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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 66 -
KAIST Develops Novel Candidiasis Treatment Overcoming Side Effects and Resistance
<(From left) Ph. D Candidate Ju Yeon Chung, Prof.Hyun Jung Chung, Ph.D candidate Seungju Yang, Ph.D candidate Ayoung Park, Dr. Yoon-Kyoung Hong from Asan Medical Center, Prof. Yong Pil Chong, Dr. Eunhee Jeon>
Candida, a type of fungus, which can spread throughout the body via the bloodstream, leading to organ damage and sepsis. Recently, the incidence of candidiasis has surged due to the increase in immunosuppressive therapies, medical implants, and transplantation. Korean researchers have successfully developed a next-generation treatment that, unlike existing antifungals, selectively acts only on Candida, achieving both high therapeutic efficacy and low side effects simultaneously.
KAIST (President Kwang Hyung Lee) announced on the 8th that a research team led by Professor Hyun-Jung Chung of the Department of Biological Sciences, in collaboration with Professor Yong Pil Jeong's team at Asan Medical Center, developed a gene-based nanotherapy (FTNx) that simultaneously inhibits two key enzymes in the Candida cell wall.
Current antifungal drugs for Candida have low target selectivity, which can affect human cells. Furthermore, their therapeutic efficacy is gradually decreasing due to the emergence of new resistant strains. Especially for immunocompromised patients, the infection progresses rapidly and has a poor prognosis, making the development of new treatments to overcome the limitations of existing therapies urgent.
The developed treatment can be administered systemically, and by combining gene suppression technology with nanomaterial technology, it effectively overcomes the structural limitations of existing compound-based drugs and successfully achieves selective treatment against only Candida.
The research team created a gold nanoparticle-based complex loaded with short DNA fragments called antisense oligonucleotides (ASO), which simultaneously target two crucial enzymes—β-1,3-glucan synthase (FKS1) and chitin synthase (CHS3)—important for forming the cell wall of the Candida fungus.
By applying a surface coating technology that binds to a specific glycolipid structure (a structure combining sugar and fat) on the Candida cell wall, a targeted delivery device was implemented. This successfully achieved a precise targeting effect, ensuring the complex is not delivered to human cells at all but acts selectively only on Candida.
<Figure 1: Overview of antifungal therapy design and experimental approach>
This complex, after entering Candida cells, cleaves the mRNA produced by the FKS1 and CHS3 genes, thereby inhibiting translation and simultaneously blocking the synthesis of cell wall components β-1,3-glucan and chitin. As a result, the
Candida cell wall loses its structural stability and collapses, suppressing bacterial survival and proliferation.
In fact, experiments using a systemic candidiasis model in mice confirmed the therapeutic effect: a significant reduction in
Candida count in the organs, normalization of immune responses, and a notable increase in survival rates were observed in the treated group.
Professor Hyun-Jung Chung, who led the research, stated, "This study presents a method to overcome the issues of human toxicity and drug resistance spread with existing treatments, marking an important turning point by demonstrating the applicability of gene therapy for systemic infections". She added, "We plan to continue research on optimizing administration methods and verifying toxicity for future clinical application."
This research involved Ju Yeon Chung and Yoon-Kyoung Hong as co-first authors , and was published in the international journal 'Nature Communications' on July 1st.
Paper Title: Effective treatment of systemic candidiasis by synergistic targeting of cell wall synthesis
DOI: 10.1038/s41467-025-60684-7
This research was supported by the Ministry of Health and Welfare and the National Research Foundation of Korea.
2025.07.08 View 270 -
KAIST Presents a Breakthrough in Overcoming Drug Resistance in Cancer – Hope for Treating Intractable Diseases like Diabetes
<(From the left) Prof. Hyun Uk Kim, Ph.D candiate Hae Deok Jung, Ph.D candidate Jina Lim, Prof.Yoosik Kim from the Department of Chemical and Biomolecular Engineering>
One of the biggest obstacles in cancer treatment is drug resistance in cancer cells. Conventional efforts have focused on identifying new drug targets to eliminate these resistant cells, but such approaches can often lead to even stronger resistance. Now, researchers at KAIST have developed a computational framework to predict key metabolic genes that can re-sensitize resistant cancer cells to treatment. This technique holds promise not only for a variety of cancer therapies but also for treating metabolic diseases such as diabetes.
On the 7th of July, KAIST (President Kwang Hyung Lee) announced that a research team led by Professors Hyun Uk Kim and Yoosik Kim from the Department of Chemical and Biomolecular Engineering had developed a computational framework that predicts metabolic gene targets to re-sensitize drug-resistant breast cancer cells. This was achieved using a metabolic network model capable of simulating human metabolism.
Focusing on metabolic alterations—key characteristics in the formation of drug resistance—the researchers developed a metabolism-based approach to identify gene targets that could enhance drug responsiveness by regulating the metabolism of drug-resistant breast cancer cells.
< Computational framework that can identify metabolic gene targets to revert the metabolic state of the drug-resistant cells to that of the drug-sensitive parental cells>
The team first constructed cell-specific metabolic network models by integrating proteomic data obtained from two different types of drug-resistant MCF7 breast cancer cell lines: one resistant to doxorubicin and the other to paclitaxel. They then performed gene knockout simulations* on all of the metabolic genes and analyzed the results.
*Gene knockout simulation: A computational method to predict changes in a biological network by virtually removing specific genes.
As a result, they discovered that suppressing certain genes could make previously resistant cancer cells responsive to anticancer drugs again. Specifically, they identified GOT1 as a target in doxorubicin-resistant cells, GPI in paclitaxel-resistant cells, and SLC1A5 as a common target for both drugs.
The predictions were experimentally validated by suppressing proteins encoded by these genes, which led to the re-sensitization of the drug-resistant cancer cells.
Furthermore, consistent re-sensitization effects were also observed when the same proteins were inhibited in other types of breast cancer cells that had developed resistance to the same drugs.
