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King Saud University and KAIST discussed Strategic AI Partnership
<From left> President Abdulla Al-Salman(King Saud University), President Kwang Hyung Lee(KAIST)
KAIST (President Kwang Hyung Lee) and King Saud University (President Abdulla Al-Salman) held a meeting on July 3 at the KAIST Campus in Seoul and agreed to pursue strategic cooperation in AI and digital platform development. The global AI landscape is increasingly polarized between closed models developed by the U.S. and China’s nationally focused technology ecosystems. In this context, many neutral countries have consistently called for an alternative third model that promotes both technological diversity and open access. President Lee has previously advocated for a "Tripartite Platform Strategy" (三分之計), proposing an international collaboration framework based on open-source principles to be free from binary digital power structures and foster cooperative coexistence.
This KAIST-KSU collaboration represents a step toward developing a new, inclusive AI model. The collaboration aims to establish an innovative multilateral framework, especially within the MENA, Japan, Korea, and Southeast Asia, by building an open-source-based AI alliance. Both institutions bring complementary strengths to the table. Saudi Arabia possesses large-scale capital and digital infrastructure, while Korea leads in core AI and semiconductor technologies, applied research, and talent cultivation.
Together, the two nations aim to establish a sustainable collaboration model that creates a virtuous cycle of investment, technology, and talent. This initiative is expected to contribute to the development of an open AI platform and promote diversity in the global AI ecosystem.
During the meeting, the two sides discussed key areas of future cooperation, including:
· Joint development of open-source AI technologies and digital platforms
· Launch of a KAIST-KSU dual graduate degree program
· Expansion of exchange programs for students, faculty, and researchers
· Collaborative research in basic science and STEM disciplines
In particular, the two institutions discussed to establish a joint AI research center to co-develop open AI models and explore practical industrial applications. The goal is to broaden access to AI technology and create an inclusive innovation environment for more countries and institutions.
President Abdulla Al-Salman stated, "Under Saudi Vision 2030, we are driving innovation in science and technology through new leadership, openness, and strategic investment. This partnership with KAIST will serve as a critical foundation for building a competitive AI ecosystem in the Middle East."
President Kwang Hyung Lee emphasized, "By combining Saudi Arabia's leadership, market, and investment capacity with KAIST's technological innovation and the rich talent pools from both countries, we will significantly contribute to diversifying the global AI ecosystem."
Both leaders further noted, "Through joint research leading to an independent AI model, our two institutions could establish a new axis beyond the existing US-China digital order—realizing a 'Tripartite AI Strategy' that will propel us into global markets extending far beyond the MENA and ASEAN regions."
KAIST and KSU plan to formalize this agreement by signing an MOU in the near future, followed by concrete actions such as launching the joint research institute and global talent development programs. This collaboration was initiated under the Korea Foundation’s Distinguished Guests Invitation Program, overseen by the Ministry of Foreign Affairs, and is expected to grow into a long-term strategic partnership with continued support from KF.
About King Saud University (KSU)
Founded in 1957, KSU is Saudi Arabia’s first and leading national university. As a top research-oriented institution in the Middle East, it has achieved international recognition in fields such as AI, energy, and biotechnology. It plays a central role in nurturing talent and driving innovation aligned with Saudi Arabia’s Vision 2030, and is expanding global partnerships to further strengthen its research capabilities.
About the Korea Foundation (KF)
Established in 1991 under the Ministry of Foreign Affairs, the Korea Foundation is a public diplomacy institution dedicated to strengthening international understanding and friendship with Korea. KF plays a key role in expanding Korea’s soft power through academic and cultural exchange, people-to-people networks, and global Korean studies programs. Its Distinguished Guests Invitation Program fosters strategic partnerships with global leaders in government, academia, and industry.
2025.07.04 View 54 -
‘InnoCORE Research Group’ Launched to Lead AI Convergence Innovation
KAIST announced on the 16th of June that it has launched the ‘InnoCORE (Innovation-Core) Research Group,’ which will lead advanced strategic research in AI convergence (AI+S&T), in cooperation with the Ministry of Science and ICT (Minister Yoo Sang-im, hereinafter referred to as MSIT) and DGIST, GIST, and UNIST*. Through this, the group plans to actively recruit up to 200 world-class postdoctoral researchers.
DGIST (Daegu Gyeongbuk Institute of Science & Technology), GIST (Gwangju Institute of Science & Technology), UNIST (Ulsan National Institute of Science and Technology)
The ‘InnoCORE Research Group’ aims to foster core research personnel who will lead innovation in the field of AI convergence, focusing on nurturing and attracting high-level research talent in AI+Science & Technology. This is a strategic response to prevent brain drain of domestic talent and attract excellent overseas talent amidst the accelerating global competition for AI talent.
Through this initiative, our university plans to accelerate AI-based science and technology innovation and disseminate research achievements across industries and the economy by supporting top domestic and international postdoctoral researchers to dedicate themselves to developing AI convergence technologies in an advanced collaborative research environment.
The InnoCORE project for advanced AI+S&T convergence research and global talent attraction is jointly promoted by four science and technology institutes, including KAIST. It is structured around AI core technologies (such as hyper-scale language models, AI semiconductors) and AI convergence technologies (such as bio, manufacturing, energy, and aerospace).
As the leading institution, our university operates the following four research groups:
Hyper-scale Language Model Innovation Research Group: Advancement of LLM technology and research on generative AI, multimodal AI, and ensuring reliability.
AI-based Intelligent Design-Manufacturing Integration Research Group: Establishment of an AI platform for the entire lifecycle of the manufacturing industry and innovation in design and processes.
AI-Innovation Drug Research Group: Securing AI-based drug development technologies across the entire lifecycle and overcoming intractable diseases.
AI-Transformed Aerospace Research Group: AI transformation of aerospace systems throughout their lifecycle and development of new technologies such as autonomous flight and space communication.
< Poster on the InnoCORE Global Jobfair for Recruitment of Postdoctoral Researchers >
In addition, a total of eight research groups are formed to promote global collaborative convergence research, including those led by DGIST, GIST, and UNIST: ▲Bio-Integrated Physical AI, ▲Early Diagnosis of Brain Diseases AI+Nano Convergence, ▲Intelligent Hydrogen Technology Innovation, and ▲AI-Space Solar Power Research Group.
