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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 331 -
KAIST Introduces ‘Virtual Teaching Assistant’ That can Answer Even in the Middle of the Night – Successful First Deployment in Classroom
- Research teams led by Prof. Yoonjae Choi (Kim Jaechul Graduate School of AI) and Prof. Hwajeong Hong (Department of Industrial Design) at KAIST developed a Virtual Teaching Assistant (VTA) to support learning and class operations for a course with 477 students.
- The VTA responds 24/7 to students’ questions related to theory and practice by referencing lecture slides, coding assignments, and lecture videos.
- The system’s source code has been released to support future development of personalized learning support systems and their application in educational settings.
< Photo 1. (From left) PhD candidate Sunjun Kweon, Master's candidate Sooyohn Nam, PhD candidate Hyunseung Lim, Professor Hwajung Hong, Professor Yoonjae Choi >
“At first, I didn’t have high expectations for the Virtual Teaching Assistant (VTA), but it turned out to be extremely helpful—especially when I had sudden questions late at night, I could get immediate answers,” said Jiwon Yang, a Ph.D. student at KAIST. “I was also able to ask questions I would’ve hesitated to bring up with a human TA, which led me to ask even more and ultimately improved my understanding of the course.”
KAIST (President Kwang Hyung Lee) announced on June 5th that a joint research team led by Prof. Yoonjae Choi of the Kim Jaechul Graduate School of AI and Prof. Hwajeong Hong of the Department of Industrial Design has successfully developed and deployed a Virtual Teaching Assistant (VTA) that provides personalized feedback to individual students even in large-scale classes.
This study marks one of the first large-scale, real-world deployments in Korea, where the VTA was introduced in the “Programming for Artificial Intelligence” course at the KAIST Kim Jaechul Graduate School of AI, taken by 477 master’s and Ph.D. students during the Fall 2024 semester, to evaluate its effectiveness and practical applicability in an actual educational setting.
The AI teaching assistant developed in this study is a course-specialized agent, distinct from general-purpose tools like ChatGPT or conventional chatbots. The research team implemented a Retrieval-Augmented Generation (RAG) architecture, which automatically vectorizes a large volume of course materials—including lecture slides, coding assignments, and video lectures—and uses them as the basis for answering students’ questions.
< Photo 2. Teaching Assistant demonstrating to the student how the Virtual Teaching Assistant works>
When a student asks a question, the system searches for the most relevant course materials in real time based on the context of the query, and then generates a response. This process is not merely a simple call to a large language model (LLM), but rather a material-grounded question answering system tailored to the course content—ensuring both high reliability and accuracy in learning support.
Sunjun Kweon, the first author of the study and head teaching assistant for the course, explained, “Previously, TAs were overwhelmed with repetitive and basic questions—such as concepts already covered in class or simple definitions—which made it difficult to focus on more meaningful inquiries.” He added, “After introducing the VTA, students began to reduce repeated questions and focus on more essential ones. As a result, the burden on TAs was significantly reduced, allowing us to concentrate on providing more advanced learning support.”
In fact, compared to the previous year’s course, the number of questions that required direct responses from human TAs decreased by approximately 40%.
< Photo 3. A student working with VTA. >
The VTA, which was operated over a 14-week period, was actively used by more than half of the enrolled students, with a total of 3,869 Q&A interactions recorded. Notably, students without a background in AI or with limited prior knowledge tended to use the VTA more frequently, indicating that the system provided practical support as a learning aid, especially for those who needed it most.
The analysis also showed that students tended to ask the VTA more frequently about theoretical concepts than they did with human TAs. This suggests that the AI teaching assistant created an environment where students felt free to ask questions without fear of judgment or discomfort, thereby encouraging more active engagement in the learning process.
According to surveys conducted before, during, and after the course, students reported increased trust, response relevance, and comfort with the VTA over time. In particular, students who had previously hesitated to ask human TAs questions showed higher levels of satisfaction when interacting with the AI teaching assistant.
