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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 2426 -
KAIST-UIUC researchers develop a treatment platform to disable the ‘biofilm’ shield of superbugs
< (From left) Ph.D. Candidate Joo Hun Lee (co-author), Professor Hyunjoon Kong (co-corresponding author) and Postdoctoral Researcher Yujin Ahn (co-first author) from the Department of Chemical and Biomolecular Engineering of the University of Illinois at Urbana-Champaign and Ju Yeon Chung (co-first author) from the Integrated Master's and Doctoral Program, and Professor Hyun Jung Chung (co-corresponding author) from the Department of Biological Sciences of KAIST >
A major cause of hospital-acquired infections, the super bacteria Methicillin-resistant Staphylococcus aureus (MRSA), not only exhibits strong resistance to existing antibiotics but also forms a dense biofilm that blocks the effects of external treatments. To meet this challenge, KAIST researchers, in collaboration with an international team, successfully developed a platform that utilizes microbubbles to deliver gene-targeted nanoparticles capable of break ing down the biofilms, offering an innovative solution for treating infections resistant to conventional antibiotics.
KAIST (represented by President Kwang Hyung Lee) announced on May 29 that a research team led by Professor Hyun Jung Chung from the Department of Biological Sciences, in collaboration with Professor Hyunjoon Kong's team at the University of Illinois, has developed a microbubble-based nano-gene delivery platform (BTN MB) that precisely delivers gene suppressors into bacteria to effectively remove biofilms formed by MRSA.
The research team first designed short DNA oligonucleotides that simultaneously suppress three major MRSA genes, related to—biofilm formation (icaA), cell division (ftsZ), and antibiotic resistance (mecA)—and engineered nanoparticles (BTN) to effectively deliver them into the bacteria.
< Figure 1. Effective biofilm treatment using biofilm-targeting nanoparticles controlled by microbubbler system. Schematic illustration of BTN delivery with microbubbles (MB), enabling effective permeation of ASOs targeting bacterial genes within biofilms infecting skin wounds. Gene silencing of targets involved in biofilm formation, bacterial proliferation, and antibiotic resistance leads to effective biofilm removal and antibacterial efficacy in vivo. >
In addition, microbubbles (MB) were used to increase the permeability of the microbial membrane, specifically the biofilm formed by MRSA. By combining these two technologies, the team implemented a dual-strike strategy that fundamentally blocks bacterial growth and prevents resistance acquisition.
This treatment system operates in two stages. First, the MBs induce pressure changes within the bacterial biofilm, allowing the BTNs to penetrate. Then, the BTNs slip through the gaps in the biofilm and enter the bacteria, delivering the gene suppressors precisely. This leads to gene regulation within MRSA, simultaneously blocking biofilm regeneration, cell proliferation, and antibiotic resistance expression.
In experiments conducted in a porcine skin model and a mouse wound model infected with MRSA biofilm, the BTN MB treatment group showed a significant reduction in biofilm thickness, as well as remarkable decreases in bacterial count and inflammatory responses.
< Figure 2. (a) Schematic illustration on the evaluation of treatment efficacy of BTN-MB gene therapy. (b) Reduction in MRSA biofilm mass via simultaneous inhibition of multiple genes. (c, d) Antibacterial efficacy of BTN-MB over time in a porcine skin infection biofilm model. (e) Schematic of the experimental setup to verify antibacterial efficacy in a mouse skin wound infection model. (f) Wound healing effects in mice. (g) Antibacterial effects at the wound site. (h) Histological analysis results. >
These results are difficult to achieve with conventional antibiotic monotherapy and demonstrate the potential for treating a wide range of resistant bacterial infections.
Professor Hyun Jung Chung of KAIST, who led the research, stated, “This study presents a new therapeutic solution that combines nanotechnology, gene suppression, and physical delivery strategies to address superbug infections that existing antibiotics cannot resolve. We will continue our research with the aim of expanding its application to systemic infections and various other infectious diseases.”