Starting in 2025, the four science and technology institutes, including KAIST, will officially begin recruiting 400 postdoctoral researchers in the AI+S&T fields. Selected postdoctoral researchers will be guaranteed high-level treatment with an annual salary of over 90 million KRW, and additional support through matching with companies and research projects is also planned.
In particular, global recruitment fairs will be held in major US regions to expand the attraction of excellent overseas talent. Local recruitment fairs will be held in Boston (Harvard, MIT), New York (NYU), and Silicon Valley (Stanford) in June, along with promotions through global academic journals such as Nature and Science, and LinkedIn.
KAIST plans to provide multiple mentor programs, global joint research opportunities, and excellent infrastructure (such as supercomputers, semiconductor fabs, and AI research platforms) within the research groups to enable postdoctoral researchers to collaborate with experts from various academic and industrial fields.
President Kwang Hyung Lee emphasized, “Through this InnoCORE project, KAIST will leap forward as a Global Hub for AI+S&T convergence research. Young researchers from around the world will challenge themselves and grow at KAIST, and our country will play a pivotal role in establishing itself as a leading nation in global AI convergence research and industry. To achieve this, we will spare no effort in providing the best research environment and active support.”
KAIST plans to actively pursue the InnoCORE project to secure global competitiveness in AI convergence research and contribute to the development of advanced industries. The eight selected research groups will finalize their detailed research plans by the end of June and commence full-scale research in July.
2025.06.19 View 1140 -
Simultaneous Analysis of 21 Chemical Reactions... AI to Transform New Drug Development
< Photo 1. (From left) Professor Hyunwoo Kim and students Donghun Kim and Gyeongseon Choi in the Integrated M.S./Ph.D. program of the Department of Chemistry >
Thalidomide, a drug once used to alleviate morning sickness in pregnant women, exhibits distinct properties due to its optical isomers* in the body: one isomer has a sedative effect, while the other causes severe side effects like birth defects. As this example illustrates, precise organic synthesis techniques, which selectively synthesize only the desired optical isomer, are crucial in new drug development. Overcoming the traditional methods that struggled with simultaneously analyzing multiple reactants, our research team has developed the world's first technology to precisely analyze 21 types of reactants simultaneously. This breakthrough is expected to make a significant contribution to new drug development utilizing AI and robots.
*Optical Isomers: A pair of molecules with the same chemical formula that are mirror images of each other and cannot be superimposed due to their asymmetric structure. This is analogous to a left and right hand, which are similar in form but cannot be perfectly overlaid.
KAIST's Professor Hyunwoo Kim's research team in the Department of Chemistry announced on the 16th that they have developed an innovative optical isomer analysis technology suitable for the era of AI-driven autonomous synthesis*. This research is the world's first technology to precisely analyze asymmetric catalytic reactions involving multiple reactants simultaneously using high-resolution fluorine nuclear magnetic resonance spectroscopy (19F NMR). It is expected to make groundbreaking contributions to various fields, including new drug development and catalyst optimization.
*AI-driven Autonomous Synthesis: An advanced technology that automates and optimizes chemical substance synthesis processes using artificial intelligence (AI). It is gaining attention as a core element for realizing automated and intelligent research environments in future laboratories. AI predicts and adjusts experimental conditions, interprets results, and designs subsequent experiments independently, minimizing human intervention in repetitive experiments and significantly increasing research efficiency and innovativeness.
Currently, while autonomous synthesis systems can automate everything from reaction design to execution, reaction analysis still relies on individual processing using traditional equipment. This leads to slower speeds and bottlenecks, making it unsuitable for high-speed repetitive experiments.
Furthermore, multi-substrate simultaneous screening techniques proposed in the 1990s garnered attention as a strategy to maximize reaction analysis efficiency. However, limitations of existing chromatography-based analysis methods restricted the number of applicable substrates. In asymmetric synthesis reactions, which selectively synthesize only the desired optical isomer, simultaneously analyzing more than 10 types of substrates was nearly impossible.
< Figure 1. Conventional organic reaction evaluation methods follow a process of deriving optimal reaction conditions using a single substrate, then expanding the substrate scope one by one under those conditions, leaving potential reaction areas unexplored. To overcome this, high-throughput screening is introduced to broadly explore catalyst reactivity for various substrates. When combined with multi-substrate screening, this approach allows for a much broader and more systematic understanding of reaction scope and trends. >
To overcome these limitations, the research team developed a 19F NMR-based multi-substrate simultaneous screening technology. This method involves performing asymmetric catalytic reactions with multiple reactants in a single reaction vessel, introducing a fluorine functional group into the products, and then applying their self-developed chiral cobalt reagent to clearly quantify all optical isomers using 19F NMR.
Utilizing the excellent resolution and sensitivity of 19F NMR, the research team successfully performed asymmetric synthesis reactions of 21 substrates simultaneously in a single reaction vessel and quantitatively measured the product yield and optical isomer ratio without any separate purification steps.
Professor Hyunwoo Kim stated, "While anyone can perform asymmetric synthesis reactions with multiple substrates in one reactor, accurately analyzing all the products has been a challenging problem to solve until now. We expect that achieving world-class multi-substrate screening analysis technology will greatly contribute to enhancing the analytical capabilities of AI-driven autonomous synthesis platforms."
< Figure 2. A method for analyzing multi-substrate asymmetric catalytic reactions, where different substrates react simultaneously in a single reactor, using fluorine nuclear magnetic resonance has been implemented. By utilizing the characteristics of fluorine nuclear magnetic resonance, which has a clean background signal and a wide chemical shift range, the reactivity of each substrate can be quantitatively analyzed. It is also shown that the optical activity of all reactants can be simultaneously measured using a cobalt metal complex. >
He further added, "This research provides a technology that can rapidly verify the efficiency and selectivity of asymmetric catalytic reactions essential for new drug development, and it is expected to be utilized as a core analytical tool for AI-driven autonomous research."
