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Key Figures in the Establishment of KAIST, Specially Invited to the Presidential Office’s National Appointment Ceremony
KAIST announced on August 6 that Professor Emeritus Jung-Woong Ra from the Department of Electrical Engineering and Won-ki Kwon, former Vice Minister of the Ministry of Science and Technology, who played pivotal roles in the establishment of KAIST, were selected as special guests for the 'National Appointment Ceremony' hosted by the Presidential Office on August 15th. The Presidential Office selected special invitees across eight categories for the ceremony. These include individuals born in 1945 (referred to as 'Liberation Babies'), those involved in the founding of KAIST in 1971, independence activists and national patriots, overseas workers in Germany and the Middle East, AI industry professionals, residents from regions facing depopulation, leading figures in K-culture, military personnel, firefighters, police officers, families of fallen public servants and victims of social disasters, as well as promising talents in economics, science, culture, and the arts. Considering the historical significance of its establishment and its symbolic meaning for the development of national science and technology, KAIST Professor Emeritus Jung-Woong Ra, who was a key figure in the establishment of the Department of Electrical Engineering after being appointed as a professor in 1971, and former Vice Minister Kwon Won-ki, who was the first practical leader of the establishment project. Both were officially included on the special invitation list. Briefing from the Presidential Office regarding the 'National Appointment Ceremony' (2025.07.28) https://www.president.go.kr/newsroom/briefing/grehGMuP
2025.08.06
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KAIST Develops AI ‘MARIOH’ to Uncover and Reconstruct Hidden Multi-Entity Relationships
<(From Left) Professor Kijung Shin, Ph.D candidate Kyuhan Lee, and Ph.D candidate Geon Lee> Just like when multiple people gather simultaneously in a meeting room, higher-order interactions—where many entities interact at once—occur across various fields and reflect the complexity of real-world relationships. However, due to technical limitations, in many fields, only low-order pairwise interactions between entities can be observed and collected, which results in the loss of full context and restricts practical use. KAIST researchers have developed the AI model “MARIOH,” which can accurately reconstruct* higher-order interactions from such low-order information, opening up innovative analytical possibilities in fields like social network analysis, neuroscience, and life sciences. *Reconstruction: Estimating/reconstructing the original structure that has disappeared or was not observed. KAIST (President Kwang Hyung Lee) announced on the 5th that Professor Kijung Shin’s research team at the Kim Jaechul Graduate School of AI has developed an AI technology called “MARIOH” (Multiplicity-Aware Hypergraph Reconstruction), which can reconstruct higher-order interaction structures with high accuracy using only low-order interaction data. Reconstructing higher-order interactions is challenging because a vast number of higher-order interactions can arise from the same low-order structure. The key idea behind MARIOH, developed by the research team, is to utilize multiplicity information of low-order interactions to drastically reduce the number of candidate higher-order interactions that could stem from a given structure. In addition, by employing efficient search techniques, MARIOH quickly identifies promising interaction candidates and uses multiplicity-based deep learning to accurately predict the likelihood that each candidate represents an actual higher-order interaction. <Figure 1. An example of recovering high-dimensional relationships (right) from low-dimensional paper co-authorship relationships (left) with 100% accuracy, using MARIOH technology.> Through experiments on ten diverse real-world datasets, the research team showed that MARIOH reconstructed higher-order interactions with up to 74% greater accuracy compared to existing methods. For instance, in a dataset on co-authorship relations (source: DBLP), MARIOH achieved a reconstruction accuracy of over 98%, significantly outperforming existing methods, which reached only about 86%. Furthermore, leveraging the reconstructed higher-order structures led to improved performance in downstream tasks, including prediction and classification. According to Kijung, “MARIOH moves beyond existing approaches that rely solely on simplified connection information, enabling precise analysis of the complex interconnections found in the real world.” Furthermore, “it has broad potential applications in fields such as social network analysis for group chats or collaborative networks, life sciences for studying protein complexes or gene interactions, and neuroscience for tracking simultaneous activity across multiple brain regions.” The research was conducted by Kyuhan Lee (Integrated M.S.–Ph.D. program at the Kim Jaechul Graduate School of AI at KAIST; currently a software engineer at GraphAI), Geon Lee (Integrated M.S.–Ph.D. program at KAIST), and Professor Kijung Shin. It was presented at the 41st IEEE International Conference on Data Engineering (IEEE ICDE), held in Hong Kong this past May. ※ Paper title: MARIOH: Multiplicity-Aware Hypergraph Reconstruction ※ DOI: https://doi.ieeecomputersociety.org/10.1109/ICDE65448.2025.00233 <Figure 2. An example of the process of recovering high-dimensional relationships using MARIOH technology> This research was supported by the Institute of Information & Communications Technology Planning & Evaluation (IITP) through the project “EntireDB2AI: Foundational technologies and software for deep representation learning and prediction using complete relational databases,” as well as by the National Research Foundation of Korea through the project “Graph Foundation Model: Graph-based machine learning applicable across various modalities and domains.”
