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AI, Humanoid Robots, and Space Rovers to Gather: Experience Future Technologies at the Science Festival
<(From left) Photos of the KAIST Science Festival exhibition hall and booths from the previous year>
KAIST announced on April 10th that KAIST will participate in the ‘2026 Korea Science and Technology Festival,’ the largest science festival in the country, to mark Science Month in April. KAIST will operate ‘KAIST Play World,’ an interactive exhibition hall showcasing the pinnacle of AI and robotics. This year’s festival will be held in two parts: ‘2026 Korea Science Festival in Daejeon (April 17–19)’ and ‘2026 Korea Science Festival in Gyeonggi (April 24–26).’ KAIST will host consecutive exhibitions at the Daejeon DCC (Second Exhibition Hall) and KINTEX in Ilsan. Under the ‘Play World’ concept, KAIST plans to offer differentiated interactive content tailored to various generations. In particular, on-site events and souvenirs featuring the KAIST character ‘Nupjuk-i’ will be provided to enhance visitor engagement.
□ [Daejeon] From Humanoid Robots to Space Rovers and AI Semiconductor Friend ‘BROCA’ The exhibition at Daejeon DCC from April 17 to 19 will feature ‘Future Tech Experience Content’ centered on advanced robotics, space technology, and AI semiconductor technology, allowing visitors to experience KAIST's core research achievements firsthand. First, a humanoid robot equipped with control technology developed by Eurobotics Co., Ltd., a startup from Professor Myung Hyun’s research team in the School of Electrical Engineering, will be unveiled on the 17th. This robot is gaining attention as a next-generation platform capable of natural walking in both industrial and urban environments. Additionally, on the 19th, a humanoid robot from Professor Park Hae-won’s team in the Department of Mechanical Engineering will demonstrate high-difficulty human movements such as the duck walk and moonwalk, showcasing its potential for practical industrial use. Professor Lee Dae-young’s team in the Department of Aerospace Engineering will present the world’s first deployable lunar rover wheel based on origami technology. Visitors can touch the transformable wheel model and observe space rover demonstrations and displays by the co-developer, Unmanned Exploration Laboratory (UEL). Educational sessions for folding various space systems using origami will also be available. Along with this, visitors can experience advanced human-machine interaction through ‘BROCA,’ a mobile social AI agent that builds relationships with users beyond simple Q&A, and the voice-capable guide robot ‘On-Newro,’ developed by Professor Yoo Hoi-jun’s team at the AI Semiconductor Graduate School. The student startup ‘Liar Games’ will operate a trial zone for ‘Dual Focus,’ an abstract strategy board game where players compete 1:1 against AI. Similar to the deep strategic play of chess or Go, the rules are intuitive enough to learn in 5 minutes, which is expected to stimulate the challenge-seeking spirit of visitors.
< (Top row from left) Professor Park Hae-won’s humanoid robot, Professor Yoo Hoi-jun’s BROCA, (Bottom row from left) Eurobotics’ humanoid walking technology capable of overcoming any terrain based on a mobile kit, Professor Lee Dae-young’s storable and deployable rover for lunar exploration >
□ [Gyeonggi] ‘Raibo’ the Rough-Terrain Robot and AI-Based Future Experiences The Gyeonggi exhibition at KINTEX from April 24 to 26 will focus on ‘Life-Oriented Experience Content’ centered on AI and everyday technology. ‘Raibo,’ a quadrupedal robot developed by Professor Hwangbo Jemin’s team in the Department of Mechanical Engineering, is capable of high-speed movement on complex terrains such as sand, stairs, and debris, and is expected to be utilized for disaster relief and search missions. Visitors can experience Raibo’s driving technology directly at the site. The ‘Future Memories Studio’ from Professor Nam Tek-jin’s team in the Department of Industrial Design will provide a new experience where visitors can meet and talk to their future selves 10 years later, recreated using AI-generated visuals and voices. Participants will receive a four-cut photo capturing a moment that is the future for their current self but a memory for their future self. Professor Yun Yun-jin’s team at the KAIST Urban AI Research Center will present technology that analyzes the impact of climate change on small business sales through ‘AI-based Sight and Sound for Heatwave Consumption Index.’ They will showcase time-series AI-based sales prediction technology and generative AI technology that expresses this visually and audibly. Furthermore, Professor Yun’s lecture, “City Walk of Artificial Intelligence: Urban AI and the Future of Cities,” will be held on April 24 (Fri) at 15:00 in KINTEX Meeting Room 206. In addition, Professor Yoo Hoi-jun’s team from the AI Semiconductor Graduate School will continue from the Daejeon exhibition to operate an experience zone for various mobile AI agents based on AI semiconductors. Also, the student startup Rabbithole Company will introduce a new type of game where AI NPCs (Non-Player Characters) converse and cooperate to solve given problems. Visitors can participate by observing the process where AI characters create their own stories by being presented with situations or goals instead of being directly controlled.
