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KAIST Signs MOU with Université Paris-Saclay on Behalf of K-STAR
KAIST (President Choongsik Bae) announced on September 9 that, representing K-STAR, a consortium comprising KAIST, GIST, DGIST, UNIST, and POSTECH, it signed a memorandum of understanding (MOU) with Université Paris-Saclay on September 7 to strengthen research cooperation. The signing ceremony took place at Bâtiment Bréguet on the university’s campus.
The agreement was concluded on the occasion of President Lee Jae-myung’s state visit to France. It follows up on plans discussed at the ninth Korea-France Joint Committee on Science and Technology, held in Seoul in April, to expand scientific, technological, and academic exchanges between K-STAR and French universities.
Université Paris-Saclay is one of France’s leading research universities. It is home to a large research and education ecosystem encompassing universities, grandes écoles, and major national research organizations, including the French National Centre for Scientific Research (CNRS) and the French Alternative Energies and Atomic Energy Commission (CEA). The university has internationally recognized strengths across a broad range of fields, from mathematics and physics to artificial intelligence, quantum technology, biology, and engineering.
Under the agreement, K-STAR and Université Paris-Saclay will establish a practical framework for cooperation encompassing student exchanges, mobility programs for early-career researchers, and joint research. They plan to begin by offering research internships through which undergraduate and graduate students can gain experience in laboratories at partner institutions. They will also expand opportunities for exchanges and collaboration among postdoctoral researchers and early-career faculty members.
The two sides will promote joint research in key scientific and technological fields, including artificial intelligence, quantum technology, advanced biotechnology, and advanced materials. They will also facilitate shared access to research infrastructure and organize regular workshops and symposia, enabling researchers to maintain sustained exchanges and develop new collaborative research projects.
The agreement strengthens “Global Connect,” KAIST’s strategy for international cooperation. Through this initiative, KAIST seeks to move beyond conventional university exchanges by closely integrating research, education, and talent mobility. It also aims to expand its global research network in partnership with Korea’s other science and technology-focused universities.
“Global cooperation must move beyond conventional exchanges and evolve into partnerships that combine complementary strengths to create new knowledge and cultivate talent together. By connecting the research capabilities of Université Paris-Saclay and K-STAR, we expect to generate new research achievements in critical fields such as AI, quantum technology, and biotechnology, while further strengthening Korea’s global network in science and technology,” said KAIST President Choongsik Bae.
The agreement is also significant because it expands the educational and research cooperation that KAIST has developed with France over the past 15 years to the K-STAR level.
KAIST also signed a student exchange agreement with CentraleSupélec, a grande école affiliated with Université Paris-Saclay, in 2011. The two institutions subsequently established a dual-degree program in mechanical engineering in 2017 and have continued to develop their partnership. Building on the experience and mutual trust accumulated through this cooperation, the new agreement broadens the partnership to encompass K-STAR and Université Paris-Saclay.
Université Paris-Saclay President Camille Galap said, “Université Paris-Saclay and K-STAR have broad research capabilities spanning basic science and advanced technology, giving this partnership considerable potential. I hope the agreement will promote more active exchanges among students and researchers from both countries and enable us to achieve new scientific advances through joint research.”
Jaemin Jung, KAIST Senior Vice President for Planning and Budget, said, “This agreement marks the beginning of our efforts to translate the university-level cooperation discussed at the ninth Korea-France Joint Committee on Science and Technology in April into concrete research collaboration. KAIST will support exchanges among students and researchers so that they can work in one another’s laboratories and produce tangible outcomes, including joint research projects, publications, and the shared use of research infrastructure.”
The signing ceremony was also attended by Stéphane Nonnenmacher, Director of the Graduate School of Mathematics at Université Paris-Saclay; Divya Madhavan, Director of International Relations at CentraleSupélec; and a delegation from the Korea Institute for Advanced Study (KIAS), a KAIST-affiliated institute.