< (From left) Ju Yeon Chung from the Integrated Master's and Doctoral Program, and Professor Hyun Jung Chung from the Department of Biological Sciences >
The study was co-first authored by Ju Yeon Chung, a graduate student in the Department of Biological Sciences at KAIST, and Dr. Yujin Ahn from the University of Illinois. The study was published online on May 19 in the journal, Advanced Functional Materials.
※ Paper Title: Microbubble-Controlled Delivery of Biofilm-Targeting Nanoparticles to Treat MRSA Infection ※ DOI: https://doi.org/10.1002/adfm.202508291
This study was supported by the National Research Foundation and the Ministry of Health and Welfare, Republic of Korea; and the National Science Foundation and National Institutes of Health, USA.
2025.05.29 View 1721 -
KAIST to Develop a Korean-style ChatGPT Platform Specifically Geared Toward Medical Diagnosis and Drug Discovery
On May 23rd, KAIST (President Kwang-Hyung Lee) announced that its Digital Bio-Health AI Research Center (Director: Professor JongChul Ye of KAIST Kim Jaechul Graduate School of AI) has been selected for the Ministry of Science and ICT's 'AI Top-Tier Young Researcher Support Program (AI Star Fellowship Project).' With a total investment of ₩11.5 billion from May 2025 to December 2030, the center will embark on the full-scale development of AI technology and a platform capable of independently inferring and determining the kinds of diseases, and discovering new drugs.
< Photo. On May 20th, a kick-off meeting for the AI Star Fellowship Project was held at KAIST Kim Jaechul Graduate School of AI’s Yangjae Research Center with the KAIST research team and participating organizations of Samsung Medical Center, NAVER Cloud, and HITS. [From left to right in the front row] Professor Jaegul Joo (KAIST), Professor Yoonjae Choi (KAIST), Professor Woo Youn Kim (KAIST/HITS), Professor JongChul Ye (KAIST), Professor Sungsoo Ahn (KAIST), Dr. Haanju Yoo (NAVER Cloud), Yoonho Lee (KAIST), HyeYoon Moon (Samsung Medical Center), Dr. Su Min Kim (Samsung Medical Center) >
This project aims to foster an innovative AI research ecosystem centered on young researchers and develop an inferential AI agent that can utilize and automatically expand specialized knowledge systems in the bio and medical fields.
Professor JongChul Ye of the Kim Jaechul Graduate School of AI will serve as the lead researcher, with young researchers from KAIST including Professors Yoonjae Choi, Kimin Lee, Sungsoo Ahn, and Chanyoung Park, along with mid-career researchers like Professors Jaegul Joo and Woo Youn Kim, jointly undertaking the project. They will collaborate with various laboratories within KAIST to conduct comprehensive research covering the entire cycle from the theoretical foundations of AI inference to its practical application.
Specifically, the main goals include: - Building high-performance inference models that integrate diverse medical knowledge systems to enhance the precision and reliability of diagnosis and treatment. - Developing a convergence inference platform that efficiently combines symbol-based inference with neural network models. - Securing AI technology for new drug development and biomarker discovery based on 'cell ontology.'
Furthermore, through close collaboration with industry and medical institutions such as Samsung Medical Center, NAVER Cloud, and HITS Co., Ltd., the project aims to achieve: - Clinical diagnostic AI utilizing medical knowledge systems. - AI-based molecular target exploration for new drug development. - Commercialization of an extendible AI inference platform.
Professor JongChul Ye, Director of KAIST's Digital Bio-Health AI Research Center, stated, "At a time when competition in AI inference model development is intensifying, it is a great honor for KAIST to lead the development of AI technology specialized in the bio and medical fields with world-class young researchers." He added, "We will do our best to ensure that the participating young researchers reach a world-leading level in terms of research achievements after the completion of this seven-year project starting in 2025."
The AI Star Fellowship is a newly established program where post-doctoral researchers and faculty members within seven years of appointment participate as project leaders (PLs) to independently lead research. Multiple laboratories within a university and demand-side companies form a consortium to operate the program.
Through this initiative, KAIST plans to nurture bio-medical convergence AI talent and simultaneously promote the commercialization of core technologies in collaboration with Samsung Medical Center, NAVER Cloud, and HITS.