< Figure 1. Internal structure of the AI Teaching Assistant (VTA) applied in this course. It follows a Retrieval-Augmented Generation (RAG) structure that builds a vector database from course materials (PDFs, recorded lectures, coding practice materials, etc.), searches for relevant documents based on student questions and conversation history, and then generates responses based on them. >
Professor Yoonjae Choi, the lead instructor of the course and principal investigator of the study, stated, “The significance of this research lies in demonstrating that AI technology can provide practical support to both students and instructors. We hope to see this technology expanded to a wider range of courses in the future.”
The research team has released the system’s source code on GitHub, enabling other educational institutions and researchers to develop their own customized learning support systems and apply them in real-world classroom settings.
< Figure 2. Initial screen of the AI Teaching Assistant (VTA) introduced in the "Programming for AI" course. It asks for student ID input along with simple guidelines, a mechanism to ensure that only registered students can use it, blocking indiscriminate external access and ensuring limited use based on students. >
The related paper, titled “A Large-Scale Real-World Evaluation of an LLM-Based Virtual Teaching Assistant,” was accepted on May 9, 2025, to the Industry Track of ACL 2025, one of the most prestigious international conferences in the field of Natural Language Processing (NLP), recognizing the excellence of the research.
< Figure 3. Example conversation with the AI Teaching Assistant (VTA). When a student inputs a class-related question, the system internally searches for relevant class materials and then generates an answer based on them. In this way, VTA provides learning support by reflecting class content in context. >
This research was conducted with the support of the KAIST Center for Teaching and Learning Innovation, the National Research Foundation of Korea, and the National IT Industry Promotion Agency.
2025.06.05 View 600 -
RAIBO Runs over Walls with Feline Agility... Ready for Effortless Search over Mountaineous and Rough Terrains
< Photo 1. Research Team Photo (Professor Jemin Hwangbo, second from right in the front row) >
KAIST's quadrupedal robot, RAIBO, can now move at high speed across discontinuous and complex terrains such as stairs, gaps, walls, and debris. It has demonstrated its ability to run on vertical walls, leap over 1.3-meter-wide gaps, sprint at approximately 14.4 km/h over stepping stones, and move quickly and nimbly on terrain combining 30° slopes, stairs, and stepping stones. RAIBO is expected to be deployed soon for practical missions such as disaster site exploration and mountain searches.
Professor Jemin Hwangbo's research team in the Department of Mechanical Engineering at our university announced on June 3rd that they have developed a quadrupedal robot navigation framework capable of high-speed locomotion at 14.4 km/h (4m/s) even on discontinuous and complex terrains such as walls, stairs, and stepping stones.
The research team developed a quadrupedal navigation system that enables the robot to reach its target destination quickly and safely in complex and discontinuous terrain.
To achieve this, they approached the problem by breaking it down into two stages: first, developing a planner for planning foothold positions, and second, developing a tracker to accurately follow the planned foothold positions.
First, the planner module quickly searches for physically feasible foothold positions using a sampling-based optimization method with neural network-based heuristics and verifies the optimal path through simulation rollouts.
While existing methods considered various factors such as contact timing and robot posture in addition to foothold positions, this research significantly reduced computational complexity by setting only foothold positions as the search space. Furthermore, inspired by the walking method of cats, the introduction of a structure where the hind feet step on the same spots as the front feet further significantly reduced computational complexity.
< Figure 1. High-speed navigation across various discontinuous terrains >
Second, the tracker module is trained to accurately step on planned positions, and tracking training is conducted through a generative model that competes in environments of appropriate difficulty.
The tracker is trained through reinforcement learning to accurately step on planned plots, and during this process, a generative model called the 'map generator' provides the target distribution.
This generative model is trained simultaneously and adversarially with the tracker to allow the tracker to progressively adapt to more challenging difficulties. Subsequently, a sampling-based planner was designed to generate feasible foothold plans that can reflect the characteristics and performance of the trained tracker.