< (Top row from left) Professor Hwangbo Jemin’s Raibo, Professor Nam Tek-jin’s team: Met My Future Self 10 Years Later, (Bottom row from left) Professor Yun Yun-jin’s Seeing and Hearing Heatwave Consumption Index through AI, Game image from CEO Kim Na-hoon’s Rabbithole Company >
Through the exhibitions in both regions, KAIST plans to operate various participatory programs to make science and technology easy and fun to approach, vividly conveying how technology from the laboratory transforms our lives. KAIST President Lee Kwang-hyung remarked, “This year’s science festival is a large-scale event connecting Daejeon and Gyeonggi, allowing more citizens to experience KAIST’s innovative research achievements firsthand.” He added, “I hope this will be a precious time for people to experience the future created by robots and AI, fostering their dreams and curiosity about science.”
2026.04.13 View 1231 -
Undergraduate Rover Team (MR2) Advances to Finals of 'URC 2026', the World’s Largest Mars Rover Competition
<Photo: KAIST Undergraduate Club MR2 Team Members>
Undergraduate students from KAIST are set to take on the world stage with an exploration rover—a robotic vehicle designed to explore in place of humans—that they built themselves. The team has secured a spot in the finals of the world’s largest Mars rover competition, marking a first-ever achievement for KAIST.
KAIST announced on the 3rd that 'MR2' (Advised by Professor Yong-Hwa Park, Department of Mechanical Engineering), a rover team from the undergraduate robotics club MR (Microrobot Research), has earned a seed in the finals of the '2026 University Rover Challenge (URC)', the premier international Mars rover competition for university students.
The URC is organized by The Mars Society and takes place at the Mars Desert Research Station (MDRS) in Utah, USA, an environment that closely mimics the Martian surface. Participating teams compete in four key missions using rovers they developed: ▲Science Mission, ▲Delivery Mission, ▲Equipment Servicing Mission, and ▲Autonomous Navigation Mission.
This year’s competition saw 116 university teams from 18 countries engage in a fierce preliminary round. Team MR2 secured its place in the top 38 finalists by scoring 95.38 out of 100. This milestone is particularly significant as it is the first time a KAIST team has ever reached the URC finals, proving the excellence of KAIST undergraduates in robot design and control on a global scale.
The next-generation exploration rover 'GAP-1000', independently developed by MR2, is a modular rover designed for stable operation in extreme environments. It features a 6-DOF (Degrees of Freedom) robotic arm capable of precisely controlling objects over 5kg, allowing it to perform complex equipment manipulation tasks.
<Photo: Operation of GAP-1000's Manipulator and Science Module Integration>
The rover also boasts strong autonomous driving capabilities. By combining RTK-GNSS (precision satellite positioning), IMU (Inertial Measurement Units) for motion sensing, and odometry based on wheel rotation, it can autonomously navigate optimal paths through complex terrain. Additionally, a drone relay system has been integrated to ensure stable exploration even in areas with communication dead zones.
For the science mission, the rover can collect soil from 10cm underground, remove impurities via centrifugation, and analyze traces of life using protein detection reagents such as Biuret and Bradford. This is paired with spectroscopic analysis technology that identifies material composition by analyzing light wavelengths, creating an integrated system for real-time life detection.
"We experienced a lot of trial and error while managing everything from design to production ourselves, but I am thrilled that we achieved KAIST’s first-ever advancement to the finals," said Myung-woo Jung (Department of Mechanical Engineering), the team leader of MR2. "We will prepare thoroughly in the remaining time to achieve a great result on-site."
<Photo: Scenery of MDRS in Utah, USA, where the competition will be held (Photo Credit: The Mars Society)>
Advising Professor Yong-Hwa Park noted, "It is impressive that the students independently implemented a rover for extreme environments. This competition will serve as an opportunity to showcase KAIST’s technological prowess to the world."
KAIST President Kwang-Hyung Lee added, "It is a very meaningful achievement for our undergraduates to reach the finals of the world’s largest competition with a rover they designed and built themselves. I hope this experience serves as a catalyst for our students to challenge themselves and grow on the global stage."
Team MR2 consists of 13 undergraduate students from various majors, including Mechanical Engineering, Electrical Engineering, and Industrial Design. Having completed long-distance operation tests in outdoor environments, they are currently conducting final checks for the finals. The main competition will be held from May 27th to 30th at the MDRS in Utah, USA.