2025.08.05
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Anti-Neuroinflammatory Natural Products from Isopod-Related Fungus Now Accessible via Chemical Synthesis
<(From left) Professor Sunkyu Han, Ph.D candidate Yoojin Lee, Ph.D candidate Taewan Kim> "Herpotrichone" is a natural substance that has been evaluated highly for its excellent ability to suppress inflammation in the brain and protect nerve cells, displaying significant potential to be developed as a therapeutic agent for neurodegenerative brain diseases such as Alzheimer's disease and Parkinson's disease. This substance could only be obtained in minute quantities from fungi that are symbiotic with isopods. However, KAIST researchers have succeeded in chemically synthesizing this rare natural product, thereby presenting the possibility for the development of next-generation drugs for neurodegenerative diseases. *Chemical Synthesis: A process of creating desired substances using chemical reactions. KAIST (President Kwang Hyung Lee) announced on the 31st of July that a research team led by Professor Sunkyu Han of the Department of Chemistry successfully synthesized the natural anti-neuroinflammatory substances 'herpotrichones A, B, and C' for the first time. Herpotrichone natural products are substances obtainable only in minute quantities from 'Herpotrichia sp. SF09', a symbiotic pill bug fungus, and possess a unique 6/6/6/6/3 pentacyclic framework consisting of five fused rings (four six-membered and one three-membered ring). Interestingly, this substance exhibits excellent anti-neuroinflammatory effects that suppress brain inflammatory reactions. Recently, its mechanism of action to protect nerve cells by inhibiting ferroptosis (iron-mediated cell death) was also reported, raising expectations for its potential as a therapeutic drug for brain diseases. Professor Han's research team devised a biosynthetically inspired strategy to chemically synthesize herpotrichoneS. The key to success was a named chemical reaction "Diels-Alder (DA) reaction". This reaction forms a six-membered ring by creating new bonds between carbon-based partners, much like two puzzle pieces interlocking to form a single ring. <Figure 2. Key Synthetic Strategy for Hypotricon A, B, and C Based on Hydrogen Bonding> Furthermore, the research team focused on a weak attractive phenomenon between molecules called "hydrogen bonding". By delicately designing and controlling this hydrogen bond, they were able to precisely induce the reaction to occur chemo-, regio- and stereoselectively, thereby synthesizing herpotrichone. Notably, without the pivotal hydrogen bond, only a small amount of the target natural product was formed or only undesirable byproducts were generated. The configuration of the C2’ hydroxyl moiety was essential in directing the desired transition states leading to the target natural products. Thanks to this induced hydrogen bonding, the reacting molecules approached the correct positions and went through an ideal transition state, allowing for the synthesis of herpotrichone C. This reaction principle was also successfully applied to herpotrichone A and B, enabling the successful synthesis of these natural products. During the key Diels-Alder reaction conducted in the laboratory, new molecular structures not yet discovered in nature were also formed. Some of these have a high probability of being novel natural products with excellent pharmacological activity, thus doubling the significance of this research for anticipating natural products through synthesis. Indeed, while Professor Han's research team conducted synthetic studies on herpotrichone A and B based on a 2019 paper by Chinese researchers who discovered and elucidated their structures, the research team observed the formation of undesired byproducts. Interestingly, in 2024, the same Chinese research team that discovered herpotrichones A and bn reported the discovery of a new natural product called herpotrichone C, which turned out to be the same substance as the major byproduct previously obtained by Professor Han's team en route to herpotrichones A and B. Professor Han stated, "This is the first total synthesis of a rare natural product with pharmacological activity related to neurodegenerative diseases and systematically presents the principle of biomimetic synthesis of complex natural products." He added, "It is expected to contribute to the development of novel natural product-based anti-neuroinflammatory therapeutics and biosynthesis research of this group of natural products." This research outcome, with Yoojin Lee, a master's and Ph.D. integrated course student in the Department of Chemistry, as the first author, was published on July 16th in the Journal of the American Chemical Society (JACS), one of the most prestigious academic journals in the field of chemistry. This research was supported by the National Research Foundation of Korea (NRF) Mid-career Researcher Support Program, the KAIST UP Project, the KAIST Grand Challenge 30 Project, and the KAIST Trans-Generational Collaborative Research Laboratory Project.
2025.08.04
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KAIST Successfully Presents the Future of AI Transformation and Physical AI Strategy at the 1st National Strategic Technology Forum
<(Front row, fourth from the right) President Kwang Hyung Lee of KAIST, (back row, fifth from the right) Forum co-host Representative Hyung-Doo Choi, (back row, sixth from the left) Forum co-host Representative Han-Kyu Kim, along with ruling and opposition party members of the Science, ICT, Broadcasting, and Communications Committee and the Trade, Industry, Energy, SMEs, and Startups Committee, as well as Professors Hoe-Jun Yoo and Jung Kim from KAIST)> KAIST (President Kwang Hyung Lee) announced on July that it had successfully held the “1st National Strategic Technology Forum” at the National Assembly Members' Office Building that day under the theme “The Future of Artificial Intelligence Transformation (AX): Physical AI.” This bipartisan policy forum aimed to discuss strategies for technology hegemony by leveraging Korea’s strengths in AI semiconductors and manufacturing. The forum was hosted by KAIST and co-organized by Representative Hyung-Du Choi (People Power Party), the secretary of the National Assembly's Science, ICT, Broadcasting, and Communications Committee, and Representative Han-Kyu Kim (Democratic Party), a member of the Trade, Industry, Energy, SMEs, and Startups Committee. It marks the beginning of a five-part forum series, scheduled monthly through the rest of the year except for October. The overarching theme, “Artificial Intelligence Transformation (AX),” was designed to address the structural changes reshaping industry, the economy, and society due to the spread of generative AI. < KAIST President Kwang Hyung Lee delivering his remarks > The first