2026.09.09 View 2169 -
KAIST and Thermo Fisher Scientific to Establish Next-Generation Autonomous Research Hub, “SHARE Hub”
KAIST is partnering with Thermo Fisher Scientific to establish SHARE Hub, a next-generation autonomous research hub where AI designs experiments and robots execute them. The initiative aims to accelerate scientific discovery and drug development by integrating researchers, AI systems, laboratory robotics, and experimental data into a self-driving research environment.
KAIST (President Choongsik Bae) announced on August 27 that it had signed a memorandum of understanding with Thermo Fisher Scientific on August 26 to establish SHARE Hub and pursue broader strategic collaboration.
The MOU signing ceremony brought together KAIST President Choongsik Bae and senior executives from Thermo Fisher Scientific, including Dan Shine, Senior Vice President and President of the Analytical Instruments Group; Soo Jin Seok, Vice President and General Manager for Korea and Taiwan; Manoj Prasad, Vice President of IT & Digital Solutions for Asia Pacific and the Middle East; and Mark Fish, Vice President and General Manager of Digital Science & Automation Solutions.The two institutions will combine KAIST’s multidisciplinary expertise in life sciences, chemistry, medicine, AI, and robotics with Thermo Fisher Scientific’s advanced research equipment and capabilities in laboratory automation and systems integration to establish SHARE Hub.*
*SHARE Hub: A self-driving laboratory connecting human intuition, AI reasoning, robotic execution, and experimental data.
“SHARE Hub is not simply another laboratory equipped with advanced instruments. It is an open-innovation platform where scientists, AI researchers, engineers, and industry partners can jointly develop and validate next-generation autonomous laboratories,” said KAIST President Choongsik Bae. “We expect SHARE Hub to bring KAIST’s ‘Beyond Laboratory’ strategy to life and evolve into a global collaboration model that sets a new standard for the future of scientific research.”
Dan Shine, Senior Vice President and President, Analytical Instruments Group at Thermo Fisher Scientific, said, “As advanced analytical technologies become increasingly connected with AI and automation, the way scientists generate and interpret data and translate it into new discoveries is rapidly evolving. By bringing together KAIST’s outstanding research capabilities with Thermo Fisher Scientific’s analytical technologies and scientific expertise, we look forward to applying and validating new ways of working in real research environments through the SHARE Hub and turning promising ideas into meaningful scientific outcomes.”
SHARE Hub goes beyond conventional laboratory automation, in which machines simply perform predefined tasks. Researchers will formulate scientific questions and set research directions, and then AI will design experiments, robots will execute them, and the resulting data will be fed back into the AI system to inform subsequent experiments.
Recent advances in AI have significantly accelerated the design of new drug candidates. However, synthesizing candidate compounds and evaluating their efficacy and physicochemical properties still require considerable time, cost, and specialized expertise. Existing laboratory automation systems have also faced challenges integrating individual instruments, operating software, and AI systems, making it difficult to analyze results in real time, and autonomously select and execute subsequent experiments.
To overcome these limitations, SHARE Hub will be built around “Digital Plug & Play” and “Physical Plug & Play” architectures, enabling new AI systems, robots, and laboratory instruments to be integrated flexibly. This modular approach will allow rapidly evolving technologies to be introduced into research environments and promptly evaluated for their performance and usability under real-world conditions.
Rather than focusing solely on equipment deployment or experimental automation, the KAIST–Thermo Fisher Scientific partnership will jointly develop the enabling technologies and research methods required for autonomous laboratories. KAIST’s foundational technologies and research ideas in AI, biotechnology, and engineering will be combined with Thermo Fisher Scientific’s research instruments, automation platforms, and systems-integration capabilities. These capabilities will then be integrated, tested, and refined within SHARE Hub.
As part of this effort, the two institutions will launch a “Challenge Program” to develop core AI, robotics, and automation technologies, and apply them to real-world challenges in scientific research and drug discovery. Through the program, KAIST will serve as a co-developer, early adopter, and validation partner, helping drive the development and advancement of emerging technologies.