< Figure 3. It can be seen that in a multi-substrate reductive amination reaction using a total of 21 substrates, the yield and optical activity of the reactants according to the catalyst system were simultaneously measured using a fluorine nuclear magnetic resonance-based analysis platform. The yield of each reactant is indicated by color saturation, and the optical activity by numbers. >
Donghun Kim (first author, Integrated M.S./Ph.D. program) and Gyeongseon Choi (second author, Integrated M.S./Ph.D. program) from the KAIST Department of Chemistry participated in this research. The study was published online in the Journal of the American Chemical Society on May 27, 2025.※ Paper Title: One-pot Multisubstrate Screening for Asymmetric Catalysis Enabled by 19F NMR-based Simultaneous Chiral Analysis※ DOI: 10.1021/jacs.5c03446
This research was supported by the National Research Foundation of Korea's Mid-Career Researcher Program, the Asymmetric Catalytic Reaction Design Center, and the KAIST KC30 Project.
< Figure 4. Conceptual diagram of performing multi-substrate screening reactions and utilizing fluorine nuclear magnetic resonance spectroscopy. >
2025.06.16 View 1352 -
“One Experiment Is All It Takes”: KAIST Team Revolutionizes Drug Interaction Testing, Replacing 60,000 Studies
A groundbreaking new method developed by researchers at KAIST and Chungnam National University could drastically streamline drug interaction testing — replacing dozens of traditional experiments with just one.
The research, led by Professor Jae Kyoung Kim of KAIST Department of Mathematical Sciences & IBS Biomedical Mathematics Group and Professor Sang Kyum Kim of Chungnam National University's College of Pharmacy, introduces a novel analysis technique called 50-BOA, published in Nature Communications on June 5, 2025.
< Photo 1. (From left) Professor Sang Kyum Kim (Chungnam National University College of Pharmacy, co-corresponding author), Dr. Yun Min Song (IBS Biomedical Mathematics Group, formerly KAIST Department of Mathematical Sciences, co-first author), undergraduate student Hyeong Jun Jang (KAIST, co-first author), Professor Jae Kyoung Kim (KAIST and IBS Biomedical Mathematics Group, co-corresponding author) (Top left in the bubble) Professor Hwi-yeol Yun (Chungnam National University College of Pharmacy, co-author) >
For decades, scientists have had to repeat drug inhibition experiments across a wide range of concentrations to estimate inhibition constants — a process seen in over 60,000 scientific publications. But the KAIST-led team discovered that a single, well-chosen inhibitor concentration can yield even more accurate results.
< Figure 1. Graphical summary of 50-BOA. 50-BOA improves the accuracy and efficiency of inhibition constant estimation by using only a single inhibitor concentration instead of the traditionally used method of employing multiple inhibitor concentrations. >
“This approach challenges long-standing assumptions in experimental pharmacology,” says Prof. Kim. “It shows how mathematics can fundamentally redesign life science experiments.”
By mathematically analyzing the sources of error in conventional methods, the team found that over half the data typically collected adds no value or even skews results. Their new method not only cuts experimental effort by over 75%, but also enhances reproducibility and accuracy.
To help researchers adopt the method quickly, the team developed a user-friendly tool that takes simple Excel files as input, now freely available on GitHub:
☞ https://github.com/Mathbiomed/50-BOA
< Figure 2. The MATLAB and R package of 50-BOA at GitHub >
The work holds promise for faster and more reliable drug development, especially in assessing potential interactions in combination therapies. The U.S. FDA already emphasizes the importance of accurate enzyme inhibition assessment during early-stage drug evaluation — and this method could soon become a new gold standard.
2025.06.16 View 1545 -
KAIST Predicts Diseases by Early Detection of Aging Signals in Liver Tissue
- KAIST-KRIBB Develops ‘FiNi-seq’ Technology to Capture Characteristics of Fibrotic Microenvironments Accumulated in Liver Tissue and Dynamic Changes of Early Aging Cells
- Elucidation of the Spatial Ecosystem of Aged Liver Tissue, where Reprogramming of Senescent Cells and Immune Exhaustion Progresses, at the Single-Cell Genome and Epigenome Levels
< (From left) Professor Jong-Eun Park of KAIST Graduate School of Medical Science and Engineering (GSMSE), Dr. Chuna Kim of KRIBB, Dr. Kwon Yong Tak of KAIST GSMSE, Ph.D. Candidate Juyeon Kim of KRIBB, Ph.D. Candidate Myungsun Park of KAIST GSMSE >
Aging and chronic diseases involve the gradual accumulation of subtle tissue changes over a long period. Therefore, there are still limitations in quantitatively understanding these changes within organs and linking them to early signs of disease onset. In response, Korean researchers have successfully developed a platform technology that accurately captures localized changes that first occur within tissue, significantly aiding in faster disease discovery and prediction, and in setting personalized treatment targets.
KAIST (President Kwang Hyung Lee) announced on June 12th that a joint research team led by Professor Jong-Eun Park of the Graduate School of Medical Science and Engineering at KAIST and Dr. Chuna Kim of the Aging Convergence Research Center at the Korea Research Institute of Bioscience and Biotechnology (KRIBB, President Seok-Yoon Kwon) has developed ‘FiNi-seq (Fibrotic Niche enrichment sequencing)’ technology. This technology captures fibrotic microenvironments locally occurring in aged liver tissue and enables precise analysis at the single-cell transcriptome level*.
*Single-cell transcriptome analysis: A method to measure how actively each cell uses which genes, allowing identification and function of individual diseased cells.
The researchers developed a method to selectively enrich early aging microenvironments where regeneration is delayed and fibrosis accumulates, by physically selecting regions with high tissue degradation resistance in aged liver tissue.
In this process, high-resolution identification of fibrosis-related endothelial cells, fibroblasts interacting with the immune system, and immune-exhausted cells such as PD-1 highly expressing CD8 T cells, which were difficult to capture with existing single-cell analysis technologies, was possible.
In particular, the research team confirmed through ‘FiNi-seq’ technology that specific cells observed in fibrotic areas within aged liver tissue secondarily age the surrounding environment through secreted factors, and that this leads to the expansion of the aged environment.
Furthermore, they also elucidated the mechanism by which endothelial cells lose their tissue-specific identity and induce innate immune responses, promoting immune cell infiltration. Through spatial transcriptome analysis, the spatial distribution of fibroblasts interacting with immune cells was quantified, revealing their involvement in tissue regeneration, induction of inflammatory responses, and progression to chronic fibrosis.
