely used in aging research, the team first confirmed that the circular RNA-degrading enzyme RNASEK is essential for longevity. They also discovered that as aging progresses, the amount of RNASEK decreases, resulting in an abnormal accumulation of circular RNA within cells.
Conversely, artificially increasing the levels of RNASEK (overexpression) extended the lifespan and allowed the organisms to survive longer in a healthy state. This implies that the process of appropriately removing cellular circular RNA is critical for maintaining health and longevity.
The research team also found that RNASEK prevents the toxic aggregation of circular RNAs in aged organisms. . When RNASEK is deficient and circular RNA accumulates, "stress granules" form abnormally inside the cell, which can impair cellular functions and accelerate aging.
RNASEK works alongside the chaperone protein HSP90 (which helps proteins avoid misfolding or clumping) to inhibit the formation of these stress granules and help cells maintain a normal state. Notably, this phenomenon was observed not only in C. elegans but also in human cells. In mammals, RNASEK also functions to directly degrade circular RNA; a deficiency of RNASEK in human cells and mouse models led to premature aging.
< Diagram showing progress toward longevity or aging depending on circular RNA and the removal enzyme RNASEK >
The researchers explained that this study is significant as it identifies a mechanism for regulating aging at the RNA level. They suggested that research using RNASEK to control circular RNA could lead to the development of treatment strategies for human aging and degenerative diseases.
Professor Seung-Jae V. Lee of KAIST, who led the study, explained, "Until now, circular RNA was merely regarded as a marker of aging that accumulates over time due to its stability. This study proves that circular RNA accumulated during aging actually induces aging, and that RNASEK, which removes it, is a key regulator that slows aging and induces healthy longevity."
< (AI-generated image) Longevity induced by the circular RNA-removing enzyme RNASEK >
Drs. Sieun S. Kim, Seokjin Ham, Sung Ho Boo, and Donghun Lee from the KAIST Department of Biological Sciences participated as joint first authors. The research results were published on February 24 in the world-renowned scientific journal Molecular Cell.
Paper Title: Ribonuclease $\kappa$ promotes longevity by preventing age-associated accumulation of circular RNA in stress granules
DOI: 10.1016/j.molcel.2026.01.031
This research was conducted with support from the Leader Researcher Program of the National Research Foundation of Korea.
2026.03.18 View 3950 -
KAIST Develops Brain-Like AI… Thinks One More Time Even When Predictions Are Wrong
<(From left) Professor Sang Wan Lee, Myoung Hoon Ha, and Dr. Yoondo Sung>
Artificial intelligence now plays Go, paints pictures, and even converses like a human. However, there remains a decisive difference: AI requires far more electricity than the human brain to operate. Scientists have long asked the question, “How can the brain learn so intelligently using so little energy?” KAIST researchers have moved one step closer to the answer.
KAIST (President Kwang Hyung Lee) announced on the 29th that a research team led by Distinguished Professor Sang Wan Lee of the Department of Brain and Cognitive Sciences has developed a new technology that applies the learning principles of the human brain to deep learning, enabling stable training even in deep artificial intelligence models.
Our brain does not passively receive the world. Instead of merely perceiving what is happening in the present, it first predicts what will happen next and, when reality differs from that prediction, adjusts itself to reduce the difference (i.e., prediction error). This is similar to anticipating an opponent’s next move in Go and changing strategy if the prediction turns out to be wrong. This mode of information processing is known as “Predictive Coding.”
< Predictive Coding (PC) Module >
Scientists have attempted to apply this principle to AI, but encountered difficulties. As neural networks become deeper, errors tend to concentrate in specific layers or vanish altogether, repeatedly leading to performance degradation.
The research team mathematically identified the cause of this problem and proposed a new solution. The key idea is simple: instead of predicting only the final outcome, the AI is designed to also predict how its prediction errors will change in the future. The team refers to this as “Meta Prediction.” In simple terms, it is an AI that “thinks once more about its mistakes.” When this method was applied, learning proceeded stably in deep neural networks without halting.
<Analysis of Instability in Predictive Coding Model Errors>
The experimental results were also impressive. In 29 out of 30 experiments, the proposed method achieved higher accuracy than the current standard AI training method, backpropagation. Backpropagation is the representative learning method in which AI “goes backward by the amount of error and corrects it.”