SHARE Hub is envisioned not as an autonomous laboratory dedicated to a single research team or discipline, but as an open research hub where KAIST researchers from diverse fields can collaborate with external partners to test and apply new technologies. By bringing life sciences, chemistry, and medicine together with AI and robotics, the hub will develop new autonomous experimentation technologies and research methods while addressing real-world scientific challenges.
KAIST plans to gradually expand participation to companies, universities, research institutes, and hospitals in Korea and abroad. In doing so, it aims to develop SHARE Hub into an open-innovation testbed for the joint development and validation of research equipment and AI, robotics, and automation technologies. The ultimate goal is to establish SHARE Hub as a global benchmark for autonomous science and drug discovery, pioneering new research methods and sharing the resulting technologies with research communities worldwide.
“SHARE Hub is not merely about automating experiments. Its central purpose is to connect researchers with technologies that enable AI and robots to tackle real scientific questions,” said Hee-Seung Lee, Dean of the KAIST College of Natural Sciences and Director of the InnoCORE AI-CRED Institute (AI Co-Research & Education for Innovative Drug). “We plan to develop the hub into an open research environment where researchers from different disciplines and industry partners can jointly develop and validate new technologies.”
KAIST also held the “KAIST–Thermo Fisher Scientific Mini-Symposium for SHARE” on the afternoon of August 26. During the symposium, KAIST researchers presented their latest work in major areas of autonomous science, including autonomous drug discovery, AI-driven protein design, next-generation therapeutics, and autonomous chemical experimentation.
At the symposium, Mark Fish, Vice President and General Manager of Digital Science & Automation Solutions at Thermo Fisher Scientific, presented a vision for the future of autonomous science and drug discovery. Building on the discussions at the event, the two institutions explored future directions and plans for collaborative research.
2026.08.27 View 2692 -
KAIST Teams Win Both International Challenges at ICRA 2026 and CVPR 2026
Two research teams from KAIST have claimed first place in international challenge competitions held at the world’s premier robotics and computer vision conferences.
KAIST (President Kwang-Hyung Lee) announced that the ACDC-K Team and the Curaytor Team, both from the laboratory of Prof. Hyun Myung in the School of Electrical Engineering, won first place in international challenge competitions held in conjunction with the IEEE International Conference on Robotics and Automation (ICRA 2026) and the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2026), respectively.
The achievement highlights the global competitiveness of KAIST’s robotic perception and spatial intelligence technologies, with two teams from the same laboratory securing victories in leading international competitions across distinct research fields.
The ACDC-K Team won first place among more than 60 participating teams in the SLAM (Simultaneous Localization And Mapping) category of the Hilti×Trimble SLAM Challenge 2026, held during the Open Challenges in Robotics for Asset Inspection (OCRAIM) Workshop at ICRA 2026 in Vienna, Austria, from June 1 to 5.
Jointly organized by Hilti, Trimble, and the University of Oxford, the challenge evaluates robotic localization and mapping performance using sensor data collected from real construction sites. Participants were required to address practical challenges frequently encountered in construction environments, including non-overlapping front and rear fisheye camera configurations, low-texture indoor scenes, and rapid camera motion.
To tackle these challenges, the ACDC-K Team developed a robust visual-inertial SLAM system that fuses front and rear fisheye camera data with inertial measurements. By integrating feature-point and feature-line observations with adaptive constraints and correction mechanisms, the team achieved highly reliable localization and mapping performance in complex construction environments.
Meanwhile, the Curaytor Team won first place among eight participating teams in the Nothing Stands Still (NSS) Challenge 2026, held during the Computer Vision for the Built World (CV4AEC) Workshop at CVPR 2026 in Denver, Colorado, from June 3 to 7.
Jointly organized by Stanford University, ETH Zurich, and Oregon State University, the NSS Challenge evaluates 3D point cloud registration technologies for construction and industrial environments that evolve over time.