The research team performed integrated analysis of multi-omics\* data to obtain transcriptome and epigenome information, precisely interpreting the microenvironment of aged liver tissue and its spatial heterogeneity, and confirming how these changes are connected to the intrahepatic vascular structure.
*Multi-omics: An integrated analysis method for various biological information within an organism, such as genes, proteins, metabolites, and cell information.
The newly developed ‘FiNi-seq’ technology is expected to be a useful platform for high-resolution capture of pathophysiological signals in most chronic liver diseases, including the aging process that causes fibrosis.
< Figure 1. Isolation of fibrotic regions from aged liver tissue, followed by single-cell transcriptome analysis and validation in a fibrosis model. >
The first author, Dr. Kwon Yong Tak of KAIST Graduate School of Medical Science and Engineering (GSMSE), a hepatologist at Seoul St. Mary's Hospital, designed this study to lay the groundwork for early diagnosis and treatment of fibrosis progression, the most important clinical prognostic indicator in chronic liver disease, while pursuing his Ph.D. at KAIST KAIST GSMSE with support from the physician-scientist training program. Co-first author Myungsun Park, a Ph.D. candidate at KAIST KAIST GSMSE, was responsible for the technical implementation of FiNi-seq technology, and Juyeon Kim, a Ph.D. candidate at KRIBB's Aging Convergence Research Center, was responsible for imaging analysis of aged tissue, playing a key role in the research.
Dr. Chuna Kim of KRIBB stated, “Through this study, we were able to precisely elucidate the cellular composition and spatial characteristics of the fibrotic microenvironment observed in aged liver tissue at the single-cell level.”
< Figure 2. Spatially defined stepwise progression patterns of aging-related regions within the liver and identification of regulatory factors inducing them. >
Professor Jong-Eun Park of the Graduate School of Medical Science and Engineering said, “As an analytical technology that can capture subtle changes occurring in the early stages of aging and chronic diseases, it is expected to play a significant role in finding effective treatment targets in the future. Also, we plan to expand this research to chronic diseases in other organs such as the lungs and kidneys, as well as various liver disease models.”
This research was published in the international journal ‘Nature Aging’ on May 5, 2025, with Dr. Kwon Yong Tak of KAIST KAIST GSMSE, Ph.D. Candidate Juyeon Kim of KRIBB, and Ph.D. Candidate Myungsun Park of KAIST as co-first authors.
*Paper Title: Quasi-spatial single-cell transcriptome based on physical tissue properties defines early aging associated niche in liver
*DOI: https://doi.org/10.1038/s43587-025-00857-7
This research was supported by several domestic institutions, including the National Research Foundation of Korea, the Korea Health Industry Development Institute (KHIDI), the Korea Research Institute of Bioscience and Biotechnology (KRIBB), KIST, POSCO Science Fellowship, and the Convergence Medical Scientist Training Program.
2025.06.12 View 1231 -
KAIST Professor Jee-Hwan Ryu Receives Global IEEE Robotics Journal Best Paper Award
- Professor Jee-Hwan Ryu of Civil and Environmental Engineering receives the Best Paper Award from the Institute of Electrical and Electronics Engineers (IEEE) Robotics Journal, officially presented at ICRA, a world-renowned robotics conference.
- This is the highest level of international recognition, awarded to only the top 5 papers out of approximately 1,500 published in 2024.
- Securing a new working channel technology for soft growing robots expands the practicality and application possibilities in the field of soft robotics.
< Professor Jee-Hwan Ryu (left), Nam Gyun Kim, Ph.D. Candidate (right) from the KAIST Department of Civil and Environmental Engineering and KAIST Robotics Program >
KAIST (President Kwang-Hyung Lee) announced on the 6th that Professor Jee-Hwan Ryu from the Department of Civil and Environmental Engineering received the 2024 Best Paper Award from the Robotics and Automation Letters (RA-L), a premier journal under the IEEE, at the '2025 IEEE International Conference on Robotics and Automation (ICRA)' held in Atlanta, USA, on May 22nd.
This Best Paper Award is a prestigious honor presented to only the top 5 papers out of approximately 1,500 published in 2024, boasting high international competition and authority.
The award-winning paper by Professor Ryu proposes a novel working channel securing mechanism that significantly expands the practicality and application possibilities of 'Soft Growing Robots,' which are based on soft materials that move or perform tasks through a growing motion similar to plant roots.
< IEEE Robotics Journal Award Ceremony >
Existing soft growing robots move by inflating or contracting their bodies through increasing or decreasing internal pressure, which can lead to blockages in their internal passages. In contrast, the newly developed soft growing robot achieves a growing function while maintaining the internal passage pressure equal to the external atmospheric pressure, thereby successfully securing an internal passage while retaining the robot's flexible and soft characteristics.
This structure allows various materials or tools to be freely delivered through the internal passage (working channel) within the robot and offers the advantage of performing multi-purpose tasks by flexibly replacing equipment according to the working environment.
The research team fabricated a prototype to prove the effectiveness of this technology and verified its performance through various experiments. Specifically, in the slide plate experiment, they confirmed whether materials or equipment could pass through the robot's internal channel without obstruction, and in the pipe pulling experiment, they verified if a long pipe-shaped tool could be pulled through the internal channel.
< Figure 1. Overall hardware structure of the proposed soft growing robot (left) and a cross-sectional view composing the inflatable structure (right) >
Experimental results demonstrated that the internal channel remained stable even while the robot was growing, serving as a key basis for supporting the technology's practicality and scalability.
Professor Jee-Hwan Ryu stated, "This award is very meaningful as it signifies the global recognition of Korea's robotics technology and academic achievements. Especially, it holds great significance in achieving technical progress that can greatly expand the practicality and application fields of soft growing robots. This achievement was possible thanks to the dedication and collaboration of the research team, and I will continue to contribute to the development of robotics technology through innovative research."
< Figure 2. Material supplying mechanism of the Soft Growing Robot >
This research was co-authored by Dongoh Seo, Ph.D. Candidate in Civil and Environmental Engineering, and Nam Gyun Kim, Ph.D. Candidate in Robotics. It was published in IEEE Robotics and Automation Letters on September 1, 2024.