2025.05.26 View 3133 -
Hyung Kyu Lim, Former KAIST Alumni Association President, Donates 100 Million Won for a Challenge to Follow “I am a KAIST”
Hyung Kyu Lim, a former President of the KAIST Alumni Association, has donated 100 million won as the prize money for the School Song and National Anthem Challenge. This donation will be used as prize money starting from the 2026 competition and is expected to play a significant role in spreading KAIST's educational culture and fostering a sense of community.
< Photo 1. KAIST President Kwang-Hyung Lee (left) and the former Alumni Association President Hyung Kyu Lim at the ceremony for the signing of the pledge for Dr. Lim's donation. >
The School Song and National Anthem Challenge was first conceived in 2024 at the suggestion of President Kwang-Hyung Lee to enhance consensus on KAIST's values and educational philosophy and to inspire patriotism and school spirit. Participants express their sense of belonging and pride in KAIST by singing the KAIST school song, the national anthem, or the 'I'm a KAIST,' dedicated by Professor Sumi Jo, a visiting scholar at the Graduate School of Culture Technology. Notably, this year, a new category has been added where participants sing their self-composed 'My Own School Song,' making the stage more diverse.
The grand prize-winning team receives the President's Award and a prize of 1 million won. The top excellence award and participating teams also receive prizes and awards totaling 2 million won.
< Photo 2. At the ceremony for the signing of the donation pledge, KAIST President Kwang-Hyung Lee (left) is relaying a bouquet of flower and the plaque of appreciation to the former Alumni Association President Hyung Kyu Lim. >
Former Alumni Association President Hyung Kyu Lim stated, Love for the national community is the foundation of a sound global citizen consciousness. For me, love for this national community, along with family love, has been a great source of energy for growth.
He added, I hope this challenge of singing the national anthem and school song becomes a good nourishment for KAIST members to grow into global citizens with roots, expressing his thoughts on the donation.
President Kwang-Hyung Lee said, “I am grateful to former Alumni Association President Hyung Kyu Lim for his generous support of this meaningful program, which fosters pride in the school and raises interest in loving the country through the national anthem.” He added, “This donation will serve as an opportunity for KAIST members to cultivate a sense of belonging to the school and a sense of responsibility to the national community.”
Since 2018, former President Lim has annually donated prize money for the 'Linkgenesis Best Teacher Award,' encouraging faculty members who embody the values of creativity, challenge, and consideration. Furthermore, he has consistently contributed to KAIST's talent development and advancement by continuing to provide funds totaling 1 billion won, including scholarship funds for the Department of Electrical Engineering and the Alumni Academic Scholarship Foundation.
< Photo 3. Grand prize-winning team of the School Song and National Anthem Challenge >
Meanwhile, the '2nd School Song and National Anthem Challenge' was successfully held on May 21st at the main auditorium of KAIST, with over 150 spectators participating. Eight teams performed in the finals, and the final winning team was selected based on audience evaluation (10%) and judges' scores (90%).
< Photo 4. Grand prize-winning team of the School Song and National Anthem Challenge, Aeguk-Rock in performance >
The grand prize was awarded to the 'Aeguk-Rock' team, who arranged the national anthem into a rock version and performed it as a band. The top excellence award went to the 'Form of the Conductor' team, who sang the school song a cappella. The excellence award was given to Eun-Jin Choi, a student from the Graduate School of Culture Technology, who performed her self-composed school song written with an AI tool, 'Radiant You – You Are KAIST.' The 'Aeguk-Rock’ team also won the audience popularity award, and five other teams received participation awards.
< Photo 5. Group photo of the winners of the School Song and National Anthem Challenge >
2025.05.23 View 1753 -
“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 3554 -
KAIST Discovers Protein Switch that Turns Anti-Viral Immune Response On and Off
Even after the COVID-19 pandemic, various new infectious diseases continue to emerge, posing ongoing viral threats that demand robust and sustained immune defenses. However, excessive immune reactions can also harm body tissues, causing significant health issues. KAIST and an international research team have discovered a critical protein that acts as a 'switch' regulating immune responses to viruses. This breakthrough is expected to lay the groundwork for future infectious disease responses and autoimmune disease treatment strategies.