Professor Yoosik Kim remarked, “Cellular metabolism plays a crucial role in various intractable diseases including infectious and degenerative conditions. This new technology, which predicts metabolic regulation switches, can serve as a foundational tool not only for treating drug-resistant breast cancer but also for a wide range of diseases that currently lack effective therapies.”
Professor Hyun Uk Kim, who led the study, emphasized, “The significance of this research lies in our ability to accurately predict key metabolic genes that can make resistant cancer cells responsive to treatment again—using only computer simulations and minimal experimental data. This framework can be widely applied to discover new therapeutic targets in various cancers and metabolic diseases.”
The study, in which Ph.D. candidates JinA Lim and Hae Deok Jung from KAIST participated as co-first authors, was published online on June 25 in Proceedings of the National Academy of Sciences (PNAS), a leading multidisciplinary journal that covers top-tier research in life sciences, physics, engineering, and social sciences.
※ Title: Genome-scale knockout simulation and clustering analysis of drug-resistant breast cancer cells reveal drug sensitization targets ※ DOI: https://doi.org/10.1073/pnas.2425384122 ※ Authors: JinA Lim (KAIST, co-first author), Hae Deok Jung (KAIST, co-first author), Han Suk Ryu (Seoul National University Hospital, corresponding author), Yoosik Kim (KAIST, corresponding author), Hyun Uk Kim (KAIST, corresponding author), and five others.
This research was supported by the Ministry of Science and ICT through the National Research Foundation of Korea, and the Electronics and Telecommunications Research Institute (ETRI).
2025.07.08 View 369 -
KAIST Presents Game-Changing Technology for Intractable Brain Disease Treatment Using Micro OLEDs
<(From left)Professor Kyung Cheol Choi, Hyunjoo J. Lee, Somin Lee from the School of Electrical Engineering>
Optogenetics is a technique that controls neural activity by stimulating neurons expressing light-sensitive proteins with specific wavelengths of light. It has opened new possibilities for identifying causes of brain disorders and developing treatments for intractable neurological diseases. Because this technology requires precise stimulation inside the human brain with minimal damage to soft brain tissue, it must be integrated into a neural probe—a medical device implanted in the brain. KAIST researchers have now proposed a new paradigm for neural probes by integrating micro OLEDs into thin, flexible, implantable medical devices.
KAIST (President Kwang Hyung Lee) announced on the 6th of July that Professor Kyung Cheol Choi and researcher Hyunjoo J. Lee from the School of Electrical Engineering have jointly succeeded in developing an optogenetic neural probe integrated with flexible micro OLEDs.
Optical fibers have been used for decades in optogenetic research to deliver light to deep brain regions from external light sources. Recently, research has focused on flexible optical fibers and ultra-miniaturized neural probes that integrate light sources for single-neuron stimulation.
The research team focused on micro OLEDs due to their high spatial resolution and flexibility, which allow for precise light delivery to small areas of neurons. This enables detailed brain circuit analysis while minimizing side effects and avoiding restrictions on animal movement. Moreover, micro OLEDs offer precise control of light wavelengths and support multi-site stimulation, making them suitable for studying complex brain functions.
However, the device's electrical properties degrade easily in the presence of moisture or water, which limited their use as implantable bioelectronics. Furthermore, optimizing the high-resolution integration process on thin, flexible probes remained a challenge.
To address this, the team enhanced the operational reliability of OLEDs in moist, oxygen-rich environments and minimized tissue damage during implantation. They patterned an ultrathin, flexible encapsulation layer* composed of aluminum oxide and parylene-C (Al₂O₃/parylene-C) at widths of 260–600 micrometers (μm) to maintain biocompatibility.
*Encapsulation layer: A barrier that completely blocks oxygen and water molecules from the external environment, ensuring the longevity and reliability of the device.
When integrating the high-resolution micro OLEDs, the researchers also used parylene-C, the same biocompatible material as the encapsulation layer, to maintain flexibility and safety. To eliminate electrical interference between adjacent OLED pixels and spatially separate them, they introduced a pixel define layer (PDL), enabling the independent operation of eight micro OLEDs.
Furthermore, they precisely controlled the residual stress and thickness in the multilayer film structure of the device, ensuring its flexibility even in biological environments. This optimization allowed for probe insertion without bending or external shuttles or needles, minimizing mechanical stress during implantation.
Advanced Functional Materials-Conceptual diagram of a flexible neural probe for integrated optogenetics (Micro-OLED)>
As a result, the team developed a flexible neural probe with integrated micro OLEDs capable of emitting more than one milliwatt per square millimeter (mW/mm²) at 470 nanometers (nm), the optimal wavelength for activating channelrhodopsin-2. This is a significantly high light output for optogenetics and biomedical stimulation applications.
The ultrathin flexible encapsulation layer exhibited a low water vapor transmission rate of 2.66×10⁻⁵ g/m²/day, allowing the device to maintain functionality for over 10 years. The parylene-C-based barrier also demonstrated excellent performance in biological environments, successfully enabling the independent operation of the integrated OLEDs without electrical interference or bending issues.
Dr. Somin Lee, the lead author from Professor Choi’s lab, stated, “We focused on fine-tuning the integration process of highly flexible, high-resolution micro OLEDs onto thin flexible probes, enhancing their biocompatibility and application potential. This is the first reported development of such flexible OLEDs in a probe format and presents a new paradigm for using flexible OLEDs as implantable medical devices for monitoring and therapy.”
This study, with Dr. Somin Lee as the first author, was published online on March 26 in Advanced Functional Materials (IF 18.5), a leading international journal in the field of nanotechnology, and was selected as the cover article for the upcoming July issue.
※ Title: Advanced Micro-OLED Integration on Thin and Flexible Polymer Neural Probes for Targeted Optogenetic Stimulation ※ DOI: https://doi.org/10.1002/adfm.202420758
The research was supported by the Ministry of Science and ICT and the National Research Foundation of Korea through the Electronic Medicine Technology Development Program (Project title: Development of Core Source Technologies and In Vivo Validation for Brain Cognition and Emotion-Enhancing Light-Stimulating Electronic Medicine).