session focused on “Physical AI,” reflecting how AI innovation—sparked by the proliferation of large language models (LLMs)—is rapidly expanding into the physical realm through ultra-low-power, ultra-lightweight semiconductors. This includes applications in robotics, sensors, and edge devices. Physical AI refers to technologies that interact directly with the real world through AI integration with robotics, autonomous driving, and smart factories. It is drawing attention as a promising next-generation field where Korea can secure a strategic edge, given its strengths in semiconductors and manufacturing. <Hoi-Jun Yoo, Dean of the KAIST Graduate School of AI Semiconductor> Hoi-Jun Yoo, Dean of the KAIST Graduate School of AI Semiconductor, gave a presentation titled “The Second AI Innovation Enabled by Ultra-Low-Power AI Semiconductors and Lightweight AI Models,” covering semiconductor trends for implementing Physical AI, academic and industrial strategies for robotics and semiconductors, and Korea’s development direction for “K-Physical AI.” <Professor Jung Kim, the head of KAIST’s Department of Mechanical and Aerospace Engineering> Following that, Professor Jung Kim, the head of KAIST’s Department of Mechanical and Aerospace Engineering gave a talk on “Trends in Physical AI and Humanoid Robots,” predicting a new industrial paradigm shaped by AI-robot convergence. He presented global trends, Korea’s development trajectory, and survival strategies for humanoid robots that can supplement or replace human intellectual and physical functions. During the open discussion that followed, participating lawmakers and experts engaged in in-depth conversations about the need for bipartisan strategies and collaboration. Representative Hyung-Du Choi (People Power Party) stated, “Through this forum as a platform for public discourse, I will work to ensure that legislation and policy align with the direction of the science and technology field, and that necessary measures are taken promptly to strengthen national competitiveness.” Representative Han-Kyu Kim (Democratic Party) emphasized, “As strategic planning in science and technology accelerates, it becomes more difficult to coordinate policies involving multiple ministries. Forums like this, which enable ongoing communication among stakeholders, are instrumental in finding effective solutions.” KAIST President Kwang Hyung Lee remarked, “Although Korea is a latecomer in the generative AI field, we have a unique opportunity to gain strategic superiority in Physical AI, thanks to our technological capabilities in manufacturing, semiconductors, and robotics.” He added, “I hope lawmakers from both the ruling and opposition parties, along with experts, will come together regularly to devise practical policies and contribute to the advancement of Korea’s science and technology.” <Poster of National Strategic Technology Forum> This forum series aims to explore policy and institutional solutions to help Korea gain technological leadership in a global context where strategic technologies—such as AI, semiconductors, biotechnology, and energy—directly influence national security and economic sovereignty. Lawmakers from both the Science, ICT, Broadcasting, and Communications Committee and the Trade, Industry, Energy, SMEs, and Startups Committee will continue to participate, fostering bipartisan dialogue. The forums are coordinated by the KAIST Policy Research Institute for National Strategic Technologies.
2025.07.31
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Is 24-hour health monitoring possible with ambient light energy?
<(From left) Ph.D candidate Youngmin Sim, Ph.D candidate Do Yun Park, Dr. Chanho Park, Professor Kyeongha Kwon> Miniaturization and weight reduction of medical wearable devices for continuous health monitoring such as heart rate, blood oxygen saturation, and sweat component analysis remain major challenges. In particular, optical sensors consume a significant amount of power for LED operation and wireless transmission, requiring heavy and bulky batteries. To overcome these limitations, KAIST researchers have developed a next-generation wearable platform that enables 24-hour continuous measurement by using ambient light as an energy source and optimizing power management according to the power environment. KAIST (President Kwang Hyung Lee) announced on the 30th that Professor Kyeongha Kwon's team from the School of Electrical Engineering, in collaboration with Dr. Chanho Park’s team at Northwestern University in the U.S., has developed an adaptive wireless wearable platform that reduces battery load by utilizing ambient light. To address the battery issue of medical wearable devices, Professor Kyeongha Kwon’s research team developed an innovative platform that utilizes ambient natural light as an energy source. This platform integrates three complementary light energy technologies. <Figure1.The wireless wearable platform minimizes the energy required for light sources through i) Photometric system that directly utilizes ambient light passing through windows for measurements, ii) Photovoltaic system that receives power from high-efficiency photovoltaic cells and wireless power receiver coils, and iii) Photoluminescent system that stores light using photoluminescent materials and emits light in dark conditions to support the two aforementioned systems. In-sensor computing minimizes power consumption by wirelessly transmitting only essential data. The adaptive power management system efficiently manages power by automatically selecting the optimal mode among 11 different power modes through a power selector based on the power supply level from the photovoltaic system and battery charge status.> The first core technology, the Photometric Method, is a technique that adaptively adjusts LED brightness depending on the intensity of the ambient light source. By combining ambient natural light with LED light to maintain a constant total illumination level, it automatically dims the LED when natural light is strong and brightens it when natural light is weak. Whereas conventional sensors had to keep the LED on at a fixed brightness regardless of the environment, this technology optimizes LED power in real time according to the surrounding environment. Experimental results showed that it reduced power consumption by as much as 86.22% under sufficient lighting conditions. The second is the Photovoltaic Method using high-efficiency multijunction solar cells. This goes beyond simple solar power generation to convert light in both indoor and outdoor environments into electricity. In particular, the adaptive power management system automatically switches among 11 different power configurations based on ambient conditions and battery status to achieve optimal energy efficiency. The third innovative technology is the Photoluminescent Method. By mixing