KAIST (President Kwang-Hyung Lee) announced on May 14 that a joint research team led by Professor Yoosik Kim from the Department of Chemical and Biomolecular Engineering at KAIST and Professor Seunghee Cha from University of Florida has discovered the mechanism by which double-stranded RNA derived from mitochondria amplifies immune responses. They identified the protein SLIRP as an 'immune switch' that regulates this process, playing a crucial role in both viral infections and autoimmune diseases.
< (From left) Master's candidate Yewon Yang, Professor Yoosik Kim and Ph.D. candidate Doyeong Ku of the Department of Chemical and Biomolecular Engineering >
Autoimmune diseases arise when the immune system fails to differentiate between external pathogens and the body's own molecules, leading to self-directed attacks. Despite extensive research, the precise causes of excessive inflammatory conditions like Sjögren’s syndrome and systemic lupus erythematosus remain unclear, and effective treatments are still limited.
To uncover the molecular mechanisms driving immune hyperactivation and to identify potential regulatory factors, the research team led by Professor Yoosik Kim focused on mitochondrial double-stranded RNA (mt-dsRNA), a genetic immunogenic material produced within cellular organelles. Since mt-dsRNA structurally resembles viral RNA, it can mistakenly trigger immune responses even in the absence of an actual viral infection.
The team discovered that SLIRP, a key regulator of mt-dsRNA, amplifies immune responses by stabilizing the RNA. They confirmed that SLIRP expression increases in experimental models simulating the tissues of autoimmune disease patients and viral infections. Conversely, suppressing SLIRP significantly reduced the immune response, underscoring its role as a critical factor in immune amplification.
This study also demonstrated the dual function of SLIRP in different contexts. In cells infected with human beta coronavirus OC43 and encephalomyocarditis virus (EMCV), SLIRP suppression led to reduced antiviral responses and increased viral replication. Meanwhile, in the blood and salivary gland cells of Sjögren’s syndrome patients, where both SLIRP and mt-dsRNA levels were elevated, suppressing SLIRP alleviated the abnormal immune response.
These findings highlight SLIRP as a key molecular switch that regulates immune responses in both infections and autoimmune diseases.
< Figure 1. Schematic diagram of antiviral signal amplification by SLIRP: SLIRP-based mt-dsRNA induction, cytoplasmic accumulation, and strong interferon response induction by positive feedback of immune response activation. Confirmation of the immune regulatory function of SLIRP in defense against autoimmune diseases Sjögren's syndrome, coronavirus, and encephalomyocarditis virus infection. >
Professor Yoosik Kim remarked, "Through this study, we have identified SLIRP as a crucial protein that drives immune amplification via mt-dsRNAs. Given its dual role in autoimmune diseases and viral infections, SLIRP presents a promising target for immune regulation therapies across various inflammatory disease contexts."
The study, with Ph.D. student Do-Young Ku (first author) and M.S. student Ye-Won Yang (second author) from the Department of Chemical and Biomolecular Engineering at KAIST as primary contributors, was published online in the journal Cell Reports on April 19, 2025.
※ Paper title: SLIRP amplifies antiviral signaling via positive feedback regulation and contributes to autoimmune diseases※ Main authors: Do-Young Ku (KAIST, first author), Ye-Won Yang (KAIST, second author), Seunghee Cha (University of Florida, corresponding author), Yoosik Kim (KAIST, corresponding author)
This study was supported by the Ministry of Health and Welfare's Public Health Technology Research Program and the National Institutes of Health (NIH) through Research Project (R01) funding.
2025.05.14 View 2458 -
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 3272 -
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 4724 -
KAIST sends out Music and Bio-Signs of Professor Kwon Ji-yong, a.k.a. G-Dragon, into Space to Pulsate through Universe and Resonate among Stars
KAIST (President Kwang-Hyung Lee) announced on the 10th of April that it successfully promoted the world’s first ‘Space Sound Source Transmission Project’ based on media art at the KAIST Space Research Institute on April 9th through collaboration between Professor Jinjoon Lee of the Graduate School of Culture Technology, a world-renowned media artist, and the global K-Pop artist, G-Dragon.