The Curaytor Team developed a novel multi-registration framework capable of aligning multiple LiDAR scans collected across different times and locations. The framework integrates feature extraction, correspondence estimation, robust global registration, registration confidence assessment, and change-aware refinement techniques. As a result, the team achieved highly accurate registration performance even in environments containing structural changes and dynamic objects.
“This achievement demonstrates the robustness of our visual-inertial SLAM and 3D LiDAR registration technologies in complex and constantly changing real-world environments,” said Prof. Hyun Myung. “It is particularly meaningful that our students secured first-place finishes in highly competitive international challenges hosted at two of the world’s most prestigious conferences in robotics and computer vision.”
Prof. Hyun Myung’s laboratory has consistently demonstrated excellence in spatial intelligence research. The laboratory previously won first place in the LiDAR track and ranked first among academic teams in the vision track of the Hilti SLAM Challenge in 2023. In addition, the Curaytor Team successfully defended its title in the NSS Challenge, securing back-to-back championships in 2025 and 2026.
2026.06.19 View 7645 -
KAIST holds Global Science and Technology Cooperation Forum… Discusses sustainable international cooperation measures
KAIST announced on June 11th that the Global Center for Development and Strategy (G-CODEs) hosted the "Forum on Global Cooperation in Science and Technology: Beyond Crisis, Toward Sustainable Cooperation" at the KAIST Academic Cultural Complex on June 10th.
This forum was organized to review South Korea's international cooperation strategies and execution capabilities under a rapidly changing environment for international cooperation in science and technology, driven by intensifying competition for technological hegemony, restructuring of global supply chains, and rising uncertainty in energy security.
In particular, this forum was organized as a follow-up event to the 'Global Science and Technology Cooperation Forum: Reflection and Outlook' held last year. While last year's forum discussed South Korea's response strategies amid the restructuring of the global science and technology order, this year's forum continued the discussion with a focus on more specific cooperation tasks, such as execution capabilities and institutional foundations for international cooperation, fostering professional talent, international joint research, and research security.
Beginning with opening remarks by Sang-wook Kang, Director General for Planning and Coordination at the Ministry of Science and ICT, the forum proceeded with a total of three sessions.
In the first session, 'Restructuring Science and Technology International Cooperation in the Era of Techno-Geopolitics,' So Young Kim, Vice President of International Office at KAIST, served as the chair to discuss the direction of international cooperation in science and technology according to changes in the economic security and techno-geopolitical environment. Wonho Yeon, Director at Hyundai Motor Group Global Policy Office, presented global cooperation strategies in the era of economic security; Eunkyo Cho, Head of Team at the Korea Institute for Industrial Economics & Trade (KIET), presented the potential for Korea-China cooperation in the era of physical AI; and Inkyoung Sun, Research Fellow at the Science and Technology Policy Institute (STEPI), presented the importance of research security for international joint research. Subsequently, Damian Bank, Professor at the Global Center for Development and Strategy (G-CODEs) at KAIST, and Chaegwon Lim, Professor at the School of Electrical Engineering at KAIST, participated in the panel discussion.
In the second session, 'International Joint Research: Issues and Challenges,' Jae-Yong Choung, Professor at the Graduate School of Science and Technology Policy at KAIST, served as the chair to address practical experiences and institutional challenges of international joint research. Eunseong Kim, Professor at the Department of Physics and the Graduate School of Quantum Science and Technology at KAIST, shared the experiences of the KAIST-MIT global partnership, and Dr. Hae-Jung Lee from the National Institute of Standards and Technology (NIST) in the United States presented South Korea's collaborative capabilities and areas for improvement from the perspective of an overseas partner.
Seokkyun Woo, Professor at the Graduate School of Science and Technology Policy at KAIST, analyzed the current status and characteristics of international cooperation research by government-funded research institutes currently being conducted by the G-CODEs research center, and discussed directions for improving the international cooperation support system. Ju Young Kim, Policy Officer at the Delegation of the European Union to the Republic of Korea, and Hyerin Park, Center Head at the Korea Research Institute of Standards and Science (KRISS), participated in the panel discussion.