2025.07.07 View 226 -
KAIST Enhances Immunotherapy for Difficult-to-Treat Brain Tumors with Gut Microbiota
< Photo 1.(From left) Prof. Heung Kyu Lee, Department of Biological Sciences,
and Dr. Hyeon Cheol Kim>
Advanced treatments, known as immunotherapies that activate T cells—our body's immune cells—to eliminate cancer cells, have shown limited efficacy as standalone therapies for glioblastoma, the most lethal form of brain tumor. This is due to their minimal response to glioblastoma and high resistance to treatment.
Now, a KAIST research team has now demonstrated a new therapeutic strategy that can enhance the efficacy of immunotherapy for brain tumors by utilizing gut microbes and their metabolites. This also opens up possibilities for developing microbiome-based immunotherapy supplements in the future.
KAIST (President Kwang Hyung Lee) announced on July 1 that a research team led by Professor Heung Kyu Lee of the Department of Biological Sciences discovered and demonstrated a method to significantly improve the efficiency of glioblastoma immunotherapy by focusing on changes in the gut microbial ecosystem.
The research team noted that as glioblastoma progresses, the concentration of ‘tryptophan’, an important amino acid in the gut, sharply decreases, leading to changes in the gut microbial ecosystem. They discovered that by supplementing tryptophan to restore microbial diversity, specific beneficial strains activate CD8 T cells (a type of immune cell) and induce their infiltration into tumor tissues. Through a mouse model of glioblastoma, the research team confirmed that tryptophan supplementation enhanced the response of cancer-attacking T cells (especially CD8 T cells), leading to their increased migration to tumor sites such as lymph nodes and the brain.
In this process, they also revealed that ‘Duncaniella dubosii’, a beneficial commensal bacterium present in the gut, plays a crucial role. This bacterium helped T cells effectively redistribute within the body, and survival rates significantly improved when used in combination with immunotherapy (anti-PD-1).
Furthermore, it was demonstrated that even when this commensal bacterium was administered alone to germ-free mice (mice without any commensal microbes), the survival rate for glioblastoma increased. This is because the bacterium utilizes tryptophan to regulate the gut environment, and the metabolites produced in this process strengthen the ability of CD8 T cells to attack cancer cells.
Professor Heung Kyu Lee explained, "This research is a meaningful achievement, showing that even in intractable brain tumors where immune checkpoint inhibitors had no effect, a combined strategy utilizing gut microbes can significantly enhance treatment response."
Dr. Hyeon Cheol Kim of KAIST (currently a postdoctoral researcher at the Institute for Biological Sciences) participated as the first author. The research findings were published online in Cell Reports, an international journal in the life sciences, on June 26.
This research was conducted as part of the Basic Research Program and Bio & Medical Technology Development Program supported by the Ministry of Science and ICT and the National Research Foundation of Korea.
※Paper Title: Gut microbiota dysbiosis induced by brain tumor modulates the efficacy of immunotherapy
※DOI: https://doi.org/10.1016/j.celrep.2025.115825
2025.07.02 View 836 -
2025 KAIST Global Entrepreneurship Summer School Concludes Successfully in Silicon Valley
< A group photo taken at the 2025 GESS Special Lecture.Vice President So Young Kim from the International Office, VC Jay Eum from GFT Ventures, Professor Byungchae Jin from the Impact MBA Program at the Business School, and Research Assistant Professor Sooa Lee from the Office of Global Initiative>
The “2025 KAIST Global Entrepreneurship Summer School (2025 KAIST GESS),” organized by the Office of Global Initiative of the KAIST International Office (Vice President So Young Kim), successfully concluded. Now in its fourth year, the program was designed to provide KAIST students with firsthand experience of the world’s leading startup ecosystem in Silicon Valley, USA, and to strengthen their practical capabilities to take on challenges on the global stage.
This year’s 2025 KAIST GESS welcomed approximately 40 participants, including 24 undergraduate and graduate students selected through document screening, interviews, team presentations, mentoring, and peer evaluations, as well as 16 Impact MBA students from the College of Business. The selected undergraduate and graduate participants underwent two months of pre-program training and received mentoring from experienced entrepreneurs to refine their business models and elevate their project ideas. Meanwhile, Impact MBA students joined the Silicon Valley program onsite, attending key lectures and networking sessions to broaden their understanding of the global startup ecosystem.
From June 22nd, participants spent seven days in Silicon Valley completing the global entrepreneurship curriculum. The program was operated in cooperation with major organizations including the KOTRA Silicon Valley IT Center, Korea-US AI Semiconductor Innovation Center (K-ASIC), and Plug and Play Tech Center. Local experts delivered lectures on topics such as “Startup Culture,” “Learning from Failures” and “Networks and Capital.”
Participants also had the opportunity to visit startups led by KAIST alumni and local entrepreneurs, gaining valuable insights from firsthand stories about global entrepreneurship. Companies visited included Medic Life Sciences (CEO Kyuho Han) and ImpriMed (CEO Sungwon Lim). Through these visits, participants received practical advice on market entry strategies and overcoming challenges in the global arena.
As part of their first onsite schedule, KAIST students attended an interactive fireside chat titled “Global Entrepreneurship and AI,” where they engaged in in-depth discussions on the future of AI-driven global startups. The session featured three distinguished speakers: Jay Kim, Head of US Business Development at Hyper Accel; Chandra Shekhar Dhir, AI/ML Director at JPMorgan Chase’s Machine Learning Center of Excellence; and Taesu Kim, co-founder of AI voice synthesis startup Neosapience and KAIST alumnus. Taesu Kim shared, “Facing serious health issues made me reflect on my life, and after recovering, I wanted to pursue something that could create a real impact on society, which led me to start my own company.” He also advised students to “take time at important turning points in life to deeply think about what you truly want to do and how you can contribute to society.