This project was proposed as part of the ‘AI Entertech Research Center’ being promoted by KAIST and Galaxy Corporation. It is a project to transmit the message and sound of G-Dragon (real name, Kwon Ji-yong), a singer/song writer affiliated with Galaxy Corporation and a visiting professor in the Department of Mechanical Engineering at KAIST, to space for the first time in the world.
This is a convergence project that combines science, technology, art, and popular music, and is a new form of ‘space culture content’ experiment that connects KAIST’s cutting-edge space technology, Professor Jinjoon Lee’s media art work, and G-Dragon’s voice and sound source containing his latest digital single, "HOME SWEET HOME".
< Photo 1. Professor Jinjoon Lee's Open Your Eyes Project "Iris"'s imagery projected on the 13m space antenna at the Space Research Institute >
This collaboration was planned with the theme of ‘emotional signals that expand the inner universe of humans to the outer universe.’ The image of G-Dragon’s iris was augmented through AI as a window into soul symbolizing his uniqueness and identity, and the new song “Home Sweet Home” was combined as an audio message containing the vibration of that emotion.
This was actually transmitted into space using a next-generation small satellite developed by KAIST Space Research Institute, completing a symbolic performance in which an individual’s inner universe is transmitted to outer space.
Professor Jinjoon Lee’s cinematic media art work “Iris” was unveiled at the site. This work was screened in the world’s first projection mapping method* on KAIST Space Research Institute’s 13m space antenna. This video was created using generative artificial intelligence (AI) technology based on the image of G-Dragon's iris, and combined with sound using the data of the sounds of Emile Bell rings – the bell that holds a thousand years of history, it presented an emotional art experience that transcends time and space.
*Projection Mapping: A technology that projects light and images onto actual structures to create visual changes, and is a method of expression that artistically reinterprets space.
This work is one of the major research achievements of KAIST TX Lab and Professor Lee based on new media technology based on biometric data such as iris, heartbeat, and brain waves.
Professor Jinjoon Lee said, "The iris is a symbol that reflects inner emotions and identity, so much so that it is called the 'mirror of the soul,' and this work sought to express 'the infinite universe seen from the inside of humanity' through G-Dragon's gaze."
< Photo 2. (From left) Professor Jinjoon Lee of the Graduate School of Culture Technology and G-Dragon (Visiting Professor Kwon Ji-yong of the Department of Mechanical Engineering) >
He continued, "The universe is a realm of technology as well as a stage for imagination and emotion, and I look forward to an encounter with the unknown through a new attempt to speak of art in the language of science including AI and imagine science in the form of art." “G-Dragon’s voice and music have now begun their journey to space,” said Yong-ho Choi, Galaxy Corporation’s Chief Happiness Officer (CHO). “This project is an act of leaving music as a legacy for humanity, while also having an important meaning of attempting to communicate with space.” He added, “This is a pioneering step to introduce human culture to space, and it will remain as a monumental performance that opens a new chapter in the history of music comparable to the Beatles.”
Galaxy Corporation is leading the future entertainment technology industry through its collaboration with KAIST, and was recently selected as the only entertainment technology company in a private meeting with Microsoft CEO Nadella. In particular, it is promoting the globalization of AI entertainment technology, receiving praise as a “pioneer of imagination” for new forms of AI entertainment content, including the AI contents for the deceased.
< Photo 3. Photo of G-Dragon's Home Sweet Home being sent into the space via Professor Jinjoon Lee's Space Sound Source Transmission Project >
Through this project, KAIST Space Research Institute presented new possibilities for utilizing satellite technology, and showed a model for science to connect with society in a more popular way.
KAIST President Kwang-Hyung Lee said, “KAIST is a place that always supports new imaginations and challenges,” and added, “We will continue to strive to continue creative research that no one has ever thought of, like this project that combines science, technology, and art.”
In the meantime, Galaxy Corporation, the agency of G-Dragon’s Professor Kwon Ji-yong, is an AI entertainment company that presents a new paradigm based on IP, media, tech, and entertainment convergence technology.