In the third session, 'Fostering Talent for Science and Technology International Cooperation,' Sukyung Park, Professor at the Department of Mechanical Engineering at KAIST, served as the chair to discuss fostering professional talent and institutional foundations for international cooperation. EunJu Jun, Director at the Korea Atomic Energy Research Institute (KAERI), Mi-Jung Um, Center Head at the Science and Technology Policy Institute (STEPI), Jonghoon Moon, Deputy Director at the Ministry of Science and ICT, Jinyeob Na, Deputy Director at the Ministry of Foreign Affairs, and Eun Jung Koh, Head of Division at the Korea Institute of Human Resources Development in Science and Technology (KIRD), participated as panelists to discuss ways to foster convergence talent, capabilities and training required for practical personnel in international cooperation, career development, and establishing support systems.
Kyung Ryul Park, Director of the Global Center for Development and Strategy (G-CODEs) at KAIST, said, "This forum was a venue to examine the changes and challenges surrounding international cooperation in science and technology and to seek sustainable cooperation measures. Reflecting its recently surging importance, students and participants showed high interest in nurturing future convergence talent for international cooperation in science and technology."
Kwang Hyung Lee, President of KAIST, stated, "International cooperation in science and technology is an important foundation for national competitiveness and future growth. I hope this forum serves as an opportunity to seek sustainable methods for international cooperation in science and technology amid a rapidly changing global environment." (End)
※ Forum Presentation Materials: Global Center for Development and Strategy Website (https://global.kaist.ac.kr/)
<Forum on Global Cooperation in Science and Technology>
2026.06.11 View 3410 -
Professor Hoon Sohn of the Department of Civil and Environmental Engineering Selected as the June Winner of the 'Korea Scientist and Engineer Award'
Professor Hoon Sohn from KAIST Department of Civil and Environmental Engineering has been selected as the June winner of the 'Korea Scientist and Engineer Award.'
The Korea Scientist and Engineer Award is presented monthly by the Ministry of Science and ICT (MSIT) and the National Research Foundation of Korea (NRF) to a researcher who has made significant contributions to the advancement of science and technology through original research achievements over the past three years. The award includes a commendation from the Deputy Prime Minister and Minister of Science and ICT, along with a cash prize of 10 million KRW.
Professor Hoon Sohn was recognized for his contributions to developing an affordable, high-precision displacement sensor technology capable of detecting disaster and hazard risks in small-to-medium-sized infrastructure in real-time.
With the rapid aging of infrastructure such as bridges and buildings in recent years, the importance of technology that continuously monitors the structural safety of facilities has been growing. However, small-to-medium-sized structures—which make up the vast majority of infrastructure worldwide—exhibit very subtle movements on a millimeter scale, requiring highly precise measurement. Moreover, existing equipment is prohibitively expensive, making widespread adoption difficult.
To overcome these limitations, Professor Sohn combined millimeter-wave (mmWave) radar with Micro-Electro-Mechanical Systems (MEMS) accelerometers and applied signal processing algorithms. Through this, he successfully developed a technology that can simultaneously measure a structure's vibration, tilt, and displacement with a single sensor.
The production cost of this sensor is under 1 million KRW, which is approximately 1/40th the cost of conventional equipment, yet it boasts a high precision of 0.026 mm. Its power consumption has also been reduced to 1/100th of existing systems. Furthermore, it incorporates energy harvesting technology that utilizes ambient wasted energy, allowing for completely wireless operation.
The reliability of this technology has been proven through field demonstrations at more than 13 domestic and international sites, including a parking garage at Stanford University (USA), a highway in San Jose (USA), a bridge in Weifang (China), and the Geumgang Pedestrian Bridge in Sejong (South Korea).