strontium aluminate microparticles* into the sensor’s silicone encapsulation structure, light from the surroundings is absorbed and stored during the day and slowly released in the dark. As a result, after being exposed to 500W/m² of sunlight for 10 minutes, continuous measurement is possible for 2.5 minutes even in complete darkness. *Strontium aluminate microparticles: A photoluminescent material used in glow-in-the-dark paint or safety signs, which absorbs light and emits it in the dark for an extended time. These three technologies work complementarily—during bright conditions, the first and second methods are active, and in dark conditions, the third method provides additional support—enabling 24-hour continuous operation. The research team applied this platform to various medical sensors to verify its practicality. The photoplethysmography sensor monitors heart rate and blood oxygen saturation in real time, allowing early detection of cardiovascular diseases. The blue light dosimeter accurately measures blue light, which causes skin aging and damage, and provides personalized skin protection guidance. The sweat analysis sensor uses microfluidic technology to simultaneously analyze salt, glucose, and pH in sweat, enabling real-time detection of dehydration and electrolyte imbalances. Additionally, introducing in-sensor data computing significantly reduced wireless communication power consumption. Previously, all raw data had to be transmitted externally, but now only the necessary results are calculated and transmitted within the sensor, reducing data transmission requirements from 400B/s to 4B/s—a 100-fold decrease. To validate performance, the research tested the device on healthy adult subjects in four different environments: bright indoor lighting, dim lighting, infrared lighting, and complete darkness. The results showed measurement accuracy equivalent to that of commercial medical devices in all conditions A mouse model experiment confirmed accurate blood oxygen saturation measurement in hypoxic conditions. <Frigure2.The multimodal device applying the energy harvesting and power management platform consists of i) photoplethysmography (PPG) sensor, ii) blue light dosimeter, iii) photoluminescent microfluidic channel for sweat analysis and biomarker sensors (chloride ion, glucose, and pH), and iv) temperature sensor. This device was implemented with flexible printed circuit board (fPCB) to enable attachment to the skin. A silicon substrate with a window that allows ambient light and measurement light to pass through, along with photoluminescent encapsulation layer, encapsulates the PPG, blue light dosimeter, and temperature sensors, while the photoluminescent microfluidic channel is attached below the photoluminescent encapsulation layer to collect sweat> Professor Kyeongha Kwon of KAIST, who led the research, stated, “This technology will enable 24-hour continuous health monitoring, shifting the medical paradigm from treatment-centered to prevention-centered shifting the medical paradigm from treatment-centered to prevention-centered,” further stating that “cost savings through early diagnosis as well as strengthened technological competitiveness in the next-generation wearable healthcare market are anticipated.” This research was published on July 1 in the international journal Nature Communications, with Do Yun Park, a doctoral student in the AI Semiconductor Graduate Program, as co–first author. ※ Paper title: Adaptive Electronics for Photovoltaic, Photoluminescent and Photometric Methods in Power Harvesting for Wireless and Wearable Sensors ※ DOI: https://doi.org/10.1038/s41467-025-60911-1 ※ URL: https://www.nature.com/articles/s41467-025-60911-1 This research was supported by the National Research Foundation of Korea (Outstanding Young Researcher Program and Regional Innovation Leading Research Center Project), the Ministry of Science and ICT and Institute of Information & Communications Technology Planning & Evaluation (IITP) AI Semiconductor Graduate Program, and the BK FOUR Program (Connected AI Education & Research Program for Industry and Society Innovation, KAIST EE).
2025.07.30
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KAIST GESS Team Awarded Honorable Mention at 2025 Entrepreneurship Olympiad
<Photo: eaureco team at the final pitch> The KAIST Global Entrepreneurship Summer School (GESS) winning team, eaureco, earned an Honorable Mention at the 2025 Entrepreneurship Olympiad, held July 21–23 at Stanford Faculty Club and hosted by Techdev Academy. Competing in the college track, the team showcased their innovative solution among participants from top institutions including Stanford University, UC Berkeley, UCLA, and UC San Diego. Team eaureco—comprising KAIST undergraduate and graduate students Jiwon Park(Semiconductor Systems Engineering), Si Li Sara (Julia) Aow, Lunar Sebastian Widjaja (both Civil & Environmental Engineering), Seoyeon Jang (Impact MBA), and Isabel Alexandra Cornejo Lima (BTM/Global Digital Innovation)—presented a B2B solution that upcycles discarded seaweed into biodegradable ice packs for cold-chain companies. Their business model was recognized for its alignment with sustainability, resource circulation, and social impact goals. <Photo: eaureco team preparing for the final pitch> The team’s ability to rapidly adapt their pitch based on mentor feedback and clearly communicate the value of their idea to judges contributed to their recognition. This accomplishment further highlights the impact of KAIST's GESS program, which supports students in building real-world entrepreneurial skills through immersive learning experiences in Silicon Valley. “The GESS program helped us refine every aspect of our business idea—from identifying the problem to developing a go-to-market strategy,” said Si Li Sara (Julia) Aow, a member of the eaureco team. “We’re grateful for the opportunity to showcase our work on a global stage and hope to continue developing innovations that drive meaningful change.” “This award reaffirms the creative potential and practical capabilities of KAIST students in global innovation ecosystems,” said Dr. Soyoung Kim, Vice President of International Office. “We will continue to invest in programs like GESS to empower our students as future leaders in entrepreneurship.” The Entrepreneurship Olympiad is a global event designed to foster innovation, entrepreneurship, and collaboration among young change-makers. This year’s program featured keynote talks, panels, and workshops led by industry pioneers including Marc Tarpenning (Co-founder, Tesla Motors), Pat Brown (Founder, Impossible Foods), and other influential entrepreneurs from the biotech, fintech, and deeptech sectors. The Honorable Mention recognition underscores KAIST’s commitment to global entrepreneurship education and the growing international visibility of the GESS program.