2025.04.10 View 4524 -
KAIST Accelerates Synthetic Microbe Design by Discovering Novel Enzymes Using AI
< (From left) Professor Sang Yup Lee of the Department of Chemical and Biomolecular Engineering (top), Hongkeun Ji, PhD candidate of the Department of Chemical and Biomolecular Engineering (top), Ha Rim Kim, PhD candidate of the Department of Chemical and Biomolecular Engineering, and Dr. Gi Bae Kim of the BioProcess Engineering Research Center >
Enzymes are proteins that catalyze biochemical reactions within cells and play a pivotal role in metabolic processes. Accordingly, identifying the functions of novel enzymes is a critical task in the construction of microbial cell factories.
A KAIST research team has leveraged artificial intelligence (AI) to design novel enzymes that do not exist in nature, significantly accelerating microbial cell factory development and boosting the potential for next-generation biotechnological applications such as drug development and biofuel production.
KAIST (represented by President Kwang-Hyung Lee) announced on the 21st of April that Distinguished Professor Sang Yup Lee and his team from the Department of Chemical and Biomolecular Engineering have published a review titled “Enzyme Functional Classification Using Artificial Intelligence,” which outlines the advancement of AI-based enzyme function prediction technologies and analyzes how AI has contributed to the discovery and design of new enzymes.
Professor Lee’s team systematically reviewed the development of enzyme function prediction technologies utilizing machine learning and deep learning, offering a comprehensive analysis.
From sequence similarity-based prediction methods to the integration of convolutional neural networks (CNNs), recurrent neural networks (RNNs), graph neural networks (GNNs), and transformer-based large language models, the paper covers a broad range of AI applications. It analyzes how these technologies extract meaningful information from protein sequences and enhance prediction accuracy.
In particular, enzyme function prediction using deep learning goes beyond simple sequence similarity analysis. By automatically extracting structural and evolutionary features embedded in amino acid sequences, deep learning enables more precise predictions of catalytic functions.
This highlights the unique advantages of AI models compared to traditional bioinformatics approaches.
Moreover, the review suggests that the advancement of generative AI will move future research beyond predicting existing functions to generating entirely new enzymes with functions not found in nature. This shift is expected to profoundly impact the trajectory of biotechnology and synthetic biology.
< Figure 1. Extraction of enzyme characteristics and function prediction using various deep learning structures >
Ha Rim Kim, a Ph.D. candidate and co-first author from the Department of Chemical and Biomolecular Engineering, stated, “AI-based enzyme function prediction and enzyme design are highly important across various fields including metabolic engineering, synthetic biology, and healthcare.”
Distinguished Professor Sang Yup Lee added, “AI-powered enzyme function prediction shows the potential to solve diverse biological problems and will significantly contribute to accelerating research across the entire field.”
The review was published on March 28 in Trends in Biotechnology, a leading biotechnology journal issued by Cell Press.
※ Title: Enzyme Functional Classification Using Artificial Intelligence
※DOI: https://doi.org/10.1016/j.tibtech.2025.03.003
※ Author Information: Ha Rim Kim (KAIST, Co-first author), Hongkeun Ji (KAIST, Co-first author), Gi Bae Kim (KAIST, Third author), Sang Yup Lee (KAIST, Corresponding author)
This research was supported by the Ministry of Science and ICT under the project Development of Core Technologies for Advanced Synthetic Biology to Lead the Bio-Manufacturing Industry (aimed at replacing petroleum-based chemicals), and also by joint support from the Ministry of Science and ICT and the Ministry of Health and Welfare for the project Development of Novel Antibiotic Structures Using Deep Learning-Based Synthetic Biology.
2025.04.07 View 3192 -
KAIST provides a comprehensive resource on microbial cell factories for sustainable chemical production
In silico analysis of five industrial microorganisms identifies optimal strains and metabolic engineering strategies for producing 235 valuable chemicals
Climate change and the depletion of fossil fuels have raised the global need for sustainable chemical production. In response to these environmental challenges, microbial cell factories are gaining attention as eco-friendly platforms for producing chemicals using renewable resources, while metabolic engineering technologies to enhance these cell factories are becoming crucial tools for maximizing production efficiency. However, difficulties in selecting suitable microbial strains and optimizing complex metabolic pathways continue to pose significant obstacles to practical industrial applications.