Professor Sohn stated, "The significance of this research lies in establishing a technological foundation to precisely manage small-to-medium-sized structures that have previously been excluded from continuous, routine monitoring." He added, "Moving forward, I will continue my research on AI-based digital twins to lead the automation, unmanned operation, and intelligent advancement of the safety diagnosis market, thereby contributing to public safety and disaster prevention."
2026.06.04 View 3741 -
KAIST Produces Eco-Friendly Core Nylon Precursors Used from Clothing to Automobiles with Microbes
<(From Left) Dr. Da-Hee Ahn, Distinguished Professor Sang Yup Lee>
Nylon is a representative plastic material used throughout our daily lives, from clothing to automobiles. However, most of its raw materials have been produced through petrochemical processes, resulting in large carbon emissions. KAIST researchers have developed a technology that can produce key nylon precursors in an eco-friendly way using microbes.
KAIST (President Kwang Hyung Lee) announced on the 31st of May that a research team led by Distinguished Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering has developed an Escherichia coli-based modular platform capable of producing three key monomers (basic molecular units that make up polymers) of “nylon 6,6” and “nylon 6” — adipic acid, hexamethylenediamine, and epsilon-caprolactam — from “glycerol (an eco-friendly bio-based byproduct generated during biodiesel production),” a renewable carbon source, using systems metabolic engineering (a technology that designs and optimizes microbial metabolic pathways to maximize the production of desired substances).
“Nylon 6” is highly flexible and is used in clothing and films, while “nylon 6,6” has excellent strength and heat resistance and is used in automobiles and machinery parts. The numbers after the nylon name indicate the number of carbon atoms contained in the raw material molecules.
The core of this study is that the biosynthetic pathway was divided into upstream and downstream modules, with E. coli strains assigned different roles. The upstream strain was designed to produce adipic acid from glycerol, while the downstream strain was designed to convert it into hexamethylenediamine or epsilon-caprolactam, respectively. Through this, the research team succeeded in producing adipic acid and hexamethylenediamine, the key raw materials of nylon 6,6, and epsilon-caprolactam, the key raw material of nylon 6, within a single integrated platform.
To improve production efficiency, the researchers compared and validated various enzymes (proteins that promote chemical reactions in living organisms), including carboxylic acid reductases and transaminases, and applied the optimal combination, thereby improving hexamethylenediamine titer. In addition, in the epsilon-caprolactam production process, they designed a flexible-linker fusion enzyme that enhances reaction efficiency through efficient cofactor regeneration.In the upstream module, the team reconstructed the biosynthetic pathway (a series of reaction processes through which compounds are produced in living organisms) and improved the performance of key enzymes using artificial intelligence (AI), increasing production titer. As a result, they succeeded in producing adipic acid at a level of 6 grams per liter (g/L) in a fed-batch fermentation process.
The research team also applied a “delayed inoculation” strategy (time-staggered co-culture), in which the second strain is introduced later after sufficient adipic acid has first been produced, rather than adding the two types of E. coli simultaneously. This is a method of sequentially introducing microbes with different roles at different times.
When this strategy was applied to a fed-batch fermentation process (a fermentation method that increases productivity by supplying nutrients step by step), the team produced 230 milligrams per liter (mg/L) of hexamethylenediamine and 808 micrograms per liter (μg/L) of epsilon-caprolactam using only glycerol. Although the production amounts are not yet high, the research team explained that these results represent world-class performance among cases of direct production from glycerol.
<Schematic Diagram>
This technology is significant in that it presents the possibility of producing nylon raw materials, which have relied on petrochemical processes, through bio-based methods.
The research team plans to further improve titer by combining AI-based enzyme design with additional systems metabolic engineering, and to expand the platform to produce various polymer raw materials (substances formed by the repeated bonding of multiple monomers).
Distinguished Professor Sang Yup Lee stated, “This study is meaningful in that it presents a modular microbial platform capable of producing key monomers required for nylon 6 and nylon 6,6 production from renewable carbon sources,” adding, “We will continue to advance enzyme and metabolic flux engineering to improve titer and develop this into a core platform for sustainably producing various bio-based polymer raw materials.”