※ Related Links
MR2 Official Website: https://urc-kaist.github.io/
MR2 Instagram: https://www.instagram.com/urc_mr2/
MR2 YouTube: https://www.youtube.com/@MR2KAISTRoverTeam
2026.04.03 View 904 -
KAIST Reveals the Orbital Principle of Electron Motion for Realizing Memory of Dreams
<(From Left) Dr. Geun-Hee Lee, Professor Kyung-Jin Lee, Professor Kyoung-Whan Kim>
Research is actively underway to develop a “dream memory” that can reduce heat generation in smartphones and laptops while delivering faster performance and lower power consumption. Korean researchers have now proposed a new possibility for controlling magnetism using the exchange interaction of electron orbitals—the motion of electrons orbiting around an atomic nucleus—rather than relying on the conventional exchange interaction of electron spin, the rotational property of electrons inside semiconductors.
KAIST (President Kwang Hyung Lee) announced on the 16th of March that a joint research team led by Professor Kyung-Jin Lee of the Department of Physics at KAIST and Professor Kyoung-Whan Kim of the Department of Physics at Yonsei University (President Dong-Sup Yoon) has established, for the first time in the world, a new theoretical framework enabling magnetism to be freely controlled through orbital exchange interaction*, surpassing the limitations of conventional technologies that control magnetism using electric currents.*Orbital exchange interaction: a phenomenon in which the orbitals formed by electrons moving around an atomic nucleus interact with one another, thereby influencing the direction or properties of magnetism.
Until now, next-generation memory research has mainly focused on the spin of electrons. Spin refers to the property of electrons that rotate on their own axis like tiny spinning tops, and information can be stored by using the direction of this rotation. However, electrons simultaneously move around the atomic nucleus along paths known as orbitals. In this study, the research team theoretically demonstrated that when electric current flows, the orbital energy of electrons interacts directly with the orbitals of magnetic materials, enabling the transmission of information. Through this mechanism, they confirmed that the properties of magnets can be altered much more efficiently than with conventional spin-based approaches.
The most significant outcome of this research is the discovery that electric current does not merely change the direction of a magnet but can also modify the intrinsic properties of the magnet itself, such as the magnetic anisotropy (a magnet’s preferred direction) and rotational characteristics.
In particular, calculations by the research team showed that orbital-based control effects could be significantly stronger than existing spin-based methods. This finding suggests the possibility of a future era of orbital-based electronic devices, in which orbitals rather than spin play the central role in semiconductor components. The researchers also proposed practical experimental methods to measure these effects, which is expected to increase the potential for industrial applications.
The principle may also apply to altermagnetic materials, which have recently attracted significant attention in academia. Altermagnetism refers to a new form of magnetic material in which electron spins within atoms are arranged in alternating directions in an ordered pattern. Although these materials do not appear magnetic externally, they strongly influence electron motion. Because of this property, they allow precise control of electron states and are considered promising for high-speed, low-power semiconductor devices and next-generation memory technologies. The study therefore provides a strong theoretical foundation for developing future logic and memory devices.
Dr. Geun-Hee Lee stated, “This study demonstrates that controlling magnetism with electric current does not necessarily have to rely solely on spin. A new perspective—understanding and controlling magnetism using the orbital motion of electrons—will become an important milestone for the development of next-generation ultra-fast, low-power memory.”
In this research, Dr. Geun-Hee Lee (KAIST) participated as the first author, while Professor Kyoung-Whan Kim (Yonsei University) and Professor Kyung-Jin Lee (KAIST) served as co-corresponding authors. The results were published on February 2 in the internationally renowned journal Nature Communications, recognizing the academic significance of the work.
※ Paper title: “Orbital exchange-mediated current control of magnetism,” DOI: https://doi.org/10.1038/s41467-026-68846-x
This research was supported by the Frontier Challenge R&D Project, the Mid-Career Researcher Program, the Science Research Center (SRC) program, the Early Career Researcher Program of the National Research Foundation of Korea, and Samsung Electronics.
2026.03.16 View 942 -
KAIST Solves the 500-Year-Old ‘Pain’ Behind Michelangelo’s painting of The Creation of Adam
<(From Left) Ph.D candidate Minwoo Choi, Ph.D candidate Hyejoon Jun, Professor Hyoungsoo Kim>
More than 500 years ago, Michelangelo spent four years painting The Creation of Adam on the ceiling of the Sistine Chapel, struggling with paint dripping onto his face. He described the process as “closer to torture than painting.” Now, researchers at KAIST have developed a technology that can effectively “hold up falling paint.” Beyond ceiling paintings, this principle could help solve the problem of liquid films collapsing on inclined surfaces, with potential applications in precision coating, electronic circuit printing, 3D printing, and fluid control in space environments.