Conventional AI training methods (backpropagation) require tightly interconnected layers, meaning the entire network must be computed and updated simultaneously. In contrast, this new approach demonstrates that, like the brain, large AI models can be effectively trained even when learning occurs in a distributed and partially independent manner.
<Performance Comparison of Predictive Coding Models>
This technology is expected to expand into various fields where power efficiency is critical, including neuromorphic computing, robot AI that must adapt to changing environments, and edge AI operating within devices.
Distinguished Professor Sang Wan Lee stated, “The key to this research is not simply imitating the structure of the brain, but enabling AI to follow the brain’s learning principles themselves,” adding, “We have opened the possibility of artificial intelligence that learns efficiently like the brain.”
This study was conducted with Dr. Myoung Hoon Ha as the first author and Professor Sang Wan Lee as the corresponding author. The paper was accepted to the International Conference on Learning Representations (ICLR 2026) and was published online on January 26.
※ Paper title: “Stable and Scalable Deep Predictive Coding Networks with Meta Prediction Errors”Original paper: https://openreview.net/forum?id=kE5jJUHl9i¬eId=e6T5T9cYqO
This research was supported by the Ministry of Science and ICT and the Institute of Information & Communications Technology Planning & Evaluation (IITP) through the Digital Global Research Support Program (joint research with Microsoft Research), the Samsung Electronics SAIT NPRC Program, and the SW Star Lab Program.
2026.03.06 View 3715 -
Designing the Heart of Hydrogen Cars with AI... Development of Next-Generation Super Catalyst
<(From left) KAIST Ph.D. Candidate HyunWoo Chang, Professor EunAe Cho. (Top, from left) Seoul National University Professor Won Bo Lee, Dr. Jae Hyun Ryu.>
In the era of climate crisis, hydrogen vehicles are emerging as an alternative for eco-friendly mobility. However, the fuel cell, known as the ‘heart of the hydrogen car,’ still faces limitations of high cost and short lifespan. The core cause is the platinum catalyst. While it is a decisive material for generating electricity, the reaction is slow, performance degrades over time, and manufacturing costs are high. Korean researchers have presented a clue to solving this difficult problem.
KAIST announced on February 26th that the research team led by Professor EunAe Cho of the Department of Materials Science and Engineering, together with the team of Professor Won Bo Lee of the School of Chemical and Biological Engineering at Seoul National University, has developed a technology that predicts the ‘atomic arrangement’ tendency of catalysts using artificial intelligence (AI).
This technology is akin to calculating beforehand which combination is advantageous for completing a puzzle before putting it together. By having AI calculate the arrangement speed of metal atoms first, it has become possible to efficiently design catalysts with better performance. The core of this research is that ‘AI revealed the fact that zinc plays a decisive role in the platinum-cobalt atomic arrangement.’
<Schematic diagram of AI-based atomic alignment prediction>
Despite the high performance of existing platinum-cobalt (Pt-Co) alloy catalysts, very high-temperature heat treatment was required to create the ‘intermetallic (L1₀)’ structure, where atoms are regularly arranged. In this process, particles would clump together, or the structure would become unstable, posing limitations for actual fuel cell application.
To solve this problem, the research team introduced machine learning-based quantum chemistry simulations. Through AI, they precisely predicted how atoms move and arrange themselves inside the catalyst.
As a result, they discovered that zinc (Zn) acts as a mediating element that promotes atomic arrangement. The principle is that when zinc is introduced, atoms find their places more easily, forming a more sophisticated and stable structure. In other words, AI has found the ‘optimal path for atomic arrangement creation’ in advance.
< Synthesis process of Zinc-introduced Platinum-Cobalt catalyst>
The zinc-platinum-cobalt catalyst, synthesized based on AI predictions, secured both higher activity and superior long-term durability compared to commercial platinum catalysts. This is a case proving that the ‘virtual blueprint’ calculated by artificial intelligence can be implemented as a high-performance catalyst in an actual laboratory.
In particular, this technology is expected to contribute to extending catalyst lifespan and reducing manufacturing costs across core carbon-neutral industries, such as hydrogen passenger cars, hydrogen trucks requiring long-distance operation, hydrogen ships, and energy storage systems (ESS).