This hierarchical structure showed superior performance in both planning speed and stability compared to existing techniques, and experiments proved its high-speed locomotion capabilities across various obstacles and discontinuous terrains, as well as its general applicability to unseen terrains.
Professor Jemin Hwangbo stated, "We approached the problem of high-speed navigation in discontinuous terrain, which previously required a significantly large amount of computation, from the simple perspective of how to select the footprint positions. Inspired by the placements of cat's paw, allowing the hind feet to step where the front feet stepped drastically reduced computation. We expect this to significantly expand the range of discontinuous terrain that walking robots can overcome and enable them to traverse it at high speeds, contributing to the robot's ability to perform practical missions such as disaster site exploration and mountain searches."
This research achievement was published in the May 2025 issue of the international journal Science Robotics.
Paper Title: High-speed control and navigation for quadrupedal robots on complex and discrete terrain, (https://www.science.org/doi/10.1126/scirobotics.ads6192)YouTube Link: https://youtu.be/EZbM594T3c4?si=kfxLF2XnVUvYVIyk
2025.06.04 View 790 -
KAIST Develops Virtual Staining Technology for 3D Histopathology
Moving beyond traditional methods of observing thinly sliced and stained cancer tissues, a collaborative international research team led by KAIST has successfully developed a groundbreaking technology. This innovation uses advanced optical techniques combined with an artificial intelligence-based deep learning algorithm to create realistic, virtually stained 3D images of cancer tissue without the need for serial sectioning nor staining. This breakthrough is anticipated to pave the way for next-generation non-invasive pathological diagnosis.
< Photo 1. (From left) Juyeon Park (Ph.D. Candidate, Department of Physics), Professor YongKeun Park (Department of Physics) (Top left) Professor Su-Jin Shin (Gangnam Severance Hospital), Professor Tae Hyun Hwang (Vanderbilt University School of Medicine) >
KAIST (President Kwang Hyung Lee) announced on the 26th that a research team led by Professor YongKeun Park of the Department of Physics, in collaboration with Professor Su-Jin Shin's team at Yonsei University Gangnam Severance Hospital, Professor Tae Hyun Hwang's team at Mayo Clinic, and Tomocube's AI research team, has developed an innovative technology capable of vividly displaying the 3D structure of cancer tissues without separate staining.
For over 200 years, conventional pathology has relied on observing cancer tissues under a microscope, a method that only shows specific cross-sections of the 3D cancer tissue. This has limited the ability to understand the three-dimensional connections and spatial arrangements between cells.
To overcome this, the research team utilized holotomography (HT), an advanced optical technology, to measure the 3D refractive index information of tissues. They then integrated an AI-based deep learning algorithm to successfully generate virtual H&E* images.* H&E (Hematoxylin & Eosin): The most widely used staining method for observing pathological tissues. Hematoxylin stains cell nuclei blue, and eosin stains cytoplasm pink.
The research team quantitatively demonstrated that the images generated by this technology are highly similar to actual stained tissue images. Furthermore, the technology exhibited consistent performance across various organs and tissues, proving its versatility and reliability as a next-generation pathological analysis tool.
< Figure 1. Comparison of conventional 3D tissue pathology procedure and the 3D virtual H&E staining technology proposed in this study. The traditional method requires preparing and staining dozens of tissue slides, while the proposed technology can reduce the number of slides by up to 10 times and quickly generate H&E images without the staining process. >
Moreover, by validating the feasibility of this technology through joint research with hospitals and research institutions in Korea and the United States, utilizing Tomocube's holotomography equipment, the team demonstrated its potential for full-scale adoption in real-world pathological research settings.
Professor YongKeun Park stated, "This research marks a major advancement by transitioning pathological analysis from conventional 2D methods to comprehensive 3D imaging. It will greatly enhance biomedical research and clinical diagnostics, particularly in understanding cancer tumor boundaries and the intricate spatial arrangements of cells within tumor microenvironments."