KAIST (President Kwang Hyung Lee) announced on the 12th of March that a research team led by Professor Hyoungsoo Kim of the Department of Mechanical Engineering has reinterpreted the fundamental cause of downward flow under gravity—known as gravitational instability—from the perspective of interfacial fluid mechanics* and proposed a method to control it by mixing a small amount of volatile liquid into a suspended liquid film.*Interfacial fluid mechanics: the study of the balance of microscopic forces acting at the surface of liquids.
Why was it so difficult for Michelangelo to paint on the ceiling? When paint is applied to a ceiling, a thin liquid film forms. However, this film gradually becomes unstable due to gravity and eventually drips down. This phenomenon is common in everyday life.
For example, when steam condenses on a bathroom ceiling, it first forms a thin layer of water that eventually gathers into droplets and falls. Similarly, droplets that appear on the ceiling of a refrigerator initially form a thin layer but gradually grow and begin to drip downward. This type of instability, where liquid accumulated on an upper surface collapses under gravity, is known as Rayleigh–Taylor instability. Until now, it has generally been considered unavoidable in the presence of gravity.
The research team proposed mixing a small amount of volatile liquid into the suspended liquid film. As the volatile component evaporates, it changes the concentration distribution along the liquid surface, creating differences in surface tension. Surface tension is the force that pulls a liquid surface inward, which is why water droplets maintain a rounded shape.
When differences in surface tension arise, the region with stronger tension pulls liquid toward itself from regions with weaker tension. This creates a surface flow known as the Marangoni effect. Through experiments and theoretical analysis, the researchers demonstrated that this surface flow can effectively hold the liquid in place and suppress the gravitational instability that would otherwise cause it to fall.
A familiar example can illustrate this effect. If pepper powder is sprinkled evenly on the surface of water, it remains floating. However, if a drop of detergent is placed in the center, the pepper suddenly moves outward toward the edges. This happens because the detergent reduces the surface tension where it touches the water, allowing the surrounding regions with stronger surface tension to pull the liquid outward. As the surface flow develops, the pepper particles move along with it.
In this study, evaporation of the volatile liquid created a similar surface tension difference. But instead of pushing particles outward like in the pepper example, the flow pulled the liquid upward, counteracting the force that would otherwise cause it to drip downward.
As a result, under certain conditions the liquid film remained intact despite gravity. In some cases, the researchers even observed a new behavior in which droplets did not fall but the liquid film oscillated periodically. This demonstrates that gravitational instability can be actively controlled using only natural processes—such as liquid composition and evaporation—without any external energy input.
This principle could enable thinner and more uniform liquid films in precision coating, printing, and layer-by-layer manufacturing processes, allowing stable coating even on tilted surfaces. It may also extend to technologies such as 3D printing and fluid control in specialized environments like space. In essence, the physical limitation that Michelangelo struggled with 500 years ago may now inspire future industrial technologies.
The Creation of Adam (AI-generated image)>
Professor Hyoungsoo Kim stated, “Rayleigh–Taylor instability has long been considered unavoidable as long as gravity exists. This research is meaningful because it shows that gravitational instability can be actively controlled without external energy by utilizing natural processes such as liquid composition and evaporation.” He added, “This principle could extend beyond coating, printing, and layering processes to fluid control technologies in space environments.”
This study was led by Minwoo Choi, an integrated master’s–PhD student in Mechanical Engineering, as the first author. The discovery, recognized as a new finding in the control of hydrodynamic instability, was published online on January 29 in the international journal Advanced Science (Wiley) and was selected as a Frontispiece article.
※ Paper title: “Evaporation-Driven Solutal Marangoni Control of Rayleigh–Taylor Instability in Inverted Films,” Authors: First author Minwoo Choi (KAIST), co-author Hyejoon Jun (KAIST), corresponding author Hyoungsoo Kim (KAIST), DOI: https://doi.org/10.1002/advs.202520343
This research was supported by the Mid-Career Researcher Program of the National Research Foundation of Korea (MSIT: 2021R1A2C2007835)
2026.03.12 View 870 -
Secret to Drug Addiction Relapse Found: Brain's Addiction Circuit Identified
<(From Left) Dr. Minju Jeong,(UCSD), Prof. Byung Kook Lim (UCSD), Prof. Se-Bum Paik (KAIST)>
Drug addiction carries an extremely high risk of relapse, as cravings can be reignited by minor stimuli even long after one has stopped using. Previously, this phenomenon was attributed to a decline in the function of the prefrontal cortex (PFC), which regulates impulses. However, a joint international research team has recently revealed that the cause of addiction relapse is not a simple decline in brain function, but rather an imbalance in specific neural circuits.