KAIST (President Kwang-Hyung Lee) announced on 27th of March that Distinguished Professor Sang Yup Lee’s research team in the Department of Chemical and Biomolecular Engineering comprehensively evaluated the production capabilities of various industrial microbial cell factories using in silico simulations and, based on these findings, identified the most suitable microbial strains for producing specific chemicals as well as optimal metabolic engineering strategies.
Previously, researchers attempted to determine the best strains and efficient metabolic engineering strategies among numerous microbial candidates through extensive biological experiments and meticulous verification processes. However, this approach required substantial time and costs. Recently, the introduction of genome-scale metabolic models (GEMs), which reconstruct the metabolic networks within an organism based on its entire genome information, has enabled systematic analysis of metabolic fluxes via computer simulations. This development offers a new way to overcome limitations of conventional experimental approaches, revolutionizing both strain selection and metabolic pathway design.
Accordingly, Professor Lee’s team at the Department of Chemical and Biomolecular Engineering, KAIST, evaluated the production capabilities of five representative industrial microorganisms—Escherichia coli, Saccharomyces cerevisiae, Bacillus subtilis, Corynebacterium glutamicum, and Pseudomonas putida—for 235 bio-based chemicals. Using GEMs, the researchers calculated both the maximum theoretical yields and the maximum achievable yields under industrial conditions for each chemical, thereby establishing criteria to identify the most suitable strains for each target compound.
< Figure 1. Outline of the strategy for improving microbial cell factories using a genome-scale metabolic model (GEM) >
The team specifically proposed strategies such as introducing heterologous enzyme reactions derived from other organisms and exchanging cofactors used by microbes to expand metabolic pathways. These strategies were shown to increase yields beyond the innate metabolic capacities of the microorganisms, resulting in higher production of industrially important chemicals such as mevalonic acid, propanol, fatty acids, and isoprenoids.
Moreover, by applying a computational approach to analyze metabolic fluxes in silico, the researchers suggested strategies for improving microbial strains to maximize the production of various chemicals. They quantitatively identified the relationships between specific enzyme reactions and target chemical production, as well as the relationships between enzymes and metabolites, determining which enzyme reactions should be up- or down-regulated. Through this, the team presented strategies not only to achieve high theoretical yields but also to maximize actual production capacities.
< Figure 2. Comparison of production routes and maximum yields of useful chemicals using representative industrial microorganisms >
Dr. Gi Bae Kim, the first author of this paper from the KAIST BioProcess Engineering Research Center, explained, “By introducing metabolic pathways derived from other organisms and exchanging cofactors, it is possible to design new microbial cell factories that surpass existing limitations. The strategies presented in this study will play a pivotal role in making microbial-based production processes more economical and efficient.” In addition, Distinguished Professor Sang Yup Lee noted, “This research serves as a key resource in the field of systems metabolic engineering, reducing difficulties in strain selection and pathway design, and enabling more efficient development of microbial cell factories. We expect it to greatly contribute to the future development of technologies for producing various eco-friendly chemicals, such as biofuels, bioplastics, and functional food materials.”
This research was conducted with the support from the Development of platform technologies of microbial cell factories for the next-generation biorefineries project and Development of advanced synthetic biology source technologies for leading the biomanufacturing industry project (Project Leader: Distinguished Professor Sang Yup Lee, KAIST) from National Research Foundation supported by the Korean Ministry of Science and ICT.
2025.03.27 View 3666 -
KAIST Innovates Mid-Infrared Photodetectors for Exoplanet Detection, Expanding Applications to Environmental and Medical Fields
NASA’s James Webb Space Telescope (JWST) utilizes mid-infrared spectroscopy to precisely analyze molecular components such as water vapor and sulfur dioxide in exoplanet atmospheres. The key to this analysis, where each molecule exhibits a unique spectral "fingerprint," lies in highly sensitive photodetector technology capable of measuring extremely weak light intensities. Recently, KAIST researchers have developed an innovative photodetector capable of detecting a broad range of mid-infrared spectra, garnering significant attention.