< Conceptual diagram of AI-based catalyst development (AI-generated image) >
Professor EunAe Cho stated, “This research is a case of utilizing machine learning to predict the atomic arrangement tendency of catalysts in advance and implementing this through actual synthesis,” and added, “AI-based material design will become a new paradigm for the development of next-generation fuel cell catalysts.”
Ph.D. Candidate HyunWoo Chang from KAIST’s Department of Materials Science and Engineering and Dr. Jae Hyun Ryu from Seoul National University’s School of Chemical and Biological Engineering participated as co-first authors in this research. The research results were published on January 15, 2026, in ‘Advanced Energy Materials,’ a world-renowned academic journal in the energy materials field. ※ Paper Title: Machine Learning-Guided Design of L1₀-PtCo Intermetallic Catalysts: Zn-Mediated Atomic Ordering, DOI: https://doi.org/10.1002/aenm.202505211
This research was conducted with the support of the National Research Foundation of Korea’s Nano & Material Technology Development Program and the Korea Institute of Energy Technology Evaluation and Planning’s Energy Innovation Research Center for Fuel Cell Technology.
2026.02.27 View 3309 -
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 3197 -
KAIST detects ‘hidden defects’ that degrade semiconductor performance with 1,000× higher sensitivity
<(From Left) Professor Byungha Shin, Ph.D candidate Chaeyoun Kim, Dr. Oki Gunawan>
Semiconductors are used in devices such as memory chips and solar cells, and within them may exist invisible defects that interfere with electrical flow. A joint research team has developed a new analysis method that can detect these “hidden defects” (electronic traps) with approximately 1,000 times higher sensitivity than existing techniques. The technology is expected to improve semiconductor performance and lifetime, while significantly reducing development time and costs by enabling precise identification of defect sources.
KAIST (President Kwang Hyung Lee) announced on January 8th that a joint research team led by Professor Byungha Shin of the Department of Materials Science and Engineering at KAIST and Dr. Oki Gunawan of the IBM T. J. Watson Research Center has developed a new measurement technique that can simultaneously analyze defects that hinder electrical transport (electronic traps) and charge carrier transport properties inside semiconductors.
Within semiconductors, electronic traps can exist that capture electrons and hinder their movement. When electrons are trapped, electrical current cannot flow smoothly, leading to leakage currents and degraded device performance. Therefore, accurately evaluating semiconductor performance requires determining how many electronic traps are present and how strongly they capture electrons.
The research team focused on Hall measurements, a technique that has long been used in semiconductor analysis. Hall measurements analyze electron motion using electric and magnetic fields. By adding controlled light illumination and temperature variation to this method, the team succeeded in extracting information that was difficult to obtain using conventional approaches.
Under weak illumination, newly generated electrons are first captured by electronic traps. As the light intensity is gradually increased, the traps become filled, and subsequently generated electrons begin to move freely. By analyzing this transition process, the researchers were able to precisely calculate the density and characteristics of electronic traps.
The greatest advantage of this method is that multiple types of information can be obtained simultaneously from a single measurement. It allows not only the evaluation of how fast electrons move, how long they survive, and how far they travel, but also the properties of traps that interfere with electron transport.
The team first validated the accuracy of the technique using silicon semiconductors and then applied it to perovskites, which are attracting attention as next-generation solar cell materials. As a result, they successfully detected extremely small quantities of electronic traps that were difficult to identify using existing methods—demonstrating a sensitivity approximately 1,000 times higher than that of conventional techniques.
< Conceptual Diagram of the Evolution of Hall Characterization (Analysis) Techniques >
Professor Byungha Shin stated, “This study presents a new method that enables simultaneous analysis of electrical transport and the factors that hinder it within semiconductors using a single measurement,” adding that “it will serve as an important tool for improving the performance and reliability of various semiconductor devices, including memory semiconductors and solar cells.”
The results of this research were published on January 1 in Science Advances, an international academic journal, with Chaeyoun Kim, a doctoral student in the Department of Materials Science and Engineering, as the first author.