KAIST announced on March 9th that a research team led by Prof. Se-Bum Paik from the Department of Brain and Cognitive Sciences and Prof. Byung Kook Lim from the University of California, San Diego (UCSD) has identified the core principle by which specific inhibitory neurons in the prefrontal cortex regulate cocaine-seeking behavior.
In particular, the research team focused on parvalbumin-positive (PV) inhibitory neurons, which regulate the balance of neural signals by suppressing the activity of other neurons in the brain. They confirmed that these cells act as a "brake gate" that controls excitatory signals in the brain and serve as a crucial factor in determining drug-seeking behavior that emerges after withdrawal.
The prefrontal cortex (PFC) of our brain can properly perform its "braking" function to suppress impulses when excitatory and inhibitory signals are in balance. To investigate how chronic drug exposure disrupts this balance, the research team conducted cocaine administration experiments on mice. During this process, they tracked when inhibitory neurons in the PFC were activated and how they sent signals to downstream brain regions.
The experimental results showed that parvalbumin (PV) cells, which account for about 60-70% of the inhibitory neurons in the PFC, were highly active when the mice attempted to seek cocaine. However, when "extinction training"—training to stop seeking the drug—was conducted, the activity of these cells significantly decreased. This demonstrates that the activity patterns of PV cells are not permanently fixed by addiction but can be readjusted through the extinction process.
<Figure 1. Experimental design illustrating cocaine self-administration and longitudinal tracking of prefrontal cortical neural activity during cocaine-seeking behavior>
The research team confirmed that artificially suppressing PV cell activity significantly reduced cocaine-seeking behavior in mice. Conversely, activating these cells caused the drug-seeking behavior to persist even after the extinction process. This effect was specifically observed in drug-addiction behavior and did not appear with general rewards like sugar water. Furthermore, this phenomenon was not observed in somatostatin (SOM) cells—another type of inhibitory neuron—indicating that PV cells selectively regulate drug addiction behavior.
<Figure 2. Comparison of single-neuron activity, population activity patterns, and behavioral modulation of prefrontal inhibitory neurons across different stages of cocaine-seeking behavior>
The team also identified the specific brain circuit through which these PV cells operate. Signals originating from the prefrontal cortex are transmitted to the reward circuit of the Ventral Tegmental Area (VTA), a key brain region related to reward. This pathway emerged as the central channel for regulating addiction behavior, determining whether or not to seek the drug again. In this process, PV neurons act as a "regulatory switch," controlling the flow of signals to influence dopamine signaling and deciding whether to maintain or suppress addictive behavior.
In short, the study revealed that addiction relapse is not due to an overall functional decline of the prefrontal cortex, but is determined by whether PV neurons regulate the neural pathway connecting the PFC to the reward circuit.
<Figure 3. Schematic illustrating the prefrontal–reward circuit mechanism that determines drug-seeking behavior>
Prof. Se-Bum Paik stated, "This research shows that drug addiction is a circuit-level problem arising from a collapse in the regulatory balance of specific neurons and downstream neural circuits. The discovery that parvalbumin (PV) cells act as a 'gate' for addictive behavior will provide a crucial lead for developing precision-targeted treatment strategies in the future."
This study was led by Dr. Minju Jeong (UCSD) as the first author, with Prof. Byung Kook Lim (UCSD) and Prof. Se-Bum Paik (KAIST) serving as co-corresponding authors. The findings were published online on February 26 in Neuron, a premier journal in the field of neuroscience.
Paper Title: Distinct Interneuronal Dynamics Selectively Gate Target-Specific Cortical Projections in Drug Seeking
DOI: 10.1016/j.neuron.2026.01.002
Full Author List: Minju Jeong, Seungdae Baek, Qingdi Wang, Li Yao, Eun Ji Lee, Arturo Marroquin Rivera, Joann Jocelynn Lee, Hyeonseok Jang, Dhananjay Bambah-Mukku, Christine Hyun-Seung Mun, Tyler Boesen, Sumit Nanda, Cheol Ryong Ku, Hong-wei Dong, Benoit Labonté, Se-Bum Paik, and Byung Kook Lim.
This research was conducted with the support of the Basic Research Program in Science and Engineering of the National Research Foundation of Korea.
2026.03.10 View 1211 -
KAIST Team Led by Dong-won Lee Wins Grand Prize at the 2nd Global Quantum AI Competition
< (From Left) M.S candidate Dongwon Lee from School of Electrical Engineering, Ph.D candidate Jaehun Han from Graduate School of Quantum Science and Technology >
"Team Yangja-jorim," consisting of Dongwon Lee, Gyungjun Kim and Jaehun Han , has been honored with the Grand Prize at the '2026 2nd Global Quantum AI Competition.' The event was hosted and organized by NORMA, a specialized quantum computing company.