< Figure 2. Results of AI-based 3D virtual H&E staining and quantitative analysis of pathological tissue. The virtually stained images enabled 3D reconstruction of key pathological features such as cell nuclei and glandular lumens. Based on this, various quantitative indicators, including cell nuclear distribution, volume, and surface area, could be extracted. >
This research, with Juyeon Park, a student of the Integrated Master’s and Ph.D. Program at KAIST, as the first author, was published online in the prestigious journal Nature Communications on May 22.
(Paper title: Revealing 3D microanatomical structures of unlabeled thick cancer tissues using holotomography and virtual H&E staining.
[https://doi.org/10.1038/s41467-025-59820-0]
This study was supported by the Leader Researcher Program of the National Research Foundation of Korea, the Global Industry Technology Cooperation Center Project of the Korea Institute for Advancement of Technology, and the Korea Health Industry Development Institute.
2025.05.26 View 1251 -
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 1511 -
KAIST and Mainz Researchers Unveil 3D Magnon Control, Charting a New Course for Neuromorphic and Quantum Technologies
< Professor Se Kwon Kim of the Department of Physics (left), Dr. Zarzuela of the University of Mainz, Germany (right) >
What if the magnon Hall effect, which processes information using magnons (spin waves) capable of current-free information transfer with magnets, could overcome its current limitation of being possible only on a 2D plane? If magnons could be utilized in 3D space, they would enable flexible design, including 3D circuits, and be applicable in various fields such as next-generation neuromorphic (brain-mimicking) computing structures, similar to human brain information processing. KAIST and an international joint research team have, for the first time in the world, predicted a 3D magnon Hall effect, demonstrating that magnons can move freely and complexly in 3D space, transcending the conventional concept of magnons.
KAIST (President Kwang Hyung Lee) announced on May 22nd that Professor Se Kwon Kim of the Department of Physics, in collaboration with Dr. Ricardo Zarzuela of the University of Mainz, Germany, has revealed that the interaction between magnons (spin waves) and solitons (spin vortices) within complex magnetic structures (topologically textured frustrated magnets) is not simple, but complex in a way that enables novel functionalities.
Magnons (spin waves), which can transmit information like electron movement, are garnering attention as a next-generation information processing technology that transmits information without using current, thus generating no heat. Until now, magnon research has focused on simple magnets where spins are neatly aligned in one direction, and the mathematics describing this was a relatively simple 'Abelian gauge theory.'
The research team demonstrated, for the first time in the world, that in complex spin structures like frustrated magnets, magnons interact and become entangled in complex ways from various directions. They applied an advanced mathematical framework, 'non-Abelian gauge theory,' to describe this movement, which is a groundbreaking achievement.
This research presents the possibility of future applications in low-power logic devices using magnons and topology-based quantum information processing technologies, indicating a potential paradigm shift in future information technology.
In conventional linear magnetic materials, the value representing the magnetic state (order parameter) is given as a vector. In magnonics research based on this, it has been interpreted that a U(1) Abelian gauge field is induced when magnons move in soliton structures like skyrmions. This means that the interaction between solitons and magnons has a structure similar to quantum electrodynamics (QED), which has successfully explained various experimental results such as the magnon Hall effect in 2D magnets.
< Figure. Schematic diagram of non-Abelian magnon quantum chromodynamics describing the dynamics of three types of magnons discovered for the first time in this study.>
However, through this research, the team theoretically revealed that in frustrated magnets, the order parameter must be expressed not as a simple vector but as a quaternion. As a result, the gauge field experienced by magnons resembles an SU(3) non-Abelian gauge field, rather than a simple U(1) Abelian gauge field.
This implies that within frustrated magnets, there are not one or two types of magnons seen in conventional magnets, but three distinct types of magnons, each interacting and intricately entangled with solitons. This structure is highly significant as it resembles quantum chromodynamics (QCD) that describes the strong interaction between quarks mediated by gluons rather than quantum electrodynamics (QED) that describes electromagnetic forces.