(Paper Title: Inflatable-Structure-Based Working-Channel Securing Mechanism for Soft Growing Robots, DOI: 10.1109/LRA.2024.3426322)
This project was supported simultaneously by the National Research Foundation of Korea's Future Promising Convergence Technology Pioneer Research Project and Mid-career Researcher Project.
2025.06.09 View 1892 -
Professor Hyun Myung's Team Wins First Place in a Challenge at ICRA by IEEE
< Photo 1. (From left) Daebeom Kim (Team Leader, Ph.D. student), Seungjae Lee (Ph.D. student), Seoyeon Jang (Ph.D. student), Jei Kong (Master's student), Professor Hyun Myung >
A team of the Urban Robotics Lab, led by Professor Hyun Myung from the KAIST School of Electrical Engineering, achieved a remarkable first-place overall victory in the Nothing Stands Still Challenge (NSS Challenge) 2025, held at the 2025 IEEE International Conference on Robotics and Automation (ICRA), the world's most prestigious robotics conference, from May 19 to 23 in Atlanta, USA.
The NSS Challenge was co-hosted by HILTI, a global construction company based in Liechtenstein, and Stanford University's Gradient Spaces Group. It is an expanded version of the HILTI SLAM (Simultaneous Localization and Mapping)* Challenge, which has been held since 2021, and is considered one of the most prominent challenges at 2025 IEEE ICRA.*SLAM: Refers to Simultaneous Localization and Mapping, a technology where robots, drones, autonomous vehicles, etc., determine their own position and simultaneously create a map of their surroundings.
< Photo 2. A scene from the oral presentation on the winning team's technology (Speakers: Seungjae Lee and Seoyeon Jang, Ph.D. candidates of KAIST School of Electrical Engineering) >
This challenge primarily evaluates how accurately and robustly LiDAR scan data, collected at various times, can be registered in situations with frequent structural changes, such as construction and industrial environments. In particular, it is regarded as a highly technical competition because it deals with multi-session localization and mapping (Multi-session SLAM) technology that responds to structural changes occurring over multiple timeframes, rather than just single-point registration accuracy.
The Urban Robotics Lab team secured first place overall, surpassing National Taiwan University (3rd place) and Northwestern Polytechnical University of China (2nd place) by a significant margin, with their unique localization and mapping technology that solves the problem of registering LiDAR data collected across multiple times and spaces. The winning team will be awarded a prize of $4,000.
< Figure 1. Example of Multiway-Registration for Registering Multiple Scans >
The Urban Robotics Lab team independently developed a multiway-registration framework that can robustly register multiple scans even without prior connection information. This framework consists of an algorithm for summarizing feature points within scans and finding correspondences (CubicFeat), an algorithm for performing global registration based on the found correspondences (Quatro), and an algorithm for refining results based on change detection (Chamelion). This combination of technologies ensures stable registration performance based on fixed structures, even in highly dynamic industrial environments.
< Figure 2. Example of Change Detection Using the Chamelion Algorithm>
LiDAR scan registration technology is a core component of SLAM (Simultaneous Localization And Mapping) in various autonomous systems such as autonomous vehicles, autonomous robots, autonomous walking systems, and autonomous flying vehicles.
Professor Hyun Myung of the School of Electrical Engineering stated, "This award-winning technology is evaluated as a case that simultaneously proves both academic value and industrial applicability by maximizing the performance of precisely estimating the relative positions between different scans even in complex environments. I am grateful to the students who challenged themselves and never gave up, even when many teams abandoned due to the high difficulty."
< Figure 3. Competition Result Board, Lower RMSE (Root Mean Squared Error) Indicates Higher Score (Unit: meters)>
The Urban Robotics Lab team first participated in the SLAM Challenge in 2022, winning second place among academic teams, and in 2023, they secured first place overall in the LiDAR category and first place among academic teams in the vision category.
2025.05.30 View 2689 -
“For the First Time, We Shared a Meaningful Exchange”: KAIST Develops an AI App for Parents and Minimally Verbal Autistic Children Connect
• KAIST team up with NAVER AI Lab and Dodakim Child Development Center Develop ‘AAcessTalk’, an AI-driven Communication Tool bridging the gap Between Children with Autism and their Parents
• The project earned the prestigious Best Paper Award at the ACM CHI 2025, the Premier International Conference in Human-Computer Interaction
• Families share heartwarming stories of breakthrough communication and newfound understanding.
< Photo 1. (From left) Professor Hwajung Hong and Doctoral candidate Dasom Choi of the Department of Industrial Design with SoHyun Park and Young-Ho Kim of Naver Cloud AI Lab >
For many families of minimally verbal autistic (MVA) children, communication often feels like an uphill battle. But now, thanks to a new AI-powered app developed by researchers at KAIST in collaboration with NAVER AI Lab and Dodakim Child Development Center, parents are finally experiencing moments of genuine connection with their children.
On the 16th, the KAIST (President Kwang Hyung Lee) research team, led by Professor Hwajung Hong of the Department of Industrial Design, announced the development of ‘AAcessTalk,’ an artificial intelligence (AI)-based communication tool that enables genuine communication between children with autism and their parents.
This research was recognized for its human-centered AI approach and received international attention, earning the Best Paper Award at the ACM CHI 2025*, an international conference held in Yokohama, Japan.*ACM CHI (ACM Conference on Human Factors in Computing Systems) 2025: One of the world's most prestigious academic conference in the field of Human-Computer Interaction (HCI).
This year, approximately 1,200 papers were selected out of about 5,000 submissions, with the Best Paper Award given to only the top 1%. The conference, which drew over 5,000 researchers, was the largest in its history, reflecting the growing interest in ‘Human-AI Interaction.’
Called AACessTalk, the app offers personalized vocabulary cards tailored to each child’s interests and context, while guiding parents through conversations with customized prompts. This creates a space where children’s voices can finally be heard—and where parents and children can connect on a deeper level.
Traditional augmentative and alternative communication (AAC) tools have relied heavily on fixed card systems that often fail to capture the subtle emotions and shifting interests of children with autism. AACessTalk breaks new ground by integrating AI technology that adapts in real time to the child’s mood and environment.