This global competition was designed to expand hands-on experience with quantum cloud services and to discover next-generation talent in the field of quantum artificial intelligence. The event spanned approximately 70 days, beginning with the preliminary opening ceremony held at Korea University’s Hana Square on December 17 last year. The final winners were announced during an awards ceremony held at NORMA's headquarters on the 27th of last month.
The competition attracted significant interest from quantum technology talent worldwide, including university students, developers, and researchers. A total of 137 teams participated in the preliminaries, with the top 10 teams advancing to the finals—a competitive ratio of approximately 13.7 to 1.
< An acquaintance attended the awards ceremony of the 2nd Global Quantum AI Competition to accept the prize on behalf of the team. >
In the final round, participants were presented with four generative problems utilizing the Quantum Circuit Born Machine (QCBM) model. To overcome the current limitations of quantum machine learning, the contestants were tasked with designing and validating Quantum-Classical Hybrid Generative AI models that integrate classical techniques. Notably, the final problem provided an opportunity to verify the proposed methods using a real Quantum Processing Unit (QPU) from Rigetti Computing, a leading global quantum computing firm.
The judging process employed a double-blind system, where the identities of both evaluators and participants remained undisclosed to ensure maximum fairness and credibility.
"Through this competition, we were able to explore the research potential of the quantum AI field more deeply," said KAIST's Team Yangja-jorim in their acceptance speech. "We hope to continue contributing to the advancement of quantum technology through consistent research and new challenges."
2026.03.10 View 1291 -
KAIST Develops mRNA Platform That Remains Effective Even in Aging and Obesity
<(From Left) Dr. Subin Yoon, Ph.D candidate Hyeonggon Cho, Prof. Jae-Hwan Nam, Prof. Young-suk Lee>
Since the COVID-19 pandemic, mRNA vaccines have gained attention as a next-generation pharmaceutical technology. mRNA therapeutics work by delivering genetic instructions that enable cells to produce specific proteins for therapeutic effects. However, their efficacy has been reported to decline in elderly individuals or patients with obesity. To address this limitation, Korean researchers have newly designed a key regulatory region of mRNA that improves therapeutic protein production efficiency, developing a next-generation mRNA platform that maintains effectiveness even in aging and obesity conditions.
KAIST (President Kwang Hyung Lee) announced on the 10th of March that a joint research team led by Professor Young-suk Lee of the Department of Bio and Brain Engineering and Professor Jae-Hwan Nam of The Catholic University of Korea (President Jun-Gyu Choi) has developed a new mRNA platform by precisely designing the sequence of the 5′ untranslated region (5′UTR)*, a key regulatory region of mRNA.*5′ untranslated region (5′UTR): A region of mRNA that initiates and regulates protein production. The design of this region influences both the amount and speed of protein synthesis.
The research team analyzed large-scale bioinformatics datasets to identify 5′UTR sequences that enable proteins to be produced more efficiently across diverse cellular environments. When applied, the designed sequences significantly enhanced protein production and immune responses even in preclinical models of aging and obesity.
mRNA is a long single-stranded RNA molecule that serves as the blueprint for producing proteins required by the body. It consists of several components: the 5′UTR, which initiates and regulates the rate of protein production; the coding sequence (CDS), which contains the genetic information for a specific protein; the 3′ untranslated region (3′UTR), which helps maintain mRNA stability within cells; and the poly(A) tail, which further enhances stability and supports protein synthesis.
Among these components, the 5′UTR and 3′UTR do not determine the type of protein produced, but they play a critical role in regulating how efficiently the protein is synthesized. For this reason, these regions are receiving increasing attention as key bioengineering platforms for improving the performance of various mRNA therapeutics, including vaccines and treatments.
<Schematic Diagram of mRNA Therapeutic Design and Validation Using Bioinformatics>
To identify highly efficient 5′UTR sequences capable of promoting protein production across multiple tissues and cellular environments, the team conducted an integrated analysis of large-scale biological datasets. This included multiple analytical approaches such as RNA sequencing (RNA-seq) for analyzing gene activity across tissues, single-cell RNA sequencing (scRNA-seq) for examining gene expression at the individual cell level, and ribosome profiling (Ribo-seq) for measuring actual protein translation efficiency.