2025.07.29
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Vulnerability Found: One Packet Can Paralyze Smartphones
<(From left) Professor Yongdae Kim, PhD candidate Tuan Dinh Hoang, PhD candidate Taekkyung Oh from KAIST, Professor CheolJun Park from Kyung Hee University; and Professor Insu Yun from KAIST> Smartphones must stay connected to mobile networks at all times to function properly. The core component that enables this constant connectivity is the communication modem (Baseband) inside the device. KAIST researchers, using their self-developed testing framework called 'LLFuzz (Lower Layer Fuzz),' have discovered security vulnerabilities in the lower layers of smartphone communication modems and demonstrated the necessity of standardizing 'mobile communication modem security testing.' *Standardization: In mobile communication, conformance testing, which verifies normal operation in normal situations, has been standardized. However, standards for handling abnormal packets have not yet been established, hence the need for standardized security testing. Professor Yongdae Kim's team from the School of Electrical Engineering at KAIST, in a joint research effort with Professor CheolJun Park's team from Kyung Hee University, announced on the 25th of July that they have discovered critical security vulnerabilities in the lower layers of smartphone communication modems. These vulnerabilities can incapacitate smartphone communication with just a single manipulated wireless packet (a data transmission unit in a network). In particular, these vulnerabilities are extremely severe as they can potentially lead to remote code execution (RCE) The research team utilized their self-developed 'LLFuzz' analysis framework to analyze the lower layer state transitions and error handling logic of the modem to detect security vulnerabilities. LLFuzz was able to precisely extract vulnerabilities caused by implementation errors by comparing and analyzing 3GPP* standard-based state machines with actual device responses. *3GPP: An international collaborative organization that creates global mobile communication standards. The research team conducted experiments on 15 commercial smartphones from global manufacturers, including Apple, Samsung Electronics, Google, and Xiaomi, and discovered a total of 11 vulnerabilities. Among these, seven were assigned official CVE (Common Vulnerabilities and Exposures) numbers, and manufacturers applied security patches for these vulnerabilities. However, the remaining four have not yet been publicly disclosed. While previous security research primarily focused on higher layers of mobile communication, such as NAS (Network Access Stratum) and RRC (Radio Resource Control), the research team concentrated on analyzing the error handling logic of mobile communication's lower layers, which manufacturers have often neglected. These vulnerabilities occurred in the lower layers of the communication modem (RLC, MAC, PDCP, PHY*), and due to their structural characteristics where encryption or authentication is not applied, operational errors could be induced simply by injecting external signals. *RLC, MAC, PDCP, PHY: Lower layers of LTE/5G communication, responsible for wireless resource allocation, error control, encryption, and physical layer transmission. The research team released a demo video showing that when they injected a manipulated wireless packet (malformed MAC packet) into commercial smartphones via a Software-Defined Radio (SDR) device using packets generated on an experimental laptop, the smartphone's communication modem (Baseband) immediately crashed ※ Experiment video: https://drive.google.com/file/d/1NOwZdu_Hf4ScG7LkwgEkHLa_nSV4FPb_/view?usp=drive_link The video shows data being normally transmitted at 23MB per second on the fast.com page, but immediately after the manipulated packet is injected, the transmission stops and the mobile communication signal disappears. This intuitively demonstrates that a single wireless packet can cripple a commercial device's communication modem. The vulnerabilities were found in the 'modem chip,' a core component of smartphones responsible for calls, texts, and data communication, making it a very important component. Qualcomm: Affects over 90 chipsets, including CVE-2025-21477, CVE-2024-23385. MediaTek: Affects over 80 chipsets, including CVE-2024-20076, CVE-2024-20077, CVE-2025-20659. Samsung: CVE-2025-26780 (targets the latest chipsets like Exynos 2400, 5400). Apple: CVE-2024-27870 (shares the same vulnerability as Qualcomm CVE). The problematic modem chips (communication components) are not only in premium smartphones but also in low-end smartphones, tablets, smartwatches, and IoT devices, leading to the widespread potential for user harm due to their broad diffusion. Furthermore, the research team experimentally tested 5G vulnerabilities in the lower layers and found two vulnerabilities in just two weeks. Considering that 5G vulnerability checks have not been generally conducted, it is possible that many more vulnerabilities exist in the mobile communication lower layers of baseband chips. Professor Yongdae Kim explained, "The lower layers of smartphone communication modems are not subject to encryption or authentication, creating a structural risk where devices can accept arbitrary signals from external sources." He added, "This research demonstrates the necessity of standardizing mobile communication modem security testing for smartphones and other IoT devices." The research team is continuing additional analysis of the 5G lower layers using LLFuzz and is also developing tools for testing LTE and 5G upper layers. They are also pursuing collaborations for future tool disclosure. The team's stance is that "as technological complexity increases, systemic security inspection systems must evolve in parallel." First author Tuan Dinh Hoang, a Ph.D. student in the School of Electrical Engineering, will present the research results in August at USENIX Security 2025, one of the world's most prestigious conferences in cybersecurity. ※ Paper Title: LLFuzz: An Over-the-Air Dynamic Testing Framework for Cellular Baseband Lower Layers (Tuan Dinh Hoang and Taekkyung Oh, KAIST; CheolJun Park, Kyung Hee Univ.; Insu Yun and Yongdae Kim, KAIST) ※ Usenix paper site: https://www.usenix.org/conference/usenixsecurity25/presentation/hoang (Not yet public), Lab homepage paper: https://syssec.kaist.ac.kr/pub/2025/LLFuzz_Tuan.pdf ※ Open-source repository: https://github.com/SysSec-KAIST/LLFuzz (To be released) This research was conducted with support from the Institute of Information & Communications Technology Planning & Evaluation (IITP) funded by the Ministry of Science and ICT.
2025.07.25
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Approaches to Human-Robot Interaction Using Biosignals
<(From left) Dr. Hwa-young Jeong, Professor Kyung-seo Park, Dr. Yoon-tae Jeong, Dr. Ji-hoon Seo, Professor Min-kyu Je, Professor Jung Kim > A joint research team led by Professor Jung Kim of KAIST Department of Mechanical Engineering and Professor Min-kyu Je of the Department of Electrical and Electronic Engineering recently published a review paper on the latest trends and advancements in intuitive Human-Robot Interaction (HRI) using bio-potential and bio-impedance in the internationally renowned academic journal 'Nature Reviews Electrical Engineering'. This review paper is the result of a collaborative effort by Dr. Kyung-seo Park (DGIST, co-first author), Dr. Hwa-young Jeong (EPFL, co-first author), Dr. Yoon-tae Jeong (IMEC), and Dr. Ji-hoon Seo (UCSD), all doctoral graduates from the two laboratories. Nature Reviews Electrical Engineering is a review specialized journal in the field of electrical, electronic, and artificial intelligence technology, newly launched by Nature Publishing Group last year. It is known to invite world-renowned scholars in the field through strict selection criteria. Professor Jung Kim's research team's paper, titled "Using bio-potential and bio-impedance for intuitive human-robot interaction," was published on July 18, 2025. (DOI: https://doi.org/10.1038/s44287-025-00191-5) This review paper explains how biosignals can be used to quickly and accurately detect movement intentions and introduces advancements in movement prediction technology based on neural signals and muscle activity. It also focuses on the crucial role of integrated circuits (ICs) in maximizing low-noise performance and energy efficiency in biosignal sensing, covering thelatest development trends in low-noise, low-power designs for accurately measuring bio-potential and impedance signals. The review emphasizes the importance of hybrid and multi-modal sensing approaches, presenting the possibility of building robust, intuitive, and scalable HRI systems. The research team stressed that collaboration between sensor and IC design fields is essential for the practical application of biosignal-based HRI systems and stated that interdisciplinary collaboration will play a significant role in the development of next-generation HRI technology. Dr. Hwa-young Jeong, a co-first author of the paper, presented the potential of bio-potential and impedance signals to make human-robot interaction more intuitive and efficient, predicting that it will make significant contributions to the development of HRI technologies such as rehabilitation robots and robotic prostheses using biosignals in the future. This research was supported by several research projects, including the Human Plus Project of the National Research Foundation of Korea.