In line with the core value of ‘paying it forward’—a fundamental principle of global entrepreneurship learned in Silicon Valley—GESS participants engaged in a community service project titled “Let’s Play with AI+Tech,” organized in collaboration with the Sunnyvale community and Foothill College. Leveraging their strong foundation in AI, KAIST students designed and led a hands-on ‘Doodle AI’ educational program to make foundational AI concepts accessible and engaging for underrepresented local elementary school children and their parents, fostering meaningful community interaction.
On the final day of the 2025 KAIST GESS, a pitch competition was held with participation from Silicon Valley venture capitalists and accelerators. Participants presented their business models, developed over the two-month program, to a panel of judges. The winning team was eaureco, and Si Li Sara Aow (Civil and Environmental Engineering) shared, “GESS was a valuable opportunity to test and hone practical entrepreneurship skills beyond mere networking.” She added, “At first, I lacked confidence, but challenging myself to pitch in the final presentation gave me the courage to take one step closer to global entrepreneurship. Pitching in Silicon Valley, the heart of global startups, was an invaluable experience that will shape my path as a global entrepreneur.”
The program concluded with a special lecture by Jay Eum, a seasoned Silicon Valley venture capitalist and a judging panel member for GESS over the past three years. He shared key insights on startup success from an investor’s perspective, advising, “The journey of entrepreneurship is never easy, but the sooner you start, the better.” He further encouraged participants to “focus on solving problems in local markets, but do not fear challenging global markets,” inspiring them with courage and actionable advice.
So Young Kim, Director of the KAIST Office of Global Initiative, said, “We hope the 2025 KAIST GESS serves as a stepping stone for KAIST students to grow into influential entrepreneurs on the global stage,” adding, “This program is also expected to further enhance KAIST’s international reputation.”
Byungchae Jin, Faculty Chair of the KAIST Impact MBA, College of Business, highlighted the program's educational benefits, stating, “Engaging directly with local entrepreneurs and gaining practical experience in Silicon Valley's startup environment provide students with hands-on learning and significant inspiration.”
The 2025 KAIST GESS was jointly hosted by the KAIST Office of Global Initiative, Impact MBA, and Startup KAIST. Moving forward, KAIST plans to continue expanding its field-based global entrepreneurship education by linking with key global hubs like Silicon Valley, fostering next-generation global leaders who will lead innovation and challenge the status quo.
2025.07.01 View 848 -
KAIST Develops AI to Easily Find Promising Materials That Capture Only CO₂
< Photo 1. (From left) Professor Jihan Kim, Ph.D. candidate Yunsung Lim and Dr. Hyunsoo Park of the Department of Chemical and Biomolecular Engineering >
In order to help prevent the climate crisis, actively reducing already-emitted CO₂ is essential. Accordingly, direct air capture (DAC) — a technology that directly extracts only CO₂ from the air — is gaining attention. However, effectively capturing pure CO₂ is not easy due to water vapor (H₂O) present in the air. KAIST researchers have successfully used AI-driven machine learning techniques to identify the most promising CO₂-capturing materials among metal-organic frameworks (MOFs), a key class of materials studied for this technology.
KAIST (President Kwang Hyung Lee) announced on the 29th of June that a research team led by Professor Jihan Kim from the Department of Chemical and Biomolecular Engineering, in collaboration with a team at Imperial College London, has developed a machine-learning-based simulation method that can quickly and accurately screen MOFs best suited for atmospheric CO₂ capture.
< Figure 1. Concept diagram of Direct Air Capture (DAC) technology and carbon capture using Metal-Organic Frameworks (MOFs). MOFs are promising porous materials capable of capturing carbon dioxide from the atmosphere, drawing attention as a core material for DAC technology. >
To overcome the difficulty of discovering high-performance materials due to the complexity of structures and the limitations of predicting intermolecular interactions, the research team developed a machine learning force field (MLFF) capable of precisely predicting the interactions between CO₂, water (H₂O), and MOFs. This new method enables calculations of MOF adsorption properties with quantum-mechanics-level accuracy at vastly faster speeds than before.
Using this system, the team screened over 8,000 experimentally synthesized MOF structures, identifying more than 100 promising candidates for CO₂ capture. Notably, this included new candidates that had not been uncovered by traditional force-field-based simulations. The team also analyzed the relationships between MOF chemical structure and adsorption performance, proposing seven key chemical features that will help in designing new materials for DAC.
< Figure 2. Concept diagram of adsorption simulation using Machine Learning Force Field (MLFF). The developed MLFF is applicable to various MOF structures and allows for precise calculation of adsorption properties by predicting interaction energies during repetitive Widom insertion simulations. It is characterized by simultaneously achieving high accuracy and low computational cost compared to conventional classical force fields. >
This research is recognized as a significant advance in the DAC field, greatly enhancing materials design and simulation by precisely predicting MOF-CO₂ and MOF-H₂O interactions.
The results of this research, with Ph.D. candidate Yunsung Lim and Dr. Hyunsoo Park of KAIST as co-first authors, were published in the international academic journal Matter on June 12.
※Paper Title: Accelerating CO₂ direct air capture screening for metal–organic frameworks with a transferable machine learning force field
※DOI: 10.1016/j.matt.2025.102203
This research was supported by the Saudi Aramco-KAIST CO₂ Management Center and the Ministry of Science and ICT's Global C.L.E.A.N. Project.
2025.06.29 View 1008 -
Military Combatants Usher in an Era of Personalized Training with New Materials
< Photo 1. (From left) Professor Steve Park of Materials Science and Engineering, Kyusoon Pak, Ph.D. Candidate (Army Major) >
Traditional military training often relies on standardized methods, which has limited the provision of optimized training tailored to individual combatants' characteristics or specific combat situations. To address this, our research team developed an e-textile platform, securing core technology that can reflect the unique traits of individual combatants and various combat scenarios. This technology has proven robust enough for battlefield use and is economical enough for widespread distribution to a large number of troops.