The researchers also focused on the fact that in aging or obesity conditions, cells often experience high levels of stress—particularly oxidative stress—which can reduce their ability to synthesize proteins. When the newly designed mRNA therapeutics were applied to preclinical models of aging and obesity, the results showed significantly improved protein production and immune responses compared with existing approaches. This research is expected to be applicable not only to mRNA vaccines but also to a wide range of biopharmaceutical technologies, including gene therapies and immunotherapies.
<Multimodal Bio–Big Data Analysis–Based mRNA Therapeutic Design (AI-Generated Image)>
Professor Young-suk Lee of KAIST Department of Bio and Brain Engineering stated, “This study identified a design strategy that enables mRNA to produce proteins more efficiently by analyzing large-scale biological data,” adding, “This technology will provide an important foundation for ensuring that mRNA vaccines and therapeutics remain effective even in environments where drug efficacy may decline, such as in elderly or obese patients.”
In this study, Dr. Subin Yoon from The Catholic University of Korea and doctoral candidate Hyeonggon Cho from KAIST participated as co-first authors. The research findings were published online on January 2 in the internationally renowned journal Molecular Therapy (IF = 12.0), a leading journal in gene and cell therapy.
(Paper title: ”Designing 5′UTR sequences improves the capacity of mRNA therapeutics in preclinical models of aging and obesity” DOI: https://doi.org/10.1016/j.ymthe.2025.12.060)
This research was supported by the Excellent Young Researcher Program and the Bio-Medical Technology Development Program of the National Research Foundation of Korea funded by the Ministry of Science and ICT, the Infectious Disease Response Innovative Technology Support Program of the Ministry of Food and Drug Safety, and the Infectious Disease Prevention and Therapeutics Technology Development Program of the Korea Health Industry Development Institute.
2026.03.10 View 1362 -
AI Developed to Locate Slums Worldwide... Wins Best Paper Award at AAAI 2026
<(From Left) Sumin Lee, Sungwon Park, Prof. Jihee Kim, Prof. Meeyoung Cha, Prof. Jeasurk Yang>
"Cities don't even know where their slums (impoverished areas) are located."
In many developing nations, the most vulnerable citizens are invisible to the state simply because their homes don't appear on any official map. Today, a breakthrough using Artificial Intelligence (AI) is changing that.
A joint research team from KAIST and Chonnam National University in South Korea and MPI-SP in Germany has developed an AI technology that autonomously identifies slum areas using nothing but satellite imagery. This technology is expected to fundamentally transform urban policy-making and public resource allocation in developing countries where data is scarce and has won the Best Paper Award in the ‘AI for Social Impact’ category at the AAAI 2026 (Association for the Advancement of Artificial Intelligence), the world's premiermost prestigious AI academic conference.
Why it Matters
While previous studies struggle to recognize slums across countries due to varying architectural styles, the team introduced a "Mixture-of-Experts (MoE)" structure. In this system, multiple AI models learn different regional characteristics; when a new city is inputted, the system automatically selects the most appropriate model.
<Figure1. Overview of the Mixture-of-Experts(MoE) structure to identify slum areas>
The core of this research is "Test-Time Adaptation (TTA)" technology. Even if humans do not pre-mark slum locations in a new city, the AI reduces its own errors by comparing and verifying the prediction results of multiple models, trusting only the areas where they commonly agree. This ensures stable performance even in regions with insufficient data.
The research team applied this technology to major cities such as Kampala (Uganda) and Maputo (Mozambique) and confirmed that it distinguishes slum areas more precisely than existing state-of-the-art technologies.
This technology is expected to be utilized in various policy fields, including:
Establishing urban infrastructure expansion plans for developing countries.
Identifying areas vulnerable to disasters and infectious diseases in advance.
Selecting targets for housing environment improvement projects.
Monitoring the implementation of UN Sustainable Development Goals (SDGs).
<Figure2. Slum segmentation results in Kampala in 2015 (yellow) and 2023 (red). Over the eight-year period, the slum ratio in the city increased from 8.4% to 8.6%>
Meeyoung Cha, an AI researcher and author, stated, "This research proves that AI is no longer just a tool for analysis. It is a tool for action. Our technology can bridge the data gap to solve the world’s most pressing social challenges." Jihee Kim, an economist and author, added, "It will complement costly field surveys and help effectively allocate limited resources to the areas that need them most."
The research results were presented at AAAI 2026 in Singapore on January 25th.
Paper Title: Generalizable Slum Detection from Satellite Imagery with Mixture-of-Experts
Paper Link: https://aaai.org/about-aaai/aaai-awards/aaai-conference-paper-awards-and-recognition/
This research was supported by the National Research Foundation of Korea (NRF) through the Mid-career Researcher Support Program and the Data Science Convergence Human Resources Training Program.