Professor Se Kwon Kim stated, "This research presents a powerful theoretical framework to explain the dynamics of magnons occurring within the complex order of frustrated magnets," adding, "By pioneering non-Abelian magnonics, it will be a conceptual turning point that can influence quantum magnetism research as a whole."
The research results, with Dr. Ricardo Zarzuela of the University of Mainz, Germany, as the first author, were published in the world-renowned physics journal Physical Review Letters on May 6th.※ Paper title: "Non-Abelian Gauge Theory for Magnons in Topologically Textured Frustrated Magnets," Phys. Rev. Lett. 134, 186701 (2025)DOI: https://doi.org/10.1103/PhysRevLett.134.186701
This research was supported by the Brain Pool Plus program of the National Research Foundation of Korea.
2025.05.22 View 1410 -
KAIST School of Computing Unveils 'KRAFTON Building,' A Symbol of Collective Generosity
< (From the fifth from the left) Provost and Executive Vice President Gyun Min Lee, Auditor Eun Woo Lee, President Kwang-Hyung Lee, Dean of the School of Computing Seok-Young Ryu, former Krafton member and donor Woong-Hee Cho, Krafton Chairman Byung-Gyu Chang >
KAIST announced on May 20th the completion of the expansion building for its School of Computing, the "KRAFTON Building." The project began in June 2021 with an ₩11 billion donation from KRAFTON and its employees, eventually growing to ₩11.7 billion with contributions from 204 donors.
Designed as a "Pay It Forward" space, the building aims to enable alumni to pass on the gratitude they received from the school to their juniors and foster connection. Byung-Gyu Chang, Chairman of KRAFTON and a KAIST alumnus, expressed his joy, stating, "I am very pleased that the first building created by alumni donations within KAIST is now complete, and I hope it will continue to be a space for communication, challenges, and growth that connects to the next generation."
The completion ceremony, held today at 3 PM in front of the KRAFTON SoC (School of Computing) Building at KAIST's main campus, was attended by over 100 people, including Chairman Byung-Gyu Chang, KAIST President Kwang-Hyung Lee, and Dean Seok-Young Ryu of the KAIST School of Computing.
The building's inception dates back to June 2021, with an ₩11 billion donation from the gaming company KRAFTON and its current and former members, dedicated to nurturing future software talent at KAIST. Four alumni, including KRAFTON Chairman Byung-Gyu Chang, who graduated from the KAIST School of Computing, were the first to pledge donations. This initial act inspired more participants, leading to ₩5.5 billion in individual donations from a total of 11 people. KRAFTON Inc. then matched this amount, bringing the total donation to ₩11 billion.
Since 2021, KRAFTON Inc. has operated a "Matching Grant" program, a donation culture initiative driven by its members. This system allows the company to match funds voluntarily raised by its employees, aiming to encourage active social participation and the creation of social value among its members.
Following this, another 11 KAIST alumni from Devsisters Inc., famous for the Cookie Run series, joined the donation effort. This wave of generosity expanded to include a total of 204 participants, comprising graduates, alumni professors, and current students, acting as a catalyst for the spread of a donation culture within the campus. To date, approximately ₩11.7 billion has been raised for the expansion of the School of Computing building. Furthermore, small donations, including those from alumni and the general public, have continuously grown, reaching over 50,000 instances from 2021 to May 2025.
The funds raised through donations were used to construct a 2,000-pyeong (approximately 6,600 square meters) building for individuals who, like Chairman Byung-Gyu Chang, will unleash their potential and become global leaders. The building was named "KRAFTON SoC (KRAFTON SoC)," and KRAFTON Inc. has further pledged additional donations for the building's maintenance over the next 10 years.