< Figure. Schematics of AACessTalk system. It provides personalized vocabulary cards for children with autism and context-based conversation guides for parents to focus on practical communication. Large ‘Turn Pass Button’ is placed at the child’s side to allow the child to lead the conversation. >
Among its standout features is a large ‘Turn Pass Button’ that gives children control over when to start or end conversations—allowing them to lead with agency. Another feature, the “What about Mom/Dad?” button, encourages children to ask about their parents’ thoughts, fostering mutual engagement in dialogue, something many children had never done before.
One parent shared, “For the first time, we shared a meaningful exchange.” Such stories were common among the 11 families who participated in a two-week pilot study, where children used the app to take more initiative in conversations and parents discovered new layers of their children’s language abilities.
Parents also reported moments of surprise and joy when their children used unexpected words or took the lead in conversations, breaking free from repetitive patterns. “I was amazed when my child used a word I hadn’t heard before. It helped me understand them in a whole new way,” recalled one caregiver.
Professor Hwajung Hong, who led the research at KAIST’s Department of Industrial Design, emphasized the importance of empowering children to express their own voices. “This study shows that AI can be more than a communication aid—it can be a bridge to genuine connection and understanding within families,” she said.
Looking ahead, the team plans to refine and expand human-centered AI technologies that honor neurodiversity, with a focus on bringing practical solutions to socially vulnerable groups and enriching user experiences.
This research is the result of KAIST Department of Industrial Design doctoral student Dasom Choi's internship at NAVER AI Lab.* Thesis Title: AACessTalk: Fostering Communication between Minimally Verbal Autistic Children and Parents with Contextual Guidance and Card Recommendation* DOI: 10.1145/3706598.3713792* Main Author Information: Dasom Choi (KAIST, NAVER AI Lab, First Author), SoHyun Park (NAVER AI Lab) , Kyungah Lee (Dodakim Child Development Center), Hwajung Hong (KAIST), and Young-Ho Kim (NAVER AI Lab, Corresponding Author)
This research was supported by the NAVER AI Lab internship program and grants from the National Research Foundation of Korea: the Doctoral Student Research Encouragement Grant (NRF-2024S1A5B5A19043580) and the Mid-Career Researcher Support Program for the Development of a Generative AI-Based Augmentative and Alternative Communication System for Autism Spectrum Disorder (RS-2024-00458557).
2025.05.19 View 3793 -
KAIST's Pioneering VR Precision Technology & Choreography Tool Receive Spotlights at CHI 2025
Accurate pointing in virtual spaces is essential for seamless interaction. If pointing is not precise, selecting the desired object becomes challenging, breaking user immersion and reducing overall experience quality. KAIST researchers have developed a technology that offers a vivid, lifelike experience in virtual space, alongside a new tool that assists choreographers throughout the creative process.
KAIST (President Kwang-Hyung Lee) announced on May 13th that a research team led by Professor Sang Ho Yoon of the Graduate School of Culture Technology, in collaboration with Professor Yang Zhang of the University of California, Los Angeles (UCLA), has developed the ‘T2IRay’ technology and the ‘ChoreoCraft’ platform, which enables choreographers to work more freely and creatively in virtual reality. These technologies received two Honorable Mention awards, recognizing the top 5% of papers, at CHI 2025*, the best international conference in the field of human-computer interaction, hosted by the Association for Computing Machinery (ACM) from April 25 to May 1.
< (From left) PhD candidates Jina Kim and Kyungeun Jung along with Master's candidate, Hyunyoung Han and Professor Sang Ho Yoon of KAIST Graduate School of Culture Technology and Professor Yang Zhang (top) of UCLA >
T2IRay: Enabling Virtual Input with Precision
T2IRay introduces a novel input method that allows for precise object pointing in virtual environments by expanding traditional thumb-to-index gestures. This approach overcomes previous limitations, such as interruptions or reduced accuracy due to changes in hand position or orientation.
The technology uses a local coordinate system based on finger relationships, ensuring continuous input even as hand positions shift. It accurately captures subtle thumb movements within this coordinate system, integrating natural head movements to allow fluid, intuitive control across a wide range.
< Figure 1. T2IRay framework utilizing the delicate movements of the thumb and index fingers for AR/VR pointing >
Professor Sang Ho Yoon explained, “T2IRay can significantly enhance the user experience in AR/VR by enabling smooth, stable control even when the user’s hands are in motion.”
This study, led by first author Jina Kim, was supported by the Excellent New Researcher Support Project of the National Research Foundation of Korea under the Ministry of Science and ICT, as well as the University ICT Research Center (ITRC) Support Project of the Institute of Information and Communications Technology Planning and Evaluation (IITP).
▴ Paper title: T2IRay: Design of Thumb-to-Index Based Indirect Pointing for Continuous and Robust AR/VR Input▴ Paper link: https://doi.org/10.1145/3706598.3713442
▴ T2IRay demo video: https://youtu.be/ElJlcJbkJPY
ChoreoCraft: Creativity Support through VR for Choreographers
In addition, Professor Yoon’s team developed ‘ChoreoCraft,’ a virtual reality tool designed to support choreographers by addressing the unique challenges they face, such as memorizing complex movements, overcoming creative blocks, and managing subjective feedback.
ChoreoCraft reduces reliance on memory by allowing choreographers to save and refine movements directly within a VR space, using a motion-capture avatar for real-time interaction. It also enhances creativity by suggesting movements that naturally fit with prior choreography and musical elements. Furthermore, the system provides quantitative feedback by analyzing kinematic factors like motion stability and engagement, helping choreographers make data-driven creative decisions.
< Figure 2. ChoreoCraft's approaches to encourage creative process >
Professor Yoon noted, “ChoreoCraft is a tool designed to address the core challenges faced by choreographers, enhancing both creativity and efficiency. In user tests with professional choreographers, it received high marks for its ability to spark creative ideas and provide valuable quantitative feedback.”
This research was conducted in collaboration with doctoral candidate Kyungeun Jung and master’s candidate Hyunyoung Han, alongside the Electronics and Telecommunications Research Institute (ETRI) and One Million Co., Ltd. (CEO Hye-rang Kim), with support from the Cultural and Arts Immersive Service Development Project by the Ministry of Culture, Sports and Tourism.