On June 25th, Professor Steve Park's research team at KAIST's Department of Materials Science and Engineering announced the development of a flexible, wearable electronic textile (E-textile) platform using an innovative technology that 'draws' electronic circuits directly onto fabric.
The wearable e-textile platform developed by the research team combines 3D printing technology with new materials engineering design to directly print flexible and highly durable sensors and electrodes onto textile substrates. This enables the collection of precise movement and human body data from individual combatants, which can then be used to propose customized training models.
Existing e-textile fabrication methods were often complex or limited in their ability to provide personalized customization. To overcome these challenges, the research team adopted an additive manufacturing technology called 'Direct Ink Writing (DIW)' 3D printing.
< Figure 1. Schematic diagram of e-textile manufactured with Direct Ink Writing (DIW) printing technology on various textiles, including combat uniforms >
This technology involves directly dispensing and printing special ink, which functions as sensors and electrodes, onto textile substrates in desired patterns. This allows for flexible implementation of various designs without the complex process of mask fabrication. This is expected to be an effective technology that can be easily supplied to hundreds of thousands of military personnel.
The core of this technology lies in the development of high-performance functional inks based on advanced materials engineering design. The research team combined styrene-butadiene-styrene (SBS) polymer, which provides flexibility, with multi-walled carbon nanotubes (MWCNT) for electrical conductivity. They developed a tensile/bending sensor ink that can stretch up to 102% and maintain stable performance even after 10,000 repetitive tests. This means that accurate data can be consistently obtained even during the strenuous movements of combatants.
< Figure 2. Measurement of human movement and breathing patterns using e-textile >
Furthermore, new material technology was applied to implement 'interconnect electrodes' that electrically connect the upper and lower layers of the fabric. The team developed an electrode ink combining silver (Ag) flakes with rigid polystyrene (PS) polymer, precisely controlling the impregnation level (how much the ink penetrates the fabric) to effectively connect both sides or multiple layers of the fabric. This secures the technology for producing multi-layered wearable electronic systems integrating sensors and electrodes.
< Figure 3. Experimental results of recognizing unknown objects after machine learning six objects using a smart glove >
The research team proved the platform's performance through actual human movement monitoring experiments. They printed the developed e-textile on major joint areas of clothing (shoulders, elbows, knees) and measured movements and posture changes during various exercises such as running, jumping jacks, and push-ups in real-time.
Additionally, they demonstrated the potential for applications such as monitoring breathing patterns using a smart mask and recognizing objects through machine learning and perceiving complex tactile information by printing multiple sensors and electrodes on gloves. These results show that the developed e-textile platform is effective in precisely understanding the movement dynamics of combatants.
This research is an important example demonstrating how cutting-edge new material technology can contribute to the advancement of the defense sector. Major Kyusoon Pak of the Army, who participated in this research, considered required objectives such as military applicability and economic feasibility for practical distribution from the research design stage.
< Figure 4. Experimental results showing that a multi-layered e-textile glove connected with interconnect electrodes can measure tensile/bending signals and pressure signals at a single point >
Major Pak stated, "Our military is currently facing both a crisis and an opportunity due to the decrease in military personnel resources caused by the demographic cliff and the advancement of science and technology. Also, respect for life in the battlefield is emerging as a significant issue. This research aims to secure original technology that can provide customized training according to military branch/duty and type of combat, thereby enhancing the combat power and ensuring the survivability of our soldiers."
He added, "I hope this research will be evaluated as a case that achieved both scientific contribution and military applicability."
This research, where Kyusoon Pak, Ph.D. Candidate (Army Major) from KAIST's Department of Materials Science and Engineering, participated as the first author and Professor Steve Park supervised, was published on May 27, 2025, in `npj Flexible Electronics (top 1.8% in JCR field)', an international academic journal in the electrical, electronic, and materials engineering fields.
* Paper Title: Fabrication of Multifunctional Wearable Interconnect E-textile Platform Using Direct Ink Writing (DIW) 3D Printing
* DOI: https://doi.org/10.1038/s41528-025-00414-7
This research was supported by the Ministry of Trade, Industry and Energy and the National Research Foundation of Korea.
2025.06.25 View 1234 -
KAIST's Li-Fi - Achieves 100 Times Faster Speed and Enhanced Security of Wi-Fi
- KAIST-KRISS Develop 'On-Device Encryption Optical Transmitter' Based on Eco-Friendly Quantum Dots
- New Li-Fi Platform Technology Achieves High Performance with 17.4% Device Efficiency and 29,000 nit Brightness, Simultaneously Improving Transmission Speed and Security
- Presents New Methodology for High-Speed and Encrypted Communication Through Single-Device-Based Dual-Channel Optical Modulation
< Photo 1. (Front row from left) Seungmin Shin, First Author; Professor Himchan Cho; (Back row from left) Hyungdoh Lee, Seungwoo Lee, Wonbeom Lee; (Top left) Dr. Kyung-geun Lim >
Li-Fi (Light Fidelity) is a wireless communication technology that utilizes the visible light spectrum (400-800 THz), similar to LED light, offering speeds up to 100 times faster than existing Wi-Fi (up to 224 Gbps). While it has fewer limitations in available frequency allocation and less radio interference, it is relatively vulnerable to security breaches as anyone can access it. Korean researchers have now proposed a new Li-Fi platform that overcomes the limitations of conventional optical communication devices and can simultaneously enhance both transmission speed and security.
KAIST (President Kwang Hyung Lee) announced on the 24th that Professor Himchan Cho's research team from the Department of Materials Science and Engineering, in collaboration with Dr. Kyung-geun Lim of the Korea Research Institute of Standards and Science (KRISS, President Ho-Seong Lee) under the National Research Council of Science & Technology (NST, Chairman Young-Sik Kim), has developed 'on-device encryption optical communication device' technology for the utilization of 'Li-Fi,' which is attracting attention as a next-generation ultra-high-speed data communication.