The newly completed KRAFTON Building is a six-story structure. From the second floor up, it features research labs for 20 professors and graduate students to freely pursue their research, along with large lecture halls. The first floor is designed as a meeting place for current students, alumni, and seniors, serving as a space to remember those who came before them.
The four lecture halls on the first floor are designated as "Immersion Camp Classrooms." During the summer and winter sessions, these rooms will be used for intensive month-long courses focused on improving coding and collaboration skills. During regular semesters, they will be utilized for other lectures.
Additionally, to support the physical and mental well-being of those weary from study and research, the building includes a small café on the first floor, a fitness center on the second floor, a Pilates studio on the fifth floor, and a soundproof band practice room in the basement.
Dean Seok-Young Ryu of the School of Computing explained, "The motivation for this wave of donations began with gratitude for the excellent professors and wonderful students, the free and open communication, the comfortable acceptance of diversity among various members, and the time when we could fearlessly dream. We cannot fully repay those who provided us with such precious time and space, but instead, this will be a 'Pay It Forward' space, a space of connection, where we share this gratitude with our juniors."
Alumnus Byung-Gyu Chang shared, "KAIST is more than just an academic foundation for me; it's a meaningful place that helped me set the direction for my life. I am very happy that this space, born from the desire of KRAFTON's members and myself to give back the opportunities and learning we received to the next generation, is completed today. I hope this space becomes a small but warm echo for KAIST members who freely communicate, challenge themselves, and grow."
< Congratulatory speech by alumnus Byung-Gyu Chang >
President Kwang-Hyung Lee stated, "The KRAFTON SoC, the expanded building for the School of Computing, is not just a space; it is the culmination of the KAIST community spirit created by alumni, current students, and faculty. I sincerely thank everyone who participated in this meaningful donation, which demonstrates the power of sharing and connection."
< Commemorative speech by President Kwang-Hyung Lee >
On a related note, the KAIST Development Foundation is actively promoting the "TeamKAIST" campaign for the general public and KAIST alumni to meet more "Daddy Long-Legs" (benefactors) for KAIST.
Website: https://giving.kaist.ac.kr/ko/sub01/sub0103_1.php
2025.05.21 View 977 -
Life Springs at KAIST: A Tale of Two Special Campus Families
A Gift of Life on Teachers' Day: Baby Geese Born at KAIST Pond
On Teachers' Day, a meaningful miracle of life arrived at the KAIST campus. A pair of geese gave birth to two goslings by the duck pond.
< On Teachers' Day, a pair of geese and their goslings leisurely swim in the pond. >
The baby goslings, covered in yellow down, began exploring the pond's edge, scurrying about, while their aunt geese steadfastly stood by. Their curious glances, watchful gazes, playful hops on waterside rocks, and the procession of babies swimming behind their parents in the water melted the hearts of onlookers.
< As night falls on the duck pond, the goose family gathers among the reeds. >
This special new life, born on Teachers' Day, seems to symbolize the day's meaning of "care" and "growth." This wondrous scene of life brought warm comfort and joy to KAIST members, adding the inspiration of nature to a campus that is a space for research and learning.
< Under the protection of the adult geese, the goslings take their first steps, exploring the pond's grassy areas and rocks. >
This adorable family is already roaming the area leisurely, like the pond's owners. With the joy of life added to the spring-filled pond, warm smiles are spreading across the KAIST campus.
< The geese look around, surveying their surroundings, while caring for their goslings. >
The pond has now become a small but special haven for students and staff. This goose family, arriving on Teachers' Day, quietly reminds us of the meaning of care and learning conveyed by nature.
< The goose family shows care and growth, and warm moments together are anticipated. >
---
On Children's Day 2025, a Duck Becomes a Mother
In July 2024, a special guest arrived at the KAIST campus. With soft yellow down, waddling gait, and a flat beak, it was undeniably a baby duck. However, for some reason, its mother was nowhere to be seen. Given that it wasn't afraid of people and followed them well, it was clear that someone had abandoned the duck.
Fortunately, the baby duck was safely rescued thanks to prompt reporting by students.