▴ Paper title: ChoreoCraft: In-situ Crafting of Choreography in Virtual Reality through Creativity Support Tools▴ Paper link: https://doi.org/10.1145/3706598.3714220
▴ ChoreoCraft demo video: https://youtu.be/Ms1fwiSBjjw
*CHI (Conference on Human Factors in Computing Systems): The premier international conference on human-computer interaction, organized by the ACM, was held this year from April 25 to May 1, 2025.
2025.05.13 View 3513 -
KAIST & CMU Unveils Amuse, a Songwriting AI-Collaborator to Help Create Music
Wouldn't it be great if music creators had someone to brainstorm with, help them when they're stuck, and explore different musical directions together? Researchers of KAIST and Carnegie Mellon University (CMU) have developed AI technology similar to a fellow songwriter who helps create music.
KAIST (President Kwang-Hyung Lee) has developed an AI-based music creation support system, Amuse, by a research team led by Professor Sung-Ju Lee of the School of Electrical Engineering in collaboration with CMU. The research was presented at the ACM Conference on Human Factors in Computing Systems (CHI), one of the world’s top conferences in human-computer interaction, held in Yokohama, Japan from April 26 to May 1. It received the Best Paper Award, given to only the top 1% of all submissions.
< (From left) Professor Chris Donahue of Carnegie Mellon University, Ph.D. Student Yewon Kim and Professor Sung-Ju Lee of the School of Electrical Engineering >
The system developed by Professor Sung-Ju Lee’s research team, Amuse, is an AI-based system that converts various forms of inspiration such as text, images, and audio into harmonic structures (chord progressions) to support composition.
For example, if a user inputs a phrase, image, or sound clip such as “memories of a warm summer beach”, Amuse automatically generates and suggests chord progressions that match the inspiration.
Unlike existing generative AI, Amuse is differentiated in that it respects the user's creative flow and naturally induces creative exploration through an interactive method that allows flexible integration and modification of AI suggestions.
The core technology of the Amuse system is a generation method that blends two approaches: a large language model creates music code based on the user's prompt and inspiration, while another AI model, trained on real music data, filters out awkward or unnatural results using rejection sampling.
< Figure 1. Amuse system configuration. After extracting music keywords from user input, a large language model-based code progression is generated and refined through rejection sampling (left). Code extraction from audio input is also possible (right). The bottom is an example visualizing the chord structure of the generated code. >
The research team conducted a user study targeting actual musicians and evaluated that Amuse has high potential as a creative companion, or a Co-Creative AI, a concept in which people and AI collaborate, rather than having a generative AI simply put together a song.
The paper, in which a Ph.D. student Yewon Kim and Professor Sung-Ju Lee of KAIST School of Electrical and Electronic Engineering and Carnegie Mellon University Professor Chris Donahue participated, demonstrated the potential of creative AI system design in both academia and industry. ※ Paper title: Amuse: Human-AI Collaborative Songwriting with Multimodal Inspirations DOI: https://doi.org/10.1145/3706598.3713818
※ Research demo video: https://youtu.be/udilkRSnftI?si=FNXccC9EjxHOCrm1
※ Research homepage: https://nmsl.kaist.ac.kr/projects/amuse/
Professor Sung-Ju Lee said, “Recent generative AI technology has raised concerns in that it directly imitates copyrighted content, thereby violating the copyright of the creator, or generating results one-way regardless of the creator’s intention. Accordingly, the research team was aware of this trend, paid attention to what the creator actually needs, and focused on designing an AI system centered on the creator.”
He continued, “Amuse is an attempt to explore the possibility of collaboration with AI while maintaining the initiative of the creator, and is expected to be a starting point for suggesting a more creator-friendly direction in the development of music creation tools and generative AI systems in the future.”
This research was conducted with the support of the National Research Foundation of Korea with funding from the government (Ministry of Science and ICT). (RS-2024-00337007)
2025.05.07 View 5012 -
Editing Parkinson's Disease – KAIST Makes World's First Discovery of an Inflammatory RNA Editing Enzyme through Co-work with UCL Researchers
< Professor Minee Choi of the Department of Brain and Cognitive Sciences (top left). Professor Sonia Gandhi (top right) and Professor Klenerman of the University College London (bottom right) >
Parkinson's disease (PD) is a neurodegenerative disorder in which the α-synuclein protein abnormally aggregates within brain cells, causing neuronal damage. Through international collaboration, researchers at KAIST have revealed that RNA editing plays a crucial role in regulating neuroinflammation, a key pathology of Parkinson's disease.
KAIST (represented by President Kwang-Hyung Lee) announced on the 27th of April that a research team led by Professor Minee L. Choi from the Department of Brain and Cognitive Sciences, in collaboration with University College London (UCL) and the Francis Crick Institute, discovered that the RNA editing enzyme ADAR1 plays an important role in controlling immune responses in astrocytes, glial cells that trigger protective reactions in the brain, and demonstrated that this mechanism is critically involved in the progression of Parkinson’s disease.
Professor Choi's research team created a co-culture model composed of astrocytes and neurons derived from stem cells originating from Parkinson's disease patients, in order to study the inflammatory responses of brain immune cells. They then treated the model with α-synuclein aggregates, which are known to cause Parkinson’s disease, and analyzed how the immune cells' inflammatory responses changed.
< Figure 1. Schematic diagram of the inflammatory RNA editing model in Parkinson's disease >
As a result, it was found that early pathological forms of α-synuclein, known as oligomers, activated the Toll-like receptor pathway, which acts as a danger sensor in astrocytes, as well as the interferon response pathway, an immune signaling network that combats viruses and pathogens. During this process, the RNA editing enzyme ADAR1 was expressed and transformed into an isoform with an altered protein structure and function.
Notably, the RNA editing activity of ADAR1, which normally functions to regulate immune responses during viral infections by converting adenosine (A) to inosine (I) through a process known as A-to-I RNA editing, was found to be abnormally focused on genes that cause inflammation rather than operating under normal conditions. This phenomenon was observed not only in the patient-derived neuron models but also in postmortem brain tissues from actual Parkinson’s disease patients.
< Figure 2. Experimental design and inflammatory response induction in astrocytes following treatment with α-synuclein oligomers (abnormally folded protein fragments) >
This directly proves that the dysregulation of RNA editing induces chronic inflammatory responses in astrocytes, ultimately leading to neuronal toxicity and pathological progression.