※ Paper title: “Electronic trap detection with carrier-resolved photo-Hall effect,” DOI: https://doi.org/10.1126/sciadv.adz0460
This research was supported by the Ministry of Science and ICT and the National Research Foundation of Korea.
< Conceptual Diagram of Charge Transport and Trap Characterization Using Photo-Hall Measurements (AI-generated image) >
2026.01.08 View 3640 -
Breaking Performance Barriers of All Solid State Batteries
< (Bottom, from left) Professor Dong-Hwa Seo, Researcher Jae-Seung Kim, (Top, from left) Professor Kyung-Wan Nam, Professor Sung-Kyun Jung, Professor Youn-Seok Jung >
Batteries are an essential technology in modern society, powering smartphones and electric vehicles, yet they face limitations such as fire explosion risks and high costs. While all-solid-state batteries have garnered attention as a viable alternative, it has been difficult to simultaneously satisfy safety, performance, and cost. Recently, a Korean research team successfully improved the performance of all-solid-state batteries simply through structural design—without adding expensive metals.
KAIST announced on January 7th that a research team led by Professor Dong-Hwa Seo from the Department of Materials Science and Engineering, in collaboration with teams led by Professor Sung-Kyun Jung (Seoul National University), Professor Youn-Suk Jung (Yonsei University), and Professor Kyung-Wan Nam (Dongguk University), has developed a design method for core materials for all-solid-state batteries that uses low-cost raw materials while ensuring high performance and low risk of fire or explosion.
Conventional batteries rely on lithium ions moving through a liquid electrolyte. In contrast, all-solid-state batteries use a solid electrolyte. While this makes them safer, achieving rapid lithium-ion movement within a solid has typically required expensive metals or complex manufacturing processes.
To create efficient pathways for lithium-ion transport within the solid electrolyte, the research team focused on "divalent anions" such as oxygen and sulfur . Divalent anions play a crucial role in altering the crystal structure by integrating into the basic framework of the electrolyte.
The team developed a technology to precisely control the internal structure of low-cost zirconium (Zr)-based halide solid electrolytes by introducing these divalent anions. This design principle, termed the "Framework Regulation Mechanism," widens the pathways for lithium ions and lowers the energy barriers they encounter during transport. By adjusting the bonding environment and crystal structure around the lithium ions, the team enabled faster and easier movement.
To verify these structural changes, the researchers utilized various high-precision analysis techniques, including:
High-energy Synchrontron X-ray diffraction(Synchrotron XRD)
Pair Distribution Function (PDF) analysis
X-ray Absorption Spectroscopy (XAS)
Density Functional Theory (DFT) modeling for electronic structure and diffusion.
The results showed that electrolytes incorporating oxygen or sulfur improved lithium-ion mobility by 2 to 4 times compared to conventional zirconium-based electrolytes. This signifies that performance levels suitable for practical all-solid-state battery applications can be achieved using inexpensive materials.
Specifically, the ionic conductivity at room temperature was measured at approximately 1.78 mS/cm for the oxygen-doped electrolyte and 1.01 mS/cm for the sulfur-doped electrolyte. Ionic conductivity indicates how quickly and smoothly lithium ions move; a value above 1 mS/cm is generally considered sufficient for practical battery applications at room temperature.
< Structural Regulation Mechanism of Zr-based Halide Electrolytes via Divalent Anion Introduction >
< Atomic Rearrangement of Solid Electrolyte for All-Solid-State Batteries (AI-generated image) >
Professor Dong-Hwa Seo stated, "Through this research, we have presented a design principle that can simultaneously improve the cost and performance of all-solid-state batteries using cheap raw materials. Its potential for industrial application is very high." Lead author Jae-Seung Kim added that the study shifts the focus from "what materials to use" to "how to design them" in the development of battery materials.
This study, with Jae-Seung Kim (KAIST) and Da-Seul Han (Dongguk University) as co-first authors, was published in the international journal Nature Communications on November 27, 2025.
Paper Title: Divalent anion-driven framework regulation in Zr-based halide solid electrolytes for all-solid-state batteries
DOI: https://www.nature.com/articles/s41467-025-65702-2
This research was supported by the Samsung Electronics Future Technology Promotion Center, the National Research Foundation of Korea, and the National Supercomputing Center.
2026.01.07 View 7784