< Photo 1. (from the left) Ph.D. candidate Inki Kim (co-author), Professor SangHyeon Kim (corresponding author), Dr. Joonsup Shim (first author), and Dr. Jinha Lim (co-author) of KAIST School of Electrical Engineering. >
KAIST (represented by President Kwang-Hyung Lee) announced on the 27th of March that a research team led by Professor SangHyeon Kim from the School of Electrical Engineering has developed a mid-infrared photodetector that operates stably at room temperature, marking a major turning point for the commercialization of ultra-compact optical sensors.
The newly developed photodetector utilizes conventional silicon-based CMOS processes, enabling low-cost mass production while maintaining stable operation at room temperature. Notably, the research team successfully demonstrated the real-time detection of carbon dioxide (CO₂) gas using ultra-compact and ultra-thin optical sensors equipped with this photodetector, proving its potential for environmental monitoring and hazardous gas analysis.
Existing mid-infrared photodetectors generally require cooling systems due to high thermal noise at room temperature. These cooling systems increase the size and cost of equipment, making miniaturization and integration into portable devices challenging. Furthermore, conventional mid-infrared photodetectors are incompatible with silicon-based CMOS processes, limiting large-scale production and commercialization.
To address these limitations, the research team developed a waveguide-integrated photodetector using germanium (Ge), a Group IV element like silicon. This approach enables broad-spectrum mid-infrared detection while ensuring stable operation at room temperature.
< Figure 1. Schematic diagram of a room-temperature mid-infrared waveguide-integrated photodetector based on the Ge-on-insulator optical platform proposed in this study (top). Optical microscope image of the integrated photodetector connected with the sensing unit (bottom). >
A waveguide is a structure designed to efficiently guide light along a specific path with minimal loss. To implement various optical functions on a chip (on-chip), the development of waveguide-integrated photodetectors and waveguide-based optical components is essential.
Unlike conventional photodetectors that primarily rely on bandgap absorption principles, this new technology leverages the bolometric effect*, allowing it to detect the entire mid-infrared spectral range. As a result, it can be widely applied to the real-time sensing of various molecular species.
*Bolometric effect: A principle in which light absorption leads to an increase in temperature, causing electrical signals to change accordingly.
The waveguide-integrated mid-infrared photodetector developed by the research team is considered a groundbreaking innovation that overcomes the limitations of existing mid-infrared sensor technologies, including the need for cooling, difficulties in mass production, and high costs.
< Figure 2. Room temperature photoresponse characteristics of the mid-infrared waveguide photodetector proposed in this study (left) and real-time carbon dioxide (CO2) gas sensing results using the photodetector (right). >
This breakthrough technology is expected to be applicable across diverse fields, including environmental monitoring, medical diagnostics, industrial process management, national defense and security, and smart devices. It also paves the way for next-generation mid-infrared sensor advancements.
Professor SangHyeon Kim from KAIST stated, "This research represents a novel approach that overcomes the limitations of existing mid-infrared photodetector technologies and has great potential for practical applications in various fields." He further emphasized, "Since this sensor technology is compatible with CMOS processes, it enables low-cost mass production, making it highly suitable for next-generation environmental monitoring systems and smart manufacturing sites."
< Figure 3. Performance comparison image of a room-temperature mid-infrared waveguide photodetector fabricated with the technology proposed in this study. It achieves the world’s highest performance compared to existing technologies utilizing the Bolometric effect, and is the only solution compatible with CMOS processes. The technology proposed by our research team is characterized by its ability to respond to a wide spectrum of the mid-infrared band without limitations. >
The study, with Dr. Joonsup Shim (currently a postdoctoral researcher at Harvard University) as the first author, was published on March 19, 2025 in the internationally renowned journal Light: Science & Applications (JCR 2.9%, IF=20.6).
(Paper title: “Room-temperature waveguide-integrated photodetector using bolometric effect for mid-infrared spectroscopy applications,” https://doi.org/10.1038/s41377-025-01803-3)
2025.03.27 View 2694