< Two ducks found on a corner of campus, immediately after their rescue in summer 2024. >
The ducks, newly integrated into KAIST, seemed to adapt relatively peacefully to campus life. As new additions, they couldn't blend in with the existing goose flock that had settled on campus, but the geese didn't ostracize them either. Perhaps because they were awkward neighbors, there was hope that the ducks would soon join the existing goose flock.
< Following their rescue based on a student's report in summer 2024, the ducks adapted to campus life under the protection of the campus facility team and Professor Won Do Heo. >
Professor Won Do Heo of the Department of Biological Sciences, widely known as "Goose Dad," stepped forward to protect them along with the KAIST facility team. Professor Heo is well-known for consistently observing and protecting the campus geese and ducks, which are practically symbols of KAIST. Thanks to the care of the staff and Professor Heo, the two ducks were safely released back onto campus approximately one month after their rescue.
< A moment on campus: Before winter, the ducks lived separately from the goose flock, maintaining a certain distance. While there were no conflicts, they rarely socialized. >
However, as winter passed, sad news arrived. One duck went missing, and the remaining one was found injured by the pond. While the policy of the facility team and Professor Heo was to minimize intervention to allow campus animals to maintain their natural state, saving the injured duck was the top priority. After being isolated again for a month of recovery, the duck fully recovered and was able to greet spring under the sun.
< The mother duck left alone in winter: One went missing, and the remaining one was found injured. After indoor isolation and recovery, she was released back onto campus in the spring. >
As spring, the ducks' breeding season, began, Professor Heo decided to offer a little more help. When signs of egg-laying appeared, he consistently provided "special meals for pregnant mothers" throughout March. On the morning of May 5th, Children's Day, 28 days after the mother duck began incubating her eggs with the care and attention of KAIST members, new life finally hatched. It was a precious outcome achieved solely by the duck that had survived abandonment and injury, with no special protection other than food.
The duck, having overcome hardship and injury to stand alone, has now formed a new family. Although there is still some distance from the existing goose flock, it is expected that they will naturally find their place in the campus ecosystem, as KAIST's geese are not aggressive or exclusive. The KAIST goose flock already has experience protecting and raising five ducklings.
< A new beginning by the pond on Children's Day: On the morning of May 5th, the 28th day of incubation, four ducklings hatched by the pond. This was a natural hatching, achieved without protective equipment. >
A single duck brought a special spring to the KAIST campus on Children's Day. The outcome achieved by that small life, leading to the birth of a new family, also symbolizes the harmonious coexistence of people and animals on the KAIST campus. The careful intervention of KAIST members, providing only the necessary assistance from rescue to hatching, makes us reconsider what "desirable coexistence between animals and people" truly means.
2025.05.21 View 1193 -
“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 2070 -
Decoding Fear: KAIST Identifies An Affective Brain Circuit Crucial for Fear Memory Formation by Non-nociceptive Threat Stimulus
Fear memories can form in the brain following exposure to threatening situations such as natural disasters, accidents, or violence. When these memories become excessive or distorted, they can lead to severe mental health disorders, including post-traumatic stress disorder (PTSD), anxiety disorders, and depression. However, the mechanisms underlying fear memory formation triggered by affective pain rather than direct physical pain have remained largely unexplored – until now.
A KAIST research team has identified, for the first time, a brain circuit specifically responsible for forming fear memories in the absence of physical pain, marking a significant advance in understanding how psychological distress is processed and drives fear memory formation in the brain. This discovery opens the door to the development of targeted treatments for trauma-related conditions by addressing the underlying neural pathways.