Professor Cho's team created high-efficiency light-emitting triode devices using eco-friendly quantum dots (low-toxicity and sustainable materials). The device developed by the research team is a mechanism that generates light using an electric field. Specifically, the electric field is concentrated in 'tiny holes (pinholes) in the permeable electrode' and transmitted beyond the electrode. This device utilizes this principle to simultaneously process two input data streams.
Using this principle, the research team developed a technology called 'on-device encryption optical transmitter.' The core of this technology is that the device itself converts information into light and simultaneously encrypts it. This means that enhanced security data transmission is possible without the need for complex, separate equipment.
External Quantum Efficiency (EQE) is an indicator of how efficiently electricity is converted into light, with a general commercialization standard of about 20%. The newly developed device recorded an EQE of 17.4%, and its luminance was 29,000 nit, significantly exceeding the maximum brightness of a smartphone OLED screen, which is 2,000 nit, demonstrating a brightness more than 10 times higher.
< Figure 1. Schematic diagram of the device structure developed by the research team and encrypted communication >
Furthermore, to more accurately understand how this device converts information into light, the research team used a method called 'transient electroluminescence analysis.' They analyzed the light-emitting characteristics generated by the device when voltage was instantaneously applied for very short durations (hundreds of nanoseconds = billionths of a second). Through this analysis, they investigated the movement of charges within the device at hundreds of nanoseconds, elucidating the operating mechanism of dual-channel optical modulation implemented within a single device.
Professor Himchan Cho of KAIST stated, "This research overcomes the limitations of existing optical communication devices and proposes a new communication platform that can both increase transmission speed and enhance security."
< Photo 2. Professor Himchan Cho, Department of Materials Science and Engineering >
He added, "This technology, which strengthens security without additional equipment and simultaneously enables encryption and transmission, can be widely applied in various fields where security is crucial in the future."
This research, with Seungmin Shin, a Ph.D. candidate at KAIST's Department of Materials Science and Engineering, participating as the first author, and Professor Himchan Cho and Dr. Kyung-geun Lim of KRISS as co-corresponding authors, was published in the international journal 'Advanced Materials' on May 30th and was selected as an inside front cover paper.※ Paper Title: High-Efficiency Quantum Dot Permeable electrode Light-Emitting Triodes for Visible-Light Communications and On-Device Data Encryption※ DOI: https://doi.org/10.1002/adma.202503189
This research was supported by the National Research Foundation of Korea, the National Research Council of Science & Technology (NST), and the Korea Institute for Advancement of Technology.
2025.06.24 View 1954 -
KAIST Develops Customized Tactile Sensor That Can Detect Light Breath, Pressure and Sound
< Photo 1. (From left) Professor Inkyu Park of KAIST Department of Mechanical Engineering (ME), Dr. Jungrak Choi of ETRI, Ph.D. Candidate Donho Lee and M.S. Graduate Chankyu Han of KAIST ME >
When a robot grabs an object or a medical device detects a pulse, the tactile sensor is the technology that senses pressure like a fingertip. Existing sensors had disadvantages, such as slow responses or declining accuracy after repeated use, but Korean researchers have succeeded in developing a sensor that can quickly and accurately detect even light breath, pressure, and sound. This sensor can be used across a broad range — from everyday movements to medical diagnostics.
KAIST (represented by President Kwang Hyung Lee) announced on the 23rd of June that Professor Inkyu Park’s team from the Department of Mechanical Engineering, through a collaborative research project with the Electronics and Telecommunications Research Institute (ETRI, President Seung Chan Bang ) under the National Research Council of Science & Technology (NST, Chairman Young Sik Kim), has developed an innovative technology that overcomes the structural limitations of existing tactile sensors.
The core of this joint research is the implementation of a customized tactile sensor that simultaneously achieves flexibility, precision, and repeatable durability by applying Thermoformed 3D Electronics (T3DE).
< Figure 1. Comparative evaluation of soft elastomer–based 3D structure versus thermoforming-based 3D structure in terms of mechanical properties. >
In particular, soft elastomer-based sensors (rubber, silicone, etc. — materials that stretch and return to their original shape) have structural problems such as slow response times, high hysteresis*, and creep**, but this new platform operates precisely in diverse environments and overcomes these limitations.
*Hysteresis: A phenomenon where the previously applied force or change is retained like a “memory,” so that the same stimulus does not always produce the same result.
**Creep: The phenomenon where a material slowly deforms when a force is continuously applied.
T3DE sensors are manufactured by precisely forming electrodes on a 2D film, then thermoforming them into a 3D structure under heat and pressure. Specifically, the top electrodes and supporting pillar structures of the sensor are designed to allow the fine-tuning of the mechanical properties for different purposes. By adjusting microstructural parameters — such as the thickness, length, and number of support pillars — the sensor’s Young’s modulus* can be tuned across a broad range of 10 Pa to 1 MPa. This matches the stiffness of biological tissues like skin, muscle, and tendons, making them highly suitable as bio-interface sensors.
*Young’s modulus: An index representing a material's stiffness; this research can control this index to match various biological tissues.
The newly developed T3DE sensor uses air as a dielectric material to reduce power consumption and demonstrates outstanding performance in sensitivity, response time, thermal stability, and repeatable accuracy.
Experimental results showed that the sensor achieved △sensitivity of 5,884 kPa⁻¹, △response time of 0.1 ms (less than one-thousandth of a second), △hysteresis of less than 0.5%, and maintained a repeatable precision of 99.9% or higher even after 5,000 repeated measurements.