This study is significant in that it newly identified the regulation of RNA editing within astrocytes as a key mechanism behind neuroinflammatory responses. In particular, it suggests that ADAR1 could serve as a novel genetic target for the treatment of Parkinson’s disease.
It is also noteworthy that the study reflected actual pathological characteristics of patients by utilizing patient-specific induced pluripotent stem cell-based precision models for brain diseases.
Professor Minee L. Choi stated, “This study demonstrates that the regulator of inflammation caused by protein aggregation operates at the new layer of RNA editing, offering a completely different therapeutic strategy from existing approaches to Parkinson's disease treatment." She further emphasized, “RNA editing technology could become an important turning point in the development of therapeutics for neuroinflammation.”
< Figure 3. When treated with α-synuclein oligomers, the causative agent of Parkinson's disease, A-to-I RNA editing is induced to change genetic information by ADAR in patient-derived stem cell-differentiated glial cells, confirming that α-synuclein is likely to be associated with the progression of Parkinson's disease through RNA editing >
This study was published in Science Advances on April 11, with Professor Choi listed as a co-first author.
Paper Title: Astrocytic RNA editing regulates the host immune response to alpha-synuclein, Science Advances Vol.11, Issue 15. (DOI:10.1126/sciadv.adp8504)
Lead Authors: Karishma D’Sa (UCL, Co-First Author), Minee L. Choi (KAIST, Co-First Author), Mina Ryten (UCL, Corresponding Author), Sonia Gandhi (Francis Crick Institute, University of Cambridge, Corresponding Author)
This research was supported by the Brain Research Program and the Excellent Young Researcher Program of the National Research Foundation of Korea, as well as KAIST’s Daekyo Cognitive Enhancement Program.
2025.05.02 View 3880 -
KAIST Develops Retinal Therapy to Restore Lost Vision
Vision is one of the most crucial human senses, yet over 300 million people worldwide are at risk of vision loss due to various retinal diseases. While recent advancements in retinal disease treatments have successfully slowed disease progression, no effective therapy has been developed to restore already lost vision—until now. KAIST researchers have successfully developed a novel drug to restore vision.
< Photo 1. (From left) Ph.D. candidate Museong Kim, Professor Jin Woo Kim, and Dr. Eun Jung Lee of KAIST Department of Biological Sciences >
KAIST (represented by President Kwang Hyung Lee) announced on the 30th of March that a research team led by Professor Jin Woo Kim from the Department of Biological Sciences has developed a treatment method that restores vision through retinal nerve regeneration.
The research team successfully induced retinal regeneration and vision recovery in a disease-model mouse by administering a compound that blocks the PROX1 (prospero homeobox 1) protein, which suppresses retinal regeneration. Furthermore, the effect lasted for more than six months.
This study marks the first successful induction of long-term neural regeneration in mammalian retinas, offering new hope to patients with degenerative retinal diseases who previously had no treatment options.
As the global population continues to age, the number of retinal disease patients is steadily increasing. However, no treatments exist to restore damaged retinas and vision. The primary reason for this is the mammalian retina's inability to regenerate once damaged.
Studies on cold-blooded animals, such as fish—known for their robust retinal regeneration—have shown that retinal injuries trigger Müller glia cells to dedifferentiate into retinal progenitor cells, which then generate new neurons. However, in mammals, this process is impaired, leading to permanent retinal damage.
< Figure 1. Schematic diagram of the mechanism of retinal regeneration through inhibition of PROX1 migration. PROX1 protein secreted from retinal damaged retinal neurons transfers to Müllerglia and inhibits dedifferentiation into neural progenitor cells and neural regeneration. When PROX1 is captured outside the cells by an antibody against PROX1 and its transfer to Müllerglia is interfered, dedifferentiation of Müllerglia cells and retinal regeneration processes are resumed, restoring visual function. >
Through this study, the research team identified the PROX1 protein as a key inhibitor of Müller glia dedifferentiation in mammals. PROX1 is a protein found in neurons of the retina, hippocampus, and spinal cord, where it suppresses neural stem cell proliferation and promotes differentiation into neurons.
The researchers discovered that PROX1 accumulates in damaged mouse retinal Müller glia, but is absent in the highly regenerative Müller glia of fish. Furthermore, they demonstrated that the PROX1 found in Müller glia is not synthesized internally but rather taken up from surrounding neurons, which fail to degrade and instead secrete the protein.
Based on this finding, the team developed a method to restore Müller glia’s regenerative ability by eliminating extracellular PROX1 before it reaches these cells.
< Figure 2. Retinal regeneration and visual recovery in a retinitis pigmentosa model mouse through Anti-PROX1 gene therapy. After administration of adeno-associated virus expressing PROX1 neutralizing antibodies (AAV2-Anti-PROX1) to the eyes of RP1 retinitis pigmentosa model mice with vision loss, the photoreceptor cell layer of the retina is restored (A) and vision is restored (B). >
This approach involves using an antibody that binds to PROX1, developed by Celliaz Inc., a biotech startup founded by Professor Jin Woo Kim’s research lab. When administered to disease-model mouse retinas, this antibody significantly promoted neural regeneration. Additionally, when delivered, the antibody gene to the retinas of retinitis pigmentosa disease model mice, it enabled sustained retinal regeneration and vision restoration for over six months.
The retinal regeneration-inducing therapy is currently being developed by Celliaz Inc. for application in various degenerative retinal diseases that currently lack effective treatments. The company aims to begin clinical trials by 2028.
This study was co-authored by Dr. Eun Jung Lee of Celliaz Inc. and Museong Kim, a Ph.D. candidate at KAIST, as joint first authors. The findings were published online on March 26 in the international journal Nature Communications. (Paper Title: Restoration of retinal regenerative potential of Müller glia by disrupting intercellular Prox1 transfer | DOI: 10.1038/s41467-025-58290-8)
Dr. Eun Jung Lee stated, "We are about completing the optimization of the PROX1-neutralizing antibody (CLZ001) and move to preclinical studies before administering it to retinal disease patients. Our goal is to provide a solution for patients at risk of blindness who currently lack proper treatment options."
This research was supported by research funds from Korean National Research Foundation (NRF) and the Korea Drug Development Foundation (KDDF).
2025.03.31 View 12953