< Photo 1. (from left) Professor Jin-Hee Han, Dr. Junho Han and Ph.D. Candidate Boin Suh of the Department of Biological Sciences >
KAIST (President Kwang-Hyung Lee) announced on May 15th that the research team led by Professor Jin-Hee Han in the Department of Biological Sciences has identified the pIC-PBN circuit*, a key neural pathway involved in forming fear memories triggered by psychological threats in the absence of sensory pain. This groundbreaking work was conducted through experiments with mice.*pIC–PBN circuit: A newly identified descending neural pathway from the posterior insular cortex (pIC) to the parabrachial nucleus (PBN), specialized for transmitting psychological threat information.
Traditionally, the lateral parabrachial nucleus (PBN) has been recognized as a critical part of the ascending pain pathway, receiving pain signals from the spinal cord. However, this study reveals a previously unknown role for the PBN in processing fear induced by non-painful psychological stimuli, fundamentally changing our understanding of its function in the brain.
This work is considered the first experimental evidence that 'emotional distress' and 'physical pain' are processed through different neural circuits to form fear memories, making it a significant contribution to the field of neuroscience. It clearly demonstrates the existence of a dedicated pathway (pIC-PBN) for transmitting emotional distress.
The study's first author, Dr. Junho Han, shared the personal motivation behind this research: “Our dog, Lego, is afraid of motorcycles. He never actually crashed into one, but ever since having a traumatizing event of having a motorbike almost run into him, just hearing the sound now triggers a fearful response. Humans react similarly – even if you didn’t have a personal experience of being involved in an accident, a near-miss or exposure to alarming media can create lasting fear memories, which may eventually lead to PTSD.”
He continued, “Until now, fear memory research has mainly relied on experimental models involving physical pain. However, much of real-world human fears arise from psychological threats, rather than from direct physical harm. Despite this, little was known about the brain circuits responsible for processing these psychological threats that can drive fear memory formation.”
To investigate this, the research team developed a novel fear conditioning model that utilizes visual threat stimuli instead of electrical shocks. In this model, mice were exposed to a rapidly expanding visual disk on a ceiling screen, simulating the threat of an approaching predator. This approach allowed the team to demonstrate that fear memories can form in response to a non-nociceptive, psychological threat alone, without the need for physical pain.
< Figure 1. Artificial activation of the posterior insular cortex (pIC) to lateral parabrachial nucleus (PBN) neural circuit induces anxiety-like behaviors and fear memory formation in mice. >
Using advanced chemogenetic and optogenetic techniques, the team precisely controlled neuronal activity, revealing that the lateral parabrachial nucleus (PBN) is essential to form fear memories in response to visual threats. They further traced the origin of these signals to the posterior insular cortex (pIC), a region known to process negative emotions and pain, confirming a direct connection between the two areas.
The study also showed that inhibiting the pIC–PBN circuit significantly reduced fear memory formation in response to visual threats, without affecting innate fear responses or physical pain-based learning. Conversely, artificially activating this circuit alone was sufficient to drive fear memory formation, confirming its role as a key pathway for processing psychological threat information.
< Figure 2. Schematic diagram of brain neural circuits transmitting emotional & physical pain threat signals. Visual threat stimuli do not involve physical pain but can create an anxious state and form fear memory through the affective pain signaling pathway. >
Professor Jin-Hee Han commented, “This study lays an important foundation for understanding how emotional distress-based mental disorders, such as PTSD, panic disorder, and anxiety disorder, develop, and opens new possibilities for targeted treatment approaches.”
The findings, authored by Dr. Junho Han (first author), Ph.D. candidate Boin Suh (second author), and Dr. Jin-Hee Han (corresponding author) of the Department of Biological Sciences, were published online in the international journal Science Advances on May 9, 2025.※ Paper Title: A top-down insular cortex circuit crucial for non-nociceptive fear learning. Science Advances (https://doi.org/10.1101/2024.10.14.618356)※ Author Information: Junho Han (first author), Boin Suh (second author), and Jin-Hee Han (corresponding author)
This research was supported by grants from the National Research Foundation of Korea (NRF-2022M3E5E8081183 and NRF-2017M3C7A1031322).
2025.05.15 View 1641 -
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 3021 -
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 2671