< Figure 2. Graphic Overview of thermoformed 3D electronics (T3DE) >
The research team also constructed a high-resolution 40×70 array, comprising a total of 2,800 densely packed sensors, to visualize the pressure distribution on the sole of the foot in real time during exercise and confirmed the possibility of using the sensor for wrist pulse measurement to assess vascular health. Furthermore, successful results were also achieved in sound-detection experiments at a level comparable to commercial acoustic sensors. In short, the sensor can precisely and quickly measure foot pressure, pulse, and sound, allowing it to be applied in areas such as sports, health, and sound sensing.
The T3DE technology was also applied to an augmented-reality(AR)-based surgical training system. By adjusting the stiffness of each sensor element to match that of biological tissues, the system provided real-time visual and tactile feedback according to the pressure applied during surgical incisions. It also offered real-time warnings if an incision was too deep or approached a risky area, making it a promising technology for enhancing immersion and accuracy in medical training.
KAIST Professor Inkyu Park stated, “Because this sensor can be precisely tuned from the design stage and operates reliably across diverse environments, it can be used not only in everyday life, but also in a variety of fields such as healthcare, rehabilitation, and virtual reality.”
The research was co-led as first authors by Dr. Jungrak Choi of ETRI, KAIST master’s student Chankyu Han, and Ph.D. candidate Donho Lee, under the overall guidance of Professor Inkyu Park. The research results were published in the May 2025 issue of ‘Science Advances’ and introduced to the global research community through the journal’s official SNS channels (Facebook, Twitter).
※ Thesis Title: Thermoforming 2D films into 3D electronics for high-performance, customizable tactile sensing
※ DOI: 10.1126/sciadv.adv0057
< Figure 3. The introduction of the study on the official SNS posting by Science Advances >
This research was supported by the Ministry of Trade, Industry and Energy, the National Research Foundation of Korea, and the Korea Institute for Advancement of Technology.
2025.06.23 View 1575 -
KAIST Researchers Unveil an AI that Generates "Unexpectedly Original" Designs
< Photo 1. Professor Jaesik Choi, KAIST Kim Jaechul Graduate School of AI >
Recently, text-based image generation models can automatically create high-resolution, high-quality images solely from natural language descriptions. However, when a typical example like the Stable Diffusion model is given the text "creative," its ability to generate truly creative images remains limited. KAIST researchers have developed a technology that can enhance the creativity of text-based image generation models such as Stable Diffusion without additional training, allowing AI to draw creative chair designs that are far from ordinary.
Professor Jaesik Choi's research team at KAIST Kim Jaechul Graduate School of AI, in collaboration with NAVER AI Lab, developed this technology to enhance the creative generation of AI generative models without the need for additional training.
< Photo 2. Gayoung Lee, Researcher at NAVER AI Lab; Dahee Kwon, Ph.D. Candidate at KAIST Kim Jaechul Graduate School of AI; Jiyeon Han, Ph.D. Candidate at KAIST Kim Jaechul Graduate School of AI; Junho Kim, Researcher at NAVER AI Lab >
Professor Choi's research team developed a technology to enhance creative generation by amplifying the internal feature maps of text-based image generation models. They also discovered that shallow blocks within the model play a crucial role in creative generation. They confirmed that amplifying values in the high-frequency region after converting feature maps to the frequency domain can lead to noise or fragmented color patterns. Accordingly, the research team demonstrated that amplifying the low-frequency region of shallow blocks can effectively enhance creative generation.
Considering originality and usefulness as two key elements defining creativity, the research team proposed an algorithm that automatically selects the optimal amplification value for each block within the generative model.
Through the developed algorithm, appropriate amplification of the internal feature maps of a pre-trained Stable Diffusion model was able to enhance creative generation without additional classification data or training.
< Figure 1. Overview of the methodology researched by the development team. After converting the internal feature map of a pre-trained generative model into the frequency domain through Fast Fourier Transform, the low-frequency region of the feature map is amplified, then re-transformed into the feature space via Inverse Fast Fourier Transform to generate an image. >
The research team quantitatively proved, using various metrics, that their developed algorithm can generate images that are more novel than those from existing models, without significantly compromising utility.
In particular, they confirmed an increase in image diversity by mitigating the mode collapse problem that occurs in the SDXL-Turbo model, which was developed to significantly improve the image generation speed of the Stable Diffusion XL (SDXL) model. Furthermore, user studies showed that human evaluation also confirmed a significant improvement in novelty relative to utility compared to existing methods.
Jiyeon Han and Dahee Kwon, Ph.D. candidates at KAIST and co-first authors of the paper, stated, "This is the first methodology to enhance the creative generation of generative models without new training or fine-tuning. We have shown that the latent creativity within trained AI generative models can be enhanced through feature map manipulation."
They added, "This research makes it easy to generate creative images using only text from existing trained models. It is expected to provide new inspiration in various fields, such as creative product design, and contribute to the practical and useful application of AI models in the creative ecosystem."
< Figure 2. Application examples of the methodology researched by the development team. Various Stable Diffusion models generate novel images compared to existing generations while maintaining the meaning of the generated object. >
This research, co-authored by Jiyeon Han and Dahee Kwon, Ph.D. candidates at KAIST Kim Jaechul Graduate School of AI, was presented on June 16 at the International Conference on Computer Vision and Pattern Recognition (CVPR), an international academic conference.* Paper Title: Enhancing Creative Generation on Stable Diffusion-based Models* DOI: https://doi.org/10.48550/arXiv.2503.23538
This research was supported by the KAIST-NAVER Ultra-creative AI Research Center, the Innovation Growth Engine Project Explainable AI, the AI Research Hub Project, and research on flexible evolving AI technology development in line with increasingly strengthened ethical policies, all funded by the Ministry of Science and ICT through the Institute for Information & Communications Technology Promotion. It also received support from the KAIST AI Graduate School Program and was carried out at the KAIST Future Defense AI Specialized Research Center with support from the Defense Acquisition Program Administration and the Agency for Defense Development.