2026.03.08 View 1055 -
Professor Kuk-Jin Yoon’s Research Team at the Department of Mechanical Engineering Achieves Landmark Success with 10 Papers Accepted at CVPR 2026
<Professor Kuk-Jin Joon from Department of Mechanical Engineering>
Professor Kuk-Jin Yoon’s research team from our university’s Department of Mechanical Engineering has once again demonstrated its overwhelming academic prowess by having a total of 10 papers accepted as lead authors at the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2026 (CVPR 2026).
CVPR is the most influential international conference in the fields of artificial intelligence and visual intelligence. Since its inception in 1983, it has selected outstanding research through a rigorous peer-review process every year. For CVPR 2026, a total of 16,092 papers were submitted worldwide, with 4,090 accepted, resulting in a competitive acceptance rate of approximately 25.42%. Achieving 10 accepted papers as lead or corresponding authors from a single laboratory is regarded as an exceptionally rare and world-class feat.
Professor Kuk-Jin Yoon’s team conducts extensive research with the ultimate goal of achieving human-level visual intelligence. The papers accepted this year cover cutting-edge topics in computer vision, including:
Event camera-based technologies
Perception technologies for autonomous driving
AI optimization and adaptation techniques
This achievement follows the team's remarkable success at ICCV 2025 last year, where they published 12 papers as lead/corresponding authors. The results at CVPR 2026 further solidify the laboratory's position as a global hub for pioneering computer vision research. The research team plans to continue contributing to the advancement of future AI technologies by tackling challenging research that transcends the limitations of existing methods.
Meanwhile, CVPR 2026 is scheduled to be held in Denver, Colorado, USA, from June 3 to June 7.
<CVPR 2026 (Denver, USA)>
2026.03.06 View 2512 -
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 1762 -
See You at KAIST: Freshman Keeps His Promise as 2026 Matriculation Ceremony Begins
<2026 Undergraduate Matriculation Ceremony>
KAIST announced that it will hold the 2026 Undergraduate Matriculation Ceremony today, February 25, at 10:00 AM in the Auditorium of the Main Campus in Daejeon. The event marks the first step for freshmen who will lead the future of South Korea’s science and technology.
In his welcoming remarks, President Kwang Hyung Lee plans to emphasize that “KAIST is a university built upon a spirit of inquiry that never stops questioning and a drive for challenge that does not fear failure.” He will encourage the students, stating, “I hope you challenge yourselves to your heart's content, and even if you fall, stand back up to blaze new trails that the world has never seen before.”
President Lee will also highlight that the role of talent in science and technology is more critical than ever in this era of massive transformation driven by Artificial Intelligence (AI) and digital transition. He plans to urge students to grow into responsible scientists and engineers who contribute to humanity and society through cooperation and communication, adding, “KAIST will spare no effort in supporting you to ensure your challenges become a reality.”
Marking the 40th class of incoming freshmen, this year’s ceremony will be attended by approximately 1,500 people, including students, parents, and distinguished guests, to celebrate this new beginning.
The speech by Junseop Shin, the student representative taking the podium, begins with the theme of a “promise.” He plans to share how the words “See you at KAIST,” spoken to him by President Kwang Hyung Lee at a defense industry forum three years ago, turned a vague dream into a definitive goal.
<Student Representative Junseop Shin delivering his speech>
Having contemplated his role in an era where science and technology dictate national competitiveness, Shin chose the challenging path of researching “small drone detection technology” instead of a more stable route. Despite numerous failures, frustrations, and discouragement from those around him, he persevered by remembering that promise, eventually achieving a technical breakthrough that garnered attention from international academic societies.
“I learned that keeping a promise isn't about never falling, but about getting back up every time you do,” Shin plans to say, vowing that his new beginning at KAIST will be a journey of fearless challenge.
The ceremony will also introduce the KAIST AI Future Challenge, themed “New and Innovative Ideas for the Future AI Era.” Any KAIST student can participate individually or as a team to tackle future societal issues with creative and feasible ideas. The winning teams will be honored at the “Education Innovation Day” ceremony in May.
<Students taking the matriculation oath>
Following the matriculation ceremony, an orientation will be held to assist students with their first steps into university life. This will include introductions to freshman programs, as well as essential training on community guidelines, mental health services, violence prevention, and safety education to support the students' stable transition into their studies and research.
Furthermore, the three-day “Freshman Start-up (Saenaegi Saerobaumteo)” will feature a diverse range of programs, including club performances, fairs, campus tours, and a welcoming broadcast festival. Freshmen will have the opportunity to experience KAIST culture firsthand and socialize with seniors and peers to shape their vision for university life.
2026.02.25 View 1264 -
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