2025.07.24
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KAIST School of Transdisciplinary Studies Is Driving Innovation in Korean Education
<(From Left) Professor Jaeseung Jeong, haed of the School of Transdiciplinary Studies, Dr, Albert Chau, Vice President of Hong Kong Baptist University> KAIST (President Kwang Hyung Lee) announced on the 24th of July that its School of Transdisciplinary Studies has been consistently showcasing the results of its experiments and practices for educational innovation both domestically and abroad. On June 27, Professor Jaeseung Jeong, head of the School of Transdisciplinary Studies, was invited to speak at the “Pacific Asia Summit on Transdisciplinary Education 2025 (PASTE 2025)” held at Hong Kong Baptist University. He presented the Korean model of transdisciplinary education under the title “The Philosophy and Achievements of the KAIST School of Transdisciplinary Studies.” In his talk, Professor Jeong pointed out the limitations of conventional education systems that rely on answer-centered evaluation, perfectionism, and competitiveness, claiming that they hinder creativity and integrative thinking. He then introduced the philosophy and operational practices of the School of Transdisciplinary Studies, which was established in 2019 to overcome these issues. Professor Jeong outlined five key principles that define the school's educational philosophy: ①a broad and integrative academic foundation, ②student-driven and customized education, ③creativity and execution, ④a sense of social responsibility and global citizenship, and ⑤learning driven by intrinsic motivation and curiosity. He explained that students are admitted without a declared major, allowed to design their own learning plans, and evaluated under a P/NR system* that focuses on growth rather than competition. *P/NR system: A non-competitive grading system led by KAIST’s School of Transdisciplinary Studies. Instead of traditional letter grades (A/B/C/Fail), students receive Pass (P) or No Record (NR), with the latter not appearing as a failure and not affecting GPA. Professor Jeong emphasized, “This experiment at KAIST represents a new educational paradigm that values questions over knowledge, culture over structure, and inquiry over competition. Students are bridging academic learning and real-world practice by addressing societal challenges through technology, which could lead to a fundamental shift in global higher education.” His presentation provided an opportunity to spotlight how KAIST’s experimental approach to nurturing transdisciplinary talent is pointing to new directions for the global education community beyond Korea. < Hyungjoon Jang, a student at the School of Transdisciplinary Studies> The achievements of KAIST’s transdisciplinary education model are also reflected in students’ academic accomplishments. Hyungjoon Jang, a student at the School of Transdisciplinary Studies, participated in a collaborative study led by his mentor, Professor Jaekyung Kim in the Department of Mathematical Sciences, along with researchers from Chungnam National University and the Institute for Basic Science (IBS). Their groundbreaking analytical method enables the accurate estimation of inhibition constants using only a single inhibitor concentration. The paper was published in the prestigious journal Nature Communications in June, with Jang listed as co–first author. Jang played a leading role throughout the research process by developing the experimental methodology, creating a software package to support the method, drafting the manuscript, and engaging in peer review. He also effectively communicated mathematical and statistical models to pharmaceutical experts by mastering presentation techniques and visual explanation strategies, thereby setting a strong example of interdisciplinary collaboration. He emphasized that “the School of Transdisciplinary Studies’ mentor system allowed regular research feedback and the systematic acquisition of essential knowledge and analytical skills through courses in biochemistry and computational neuroscience.” This example demonstrates how undergraduate students at the School of Transdisciplinary Studies can take leading roles in cutting-edge interdisciplinary research. The school’s educational philosophy is also reflected in students’ practical actions. Inseo Jeong, a current student and founder of the startup MPAge Inc., made a meaningful donation to help establish a creative makerspace in the school. <Inseo Jeong, founder of MPAG> Inseo Jeong explained that the decision was made to express gratitude for the knowledge gained and the mentorship received from professors, saying that at the School of Transdisciplinary Studies, she learned not only how to solve problems with technology but also how to view society, and that learning has helped her grow. She added, “The deep understanding of humanity and the world emphasized by Professor Jaeseung Jeong will be a great asset not only to entrepreneurs but to all students pursuing diverse paths,” expressing support for her fellow students. Inseo Jeong collaborated for over two years with Professor Hyunwook Ka of the School of Transdisciplinary Studies on software research for individuals with hearing impairments. After numerous algorithm designs and experimental iterations, their work, which considered the social scalability of technology, was presented at the world-renowned CSUN Assistive Technology Conference held at California State University, Northridge. The project has filed for a patent under KAIST’s name. ※ Presentation title: Evidence-Based Adaptive Transcription for Sign Language Users KAIST is now working to complete the makerspace on the third floor of the Administrative Annex (N2) in Room 314 with a size of approximately 33 m2 during the summer. The makerspace is expected to serve as a hands-on, integrative learning environment where various ideas can be realized and implemented, playing a key role in fostering students’ creative problem-solving and integrative thinking skills. KAIST President Kwang Hyung Lee stated, “The School of Transdisciplinary Studies is both an experimental ground and a practical field for overcoming the limitations of traditional education and nurturing global talents with creative problem-solving skills and integrative thinking, which are essential for the future.” He added, “KAIST will continue to lead efforts to cultivate question-asking, inquiry-driven, transdisciplinary talents and propose new paradigms for education and research.”