The results of this study were published on May 4 in the Proceedings of the National Academy of Sciences (PNAS), with Dr. Da-Hee Ahn of the Department of Chemical and Biomolecular Engineering as the first author.
※ Paper title: “Metabolic engineering of Escherichia coli for the biosynthesis of nylon 6 and nylon 6,6 monomers”
Authors: Sang Yup Lee (KAIST, corresponding author), Da-Hee Ahn (KAIST, first author), Tong Un Chae (KAIST, second author), total of 3 authors
DOI: https://doi.org/10.1073/pnas.2535786123
This research was supported by the “Development of Platform Technologies of Microbial Cell Factories for the Next-Generation Biorefineries” project under the Petroleum Replacement Eco-Friendly Chemical Technology Development Program supported by the Ministry of Science and ICT, and by the “Development of Advanced Synthetic Biology Source Technologies for Leading the Biomanufacturing Industry” project under the Core Synthetic Biology Technology Development Program.
2026.06.01 View 3679 -
KAIST Develops Self-Regenerating Catalyst That Restores Its Own Performance, Opening a Breakthrough for CO₂ Conversion Technology
<(From Left) Professor Dong Young Chung, Ph.D Candidate Hongmin An, Hanjoo Kim>
Technologies that convert carbon dioxide (CO₂) emitted from factories and power plants into useful chemical feedstocks are considered key to achieving carbon neutrality. However, rapid degradation of catalyst performance has long hindered commercialization. KAIST researchers have now developed a “self-regenerating” catalyst that restores its activity during operation, offering a potential solution to this challenge.
KAIST (President Kwang Hyung Lee) announced on the 11th of March that a research team led by Professor Dong Young Chung from the Department of Chemical and Biomolecular Engineering has identified the fundamental cause of catalyst degradation in electrochemical reactions that convert CO₂ into useful materials and has developed a new design strategy that allows catalysts to maintain their active state during the reaction.
<Schematic Illustration of Copper Catalyst Reconstruction>
The research team focused particularly on copper (Cu) catalysts, which are widely used in CO₂ conversion reactions. Copper catalysts are known not to simply degrade during reactions but instead undergo a process called surface reconstruction, in which their surface structure continuously changes. The study revealed that the performance and lifetime of the catalyst vary significantly depending on how this reconstruction occurs.
The researchers discovered that copper catalyst reconstruction occurs mainly through two different mechanisms. The first involves formation and reduction of oxide layers on the catalyst surface. While this temporarily increases catalytic activity, it ultimately leads to long-term degradation of catalyst performance.
The second mechanism involves partial dissolution of the catalyst metal into the electrolyte followed by redeposition onto the catalyst surface. During this process, new reactive sites—known as active sites—are continuously created on the catalyst surface.
Based on this mechanism, the team proposed a method that allows the catalyst to maintain its active state during the reaction. By introducing a trace amount of copper ions into the electrolyte, dissolution and redeposition of copper occur in a balanced cycle on the catalyst surface. This continuous cycle generates new active sites, enabling the catalyst to maintain stable performance over extended periods.
Importantly, this technology can be implemented without complex additional processes or high-voltage conditions, significantly reducing energy consumption while enabling stable production of high-value C₂ compounds such as ethylene and ethanol. C₂ compounds are molecules containing two carbon atoms and are industrially important chemicals used as feedstocks for plastics, fuels, and other materials.
This research is significant because it proposes a new design concept in which catalysts are not merely optimized at the initial stage but are engineered to maintain their optimal state throughout the reaction process. The concept is expected to be applicable not only to CO₂ conversion technologies but also to a wide range of electrochemical energy conversion systems.
Professor Dong Young Chung stated, “This research approached catalyst degradation not as an inevitable phenomenon but as a controllable process,” adding, “We proposed a new strategy that allows catalysts to continuously maintain optimal activity during the reaction.”