2025.06.20 View 1483 -
KAIST Develops Glare-Free, Heat-Blocking 'Smart Window'... Applicable to Buildings and Vehicles
• Professor Hong Chul Moon of the Department of Chemical and Biomolecular Engineering develops RECM, a next-generation smart window technology, expecting cooling energy savings and effective indoor thermal management.
• When using the developed RECM, a significantly superior temperature reduction effect is observed compared to conventional windows.
• With a 'pedestrian-friendly smart window' design that eliminates glare by suppressing external reflections, it is expected to be adapted in architectural structures, transportation, and more.
< (From left) First author Hoy Jung Jo, Professor Hong Chul Moon >
In the building sector, which accounts for approximately 40% of global energy consumption, heat ingress through windows has been identified as a primary cause of wasted heating and cooling energy. Our research team has successfully developed a 'pedestrian-friendly smart window' technology capable of not only reducing heating and cooling energy in urban buildings but also resolving the persistent issue of 'light pollution' in urban living.
On the 17th of June, Professor Hong Chul Moon's research team at KAIST's Department of Chemical and Biomolecular Engineering announced the development of a 'smart window technology' that allows users to control the light and heat entering through windows according to their intent, and effectively neutralize glare from external sources.
Recently, 'active smart window' technology, which enables free adjustment of light and heat based on user operation, has garnered significant attention. Unlike conventional windows that passively react to changes in temperature or light, this is a next-generation window system that can be controlled in real-time via electrical signals.
The next-generation smart window technology developed by the research team, RECM (Reversible Electrodeposition and Electrochromic Mirror), is a smart window system based on a single-structured *electrochromic device that can actively control the transmittance of visible light and near-infrared (heat).
*Electrochromic device: A device whose optical properties change in response to an electrical signal.
In particular, by effectively suppressing the glare phenomenon caused by external reflected light—a problem previously identified in traditional metal *deposition smart windows—through the combined application of electrochromic materials, a 'pedestrian-friendly smart window' suitable for building facades has been realized.
*Deposition: A process involving the electrochemical reaction to coat metal ions, such as Ag+, onto an electrode surface in solid form.
The RECM system developed in this study operates in three modes depending on voltage control.
Mode I (Transparent Mode) is advantageous for allowing sunlight to enter the indoor space during winter, as it transmits both light and heat like ordinary glass.
In Mode II (Colored Mode), *Prussian Blue (PB) and **DHV+• chemical species are formed through a redox (oxidation-reduction) reaction, causing the window to turn a deep blue color. In this state, light is absorbed, and only a portion of the heat is transmitted, allowing for privacy while enabling appropriate indoor temperature control.
*Prussian Blue: An electrochromic material that transitions between colorless and blue upon electrical stimulation.
**DHV+•: A radical state colored molecule generated upon electrical stimulation.
Mode III (Colored and Deposition Mode) involves the reduction and deposition of silver (Ag+) ions on the electrode surface, reflecting both light and heat. Concurrently, the colored material absorbs the reflected light, effectively blocking glare for external pedestrians.
The research team validated the practical indoor temperature reduction effect of the RECM technology through experiments utilizing a miniature model house. When a conventional glass window was installed, the indoor temperature rose to 58.7°C within 45 minutes. Conversely, when RECM was operated in Mode III, the temperature reached 31.5°C, demonstrating a temperature reduction effect of approximately 27.2°C.
Furthermore, since each state transition is achievable solely by electrical signals, it is regarded as an active smart technology capable of instantaneous response according to season, time, and intended use.
< Figure 1. Operation mechanism of the RECM smart window. The RECM system can switch among three states—transparent, colored, and colored & deposition—via electrical stimulation. At -1.6 V, DHV•+ and Prussian Blue (PB) are formed, blocking visible light to provide privacy protection and heat blocking. At -2.0 V, silver (Ag) is deposited on the electrode surface, reflecting light and heat, while DHV•+ and Prussian Blue absorb reflected light, effectively suppressing external glare. Through this mechanism, it functions as an active smart window that simultaneously controls light, heat, and glare. >
Professor Hong Chul Moon of KAIST, the corresponding author of this study, stated, "This research goes beyond existing smart window technologies limited to visible light control, presenting a truly smart window platform that comprehensively considers not only active indoor thermal control but also the visual safety of pedestrians." He added, "Various applications are anticipated, from urban buildings to vehicles and trains."
< Figure 2. Analysis of glare suppression effect of conventional reflective smart windows and RECM. This figure presents the results comparing the glare phenomenon occurring during silver (Ag) deposition between conventional reflective smart windows and RECM Mode III. Conventional reflective devices resulted in strong reflected light on the desk surface due to their high reflectivity. In contrast, RECM Mode III, where the colored material absorbed reflected light, showed a 33% reduction in reflected light intensity, and no reflected light was observed from outside. This highlights the RECM system's distinctiveness and practicality as a 'pedestrian-friendly smart window' optimized for dense urban environments, extending beyond just heat blocking. >
The findings of this research were published on June 13, 2025, in Volume 10, Issue 6 of 'ACS Energy Letters'. The listed authors for this publication are Hoy Jung Jo, Yeon Jae Jang, Hyeon-Don Kim, Kwang-Seop Kim, and Hong Chul Moon.
※ Paper Title: Glare-Free, Energy-Efficient Smart Windows: A Pedestrian-Friendly System with Dynamically Tunable Light and Heat Regulation
※ DOI: 10.1021/acsenergylett.5c00637
< Figure 3. Temperature reduction performance verification in a miniature model house. The actual heat blocking effect was evaluated by applying RECM devices to a model building. Under identical conditions, the indoor temperature with ordinary glass rose to 58.7°C, whereas with RECM in Mode III, it reached 31.5°C, demonstrating a maximum temperature reduction effect of 27.2°C. The indoor temperature difference was also visually confirmed through thermal images, which proves the potential for indoor temperature control in urban buildings. >
This research was supported by the Nano & Material Technology Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT and the internal research program of the Korea Institute of Machinery and Materials.
2025.06.20 View 3562