2025.07.24
View 286
KAIST Team Develops Optogenetic Platform for Spatiotemporal Control of Protein and mRNA Storage and Release
<Dr. Chaeyeon Lee, Professor Won Do Heo from Department of Biological Sciences> A KAIST research team led by Professor Won Do Heo (Department of Biological Sciences) has developed an optogenetic platform, RELISR (REversible LIght-induced Store and Release), that enables precise spatiotemporal control over the storage and release of proteins and mRNAs in living cells and animals. Traditional optogenetic condensate systems have been limited by their reliance on non-specific multivalent interactions, which can lead to unintended sequestration or release of endogenous molecules. RELISR overcomes these limitations by employing highly specific protein–protein (nanobody–antigen) and protein–RNA (MCP–MS2) interactions, enabling the selective and reversible compartmentalization of target proteins or mRNAs within engineered, membrane-less condensates. In the dark, RELISR stably sequesters target molecules within condensates, physically isolating them from the cellular environment. Upon blue light stimulation, the condensates rapidly dissolve, releasing the stored proteins or mRNAs, which immediately regain their cellular functions or translational competency. This allows for reversible and rapid modulation of molecular activities in response to optical cues. < Figure 1. Overview of the Artificial Condensate System (RELISR). The artificial condensate system, RELISR, includes "Protein-RELISR" for storing proteins and "mRNA-RELISR" for storing mRNA. These artificial condensates can be disassembled by blue light irradiation and reassembled in a dark state> The research team demonstrated that RELISR enables temporal and spatial regulation of protein activity and mRNA translation in various cell types, including cultured neurons and mouse liver tissue. Comparative studies showed that RELISR provides more robust and reversible control of translation than previous systems based on spatial translocation. While previous optogenetic systems such as LARIAT (Lee et al., Nature Methods, 2014) and mRNA-LARIAT (Kim et al., Nat. Cell Biol., 2019) enabled the selective sequestration of proteins or mRNAs into membrane-less condensates in response to light, they were primarily limited to the trapping phase. The RELISR platform introduced in this study establishes a new paradigm by enabling both the targeted storage of proteins and mRNAs and their rapid, light-triggered release. This approach allows researchers to not only confine molecular function on demand, but also to restore activity with precise temporal control. < Figure 2. Cell shape change using the artificial condensate system (RELISR). A target protein, Vav2, which contributes to cell shape, was stored within the artificial condensate and then released after light irradiation. This release activated the target protein Vav2, causing a change in cell shape. It was confirmed that the storage, release, and activation of various proteins were effectively achieved> Professor Heo stated, “RELISR is a versatile optogenetic tool that enables the precise control of protein and mRNA function at defined times and locations in living systems. We anticipate this platform will be broadly applicable for studies of cell signaling, neural circuits, and therapeutic development. Furthermore, the combination of RELISR with genome editing or tissue-targeted delivery could further expand its utility for molecular medicine.” < Figure 3. Expression of a target mRNA using the artificial condensate system (RELISR) in mice. The genetic material for the artificial condensate system, RELISR, was injected into a living mouse. Using this system, a target mRNA was stored within the mouse's liver. Upon light irradiation, the mRNA was released, which induced the translation of a luminescent protein> This research was conducted by first author Dr. Chaeyeon Lee, under the supervision of Professor Heo, with contributions from Dr. Daseuli Yu (co-corresponding author) and Professor YongKeun Park (co-corresponding author, Department of Physics), whose group performed quantitative imaging analyses of biophysical changes induced by RELISR in cells. The findings were published in Nature Communications (July 7, 2025; DOI: 10.1038/s41467-025-61322-y). This work was supported by the Samsung Future Technology Foundation and the National Research Foundation of Korea.
2025.07.23
View 228
KAIST Designs a New Atomic Catalyst for Air Pollution Reduction
<(From Left)Professor Jong Hun Kim from Inha University, Dr. Gyuho Han and Professor Jeong Young Park from KAIST> Platinum diselenide (PtSe2) is a two-dimensional multilayer material in which each layer is composed of platinum (Pt) and selenium (Se). It is known that its excellent crystallinity and precise control of interlayer interactions allow modulation of various physical and chemical properties. Due to these characteristics, it has been actively researched in multiple fields, including semiconductors, photodetectors, and electrochemical devices. Now, a research team has proposed a new design concept in which atomically dispersed platinum on the surface of platinum diselenide can function as a catalyst for gas reactions. Through this, they have proven its potential as a next-generation gas-phase catalyst technology for high-efficiency carbon dioxide conversion and carbon monoxide reduction. KAIST (President Kwang Hyung Lee) announced on July 22 that a joint research team led by Endowed Chair Professor Jeong Young Park from the Department of Chemistry, along with Professor Hyun You Kim's team from Chungnam National University and Professor Yeonwoong (Eric) Jung's team from the University of Central Florida (UCF), has achieved excellent carbon monoxide oxidation performance by utilizing platinum atoms exposed on the surface of platinum diselenide, a type of two-dimensional transition metal dichalcogenide (TMD). To maximize catalytic performance, the research team designed the catalyst by dispersing platinum atoms uniformly across the surface, departing from the conventional use of bulk platinum. This strategy allows more efficient catalytic reactions using a smaller amount of platinum. It also enhances electronic interactions between platinum and selenium by tuning the surface electronic structure. As a result, the platinum diselenide film with a thickness of a few nanometers showed superior carbon monoxide oxidation performance across the entire temperature range compared to a conventional platinum thin film under identical conditions. In particular, carbon monoxide and oxygen were evenly adsorbed on the surface in similar proportions, increasing the likelihood that they would encounter each other and react, which