The study was led by Hanjoo Kim, a doctoral student at KAIST, and Hongmin An, a combined master’s-doctoral student, as co-first authors. The research was published online on February 5 in the Journal of the American Chemical Society (JACS), one of the world’s most prestigious journals in chemistry.
※ Paper title: “Dynamic Interface Engineering via Mechanistic Understanding of Copper Reconstruction in Electrochemical CO₂ Reduction Reaction” DOI: 10.1021/jacs.5c16244
This research was supported by the Global Young Connect Program for Materials and the National Strategic Materials Technology Development Program funded through the National Research Foundation of Korea.
2026.03.11 View 4455 -
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 3902 -
KAIST Explores Solutions for African Youth Employment with World Bank and African Union
< Group photo of meeting participants >
KAIST announced on the 6th that the 'Jobs for Youth in Africa Knowledge Exchange' platform was held in Nairobi, Kenya, from March 3 to 5 (local time). The event was hosted by the Kenyan government and co-organized by the World Bank Group, the African Union, and the KAIST Global Center for Development and Strategy (G-CODEs).
As a high-level policy implementation platform dedicated to addressing youth employment challenges in Africa, the event drew approximately 200 participants, including government officials from over 20 African nations, international organizations, the private sector, academia, and development cooperation partners. KAIST participated as a key global partner linking technology and policy, presenting innovation models for employment systems based on digital and Artificial Intelligence (AI) technologies.
< Scene from the meeting hosted by the Kenyan government >
With Africa’s youth population projected to double by 2050, the continent faces significant hurdles such as high unemployment rates and informal employment. This event marked the second face-to-face meeting of the 'Jobs for Youth in Africa Community of Practice (CoP),' which was launched in Kigali, Rwanda, in 2025. The meeting aimed to share policy experiences among member states and materialize scalable implementation models. Salim Mvurya, Kenya's Cabinet Secretary for Youth Affairs, Creative Economy, and Sports, attended the opening ceremony and emphasized that youth job creation is a critical priority at both national and continental levels.
The program focused on several key themes:
Evidence-based youth employment strategies
Innovation in employment systems through digital and AI technologies
Improving labor market outcomes through Recognition of Prior Learning (RPL)
Business environment reforms and strengthening value chain linkages
Notably, in the session titled "Digital and AI-based Employment System Innovation," Professor Kyung Ryul Park of KAIST shared Korea’s digital transformation experiences and AI application cases, proposing directions for data-driven policy design and the development of technology-based employment platforms. Additionally, KAIST Professor Ga-young Park facilitated mutual learning and connected cases of scalable youth employment projects across countries during the "Global Cafe Session."
< Professor Kyung Ryul Park of KAIST delivering a presentation >
Participants visited the project site of "National Youth Opportunities Towards Advancement (NYOTA)," an initiative pursued by the Kenyan government and the World Bank. There, they observed a comprehensive youth employment model that integrates vocational training, job matching, and entrepreneurship support. The site visit served as a practical learning opportunity to share the processes of policy design and execution.
Since last year, KAIST has been involved in digital innovation projects for youth employment in East Africa through the Korea-World Bank Partnership Facility (KWPF). Through this event, the university reaffirmed its status as a global cooperation hub leading technology-based policy innovation.
"The issue of youth employment is a structural challenge that combines digital transformation, industrial strategy, and educational reform," stated Professor Kyung Ryul Park. "KAIST will continue to present actionable policy models based on data and technology while strengthening international cooperation."
This Knowledge Exchange platform is evaluated as a significant milestone that reaffirmed the African youth employment agenda as a core priority of international cooperation and solidified the foundation for enhancing policy implementation capabilities. A follow-up workshop is scheduled to be held early next year at the Kenya Advanced Institute of Science and Technology (Kenya-AIST) campus in Konza, Nairobi, which is modeled after KAIST.
2026.03.10 View 4549 -
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 5062 -
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 7521 -
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 5410