significantly enhanced the catalytic activity. This improvement is primarily attributed to the increased exposure of surface platinum atoms resulting from selenium vacancies (Se-vacancies), which provide adsorption sites for gas molecules. The research team confirmed in real-time that these platinum atoms served as active adsorption sites during the actual reaction process, using ambient-pressure X-ray photoelectron spectroscopy (AP-XPS) conducted at the Pohang Accelerator Laboratory. This high-precision analysis was enabled by advanced instrumentation capable of observing surfaces at the nanometer scale under ambient pressure conditions. At the same time, computer simulations based on density functional theory (DFT) demonstrated that platinum diselenide exhibits distinct electronic behavior compared to conventional platinum. *Density Functional Theory (DFT): A quantum mechanical method for calculating the total energy of a system based on electron density. Professor Jeong Young Park stated, “This research presents a new design strategy that utilizes platinum diselenide, a two-dimensional layered material distinct from conventional platinum catalysts, to enable catalytic functions optimized for gas-phase reactions.” He added, “The electronic interaction between platinum and selenium created favorable conditions for the balanced adsorption of carbon monoxide and oxygen. By designing the catalyst to exhibit higher reactivity across the entire temperature range than conventional platinum, we improved its practical applicability. This enabled a high-efficiency catalytic reaction mechanism through atomic-level design, a two-dimensional material platform, and precise adsorption control.” This research was co-authored by Dr. Gyuho Han from the Department of Chemistry at KAIST, Dr. Hyuk Choi from the Department of Materials Science and Engineering at Chungnam National University, and Professor Jong Hun Kim from Inha University. The study was published on July 3 in the world-renowned journal Nature Communications. Paper Title: Enhanced catalytic activity on atomically dispersed PtSe2 two-dimensional layers DOI: 10.1038/s41467-025-61320-0 This research was supported by the Mid-Career Researcher Program of the Ministry of Science and ICT, the Core Research Institute Program of the Ministry of Education, the National Strategic Technology Materials Development Project, the U.S. National Science Foundation (NSF) CAREER Program, research funding from Inha University, and the Postdoctoral Researcher Program (P3) at UCF. Accelerator-based analysis was conducted in cooperation with the Pohang Accelerator Laboratory and the Korea Basic Science Institute (KBSI).
2025.07.22
View 353
Professor Jung-woo' Choi ‘s Team Comes in First at the World's Top Acoustic AI Challenge
<Photo1. (From left) Ph.D candidate Yong-hoo Kwon, M.S candidate Do-hwan Kim, Professor Jung-woo Choi, Dr. Dong-heon Lee> 'Acoustic separation and classification technology' is a next-generation artificial intelligence (AI) core technology that enables the early detection of abnormal sounds in areas such as drones, fault detection of factory pipelines, and border surveillance systems, or allows for the separation and editing of spatial audio by sound source when producing AR/VR content. On the 11th of July, a research team led by Professor Jung-woo Choi of KAIST's Department of Electrical and Electronic Engineering won first place in the 'Spatial Semantic Segmentation of Sound Scenes' task of the 'DCASE2025 Challenge,' the world's most prestigious acoustic detection and analysis competition. This year’s challenge featured 86 teams competing across six tasks. In this competition, the KAIST research team achieved the best performance in their first-ever participation to Task 4. Professor Jung-woo Choi’s research team consisted of Dr. Dong-heon, Lee, Ph.D. candidate Young-hoo Kwon, and M.S. candidate Do-hwan Kim. Task 4 titled 'Spatial Semantic Segmentation of Sound Scenes' is a highly demanding task requiring the analysis of spatial information in multi-channel audio signals with overlapping sound sources. The goal was to separate individual sounds and classify them into 18 predefined categories. The research team plans to present their technology at the DCASE workshop in Barcelona this October. <Figure 1. Example of an acoustic scene with multiple mixed sounds> Early this year, Dr. Dong-heon Lee developed a state-of-the-art sound source separation AI that combines Transformer and Mamba architectures. During the competition, centered around researcher Young-hoo Kwon, they completed a ‘chain-of-inference architecture' AI model that performs sound source separation and classification again, using the waveforms and types of the initially separated sound sources as clues. This AI model is inspired by human’s auditory scene analysis mechanism that isolates individual sounds by focusing on incomplete clues such as sound type, rhythm, or direction, when listening to complex sounds. Through this, the team was the only participant to achieve double-digit performance (11 dB) in 'Class-Aware Signal-to-Distortion Ratio Improvement (CA-SDRi)*,' which is the measure for ranking how well the AI separated and classified sounds, proving their technical excellence. Class-Aware Signal-to-Distortion Ratio Improvement (CA-SDRi): Measures how much clearer (less distorted) the desired sound is separated and classified compared to the original audio, in dB (decibels). A higher number indicates more accurate and cleaner sound separation. Prof. Jung-woo Choi remarked, "The research team has showcased world-leading acoustic separation AI models for the past three years, and I am delighted that these results have been officially recognized." He added, "I am proud of every member of the research team for winning first place through focused research, despite the significant increase in difficulty and having only a few weeks for development." <Figure 2. Time-frequency patterns of sound sources separated from a mixed source> The IEEE DCASE Challenge 2025 was held online, with submissions accepted from April 1 to June 15 and results announced on June 30. Since its launch in 2013, the DCASE Challenge has served as a premier global platform of IEEE Signal Processing Society for showcasing cutting-edge AI models in acoustic signal processing. This research was supported by the Mid-Career Researcher Support Project and STEAM Research Project of the National Research Foundation of Korea, funded by the Ministry of Education, Science and Technology, as well as support from the Future Defense Research Center, funded by the Defense Acquisition Program Administration and the Agency for Defense Development.
2025.07.13
View 399
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