“AI,” the New Language of Materials Science and Engineering Spoken at KAIST
<(From Left) M.S candidate Chaeyul Kang, Professor Seumgbum Hong, Ph. D candidate Benediktus Madika, Ph.D candidate Batzorig Buyantogtokh, Ph.D candiate Aditi Saha, >
Collaborating authors include Professor Joshua Agar (Drexel University), Professors Chris Wolverton and Peter Voorhees (Northwestern University), Professor Peter Littlewood (University of St Andrews), and Professor Sergei Kalinin (University of Tennessee).
Paper Title: Artificial Intelligence for Materials Discovery, Development, and Optimization
The era has arrived in which artificial intelligence (AI) autonomously imagines and predicts the structures and properties of new materials. Today, AI functions as a researcher’s “second brain,” actively participating in every stage of research, from idea generation to experimental validation.
KAIST (President Kwang Hyung Lee) announced on October 26 that a comprehensive review paper analyzing the impact of AI, Machine Learning (ML), and Deep Learning (DL) technologies across materials science and engineering has been published in ACS Nano (Impact Factor = 18.7). The paper was co-authored by Professor Seungbum Hong and his team from the Department of Materials Science and Engineering at KAIST, in collaboration with researchers from Drexel University, Northwestern University, the University of St Andrews, and the University of Tennessee in the United States.
The research team proposed a full-cycle utilization strategy for materials innovation through an AI-based catalyst search platform, which embodies the concept of a Self-Driving Lab—a system in which robots autonomously perform materials synthesis and optimization experiments.
Professor Hong’s team categorized materials research into three major stages—Discovery, Development, and Optimization—and detailed the distinctive role of AI in each phase:
In the Discovery Stage, AI designs new structures, predicts properties, and rapidly identifies the most promising materials among vast candidate pools.
In the Development Stage, AI analyzes experimental data and autonomously adjusts experimental processes through Self-Driving Lab systems, significantly shortening research timelines.
In the Optimization Stage, AI employs Reinforcement Learning, which identifies optimal conditions through Bayesian Optimization, which efficiently finds superior results with minimal experimentation, to fine-tune designs and process conditions for maximum performance.
In essence, AI serves as a “smart assistant” that narrows down the most promising materials, reduces experimental trial and error, and autonomously optimizes experimental conditions to achieve the best-performing outcomes.
The paper further highlights how cutting-edge technologies such as Generative AI, Graph Neural Networks (GNNs), and Transformer models are transforming AI from a computational tool into a “thinking researcher.” Nonetheless, the team cautions that AI’s predictions are not error-proof and that key challenges persist, such as imbalanced data quality, limited interpretability of AI predictions, and integration of heterogeneous datasets.
To address these limitations, the authors emphasize the importance of developing AI systems capable of autonomously understanding physical principles and ensuring transparent, verifiable decision-making processes for researchers.
The review also explores the concept of the Self-Driving Lab, where AI autonomously designs experimental plans, analyzes results, and determines the next experimental steps—without manual operation by researchers. The AI-Based Catalyst Search Platform exemplifies this concept, enabling robots to automatically design, execute, and optimize catalyst synthesis experiments.
In particular, the study presents cases in which AI-driven experimentation has dramatically accelerated catalyst development, suggesting that similar approaches could revolutionize research in battery and energy materials.
<AI Driving Innovation Across the Entire Cycle of New Material Discovery, Development, and Optimization>
“This review demonstrates that artificial intelligence is emerging as the new language of materials science and engineering, transcending its role as a mere tool,” said Professor Seungbum Hong. “The roadmap presented by the KAIST team will serve as a valuable guide for researchers in Korea’s national core industries including batteries, semiconductors, and energy materials.”
Benediktus Madika (Ph.D. candidate), Aditi Saha (Ph.D. candidate), Chaeyul Kang (M.S. candidate), and Batzorig Buyantogtokh (Ph.D. candidate) from KAIST’s Department of Materials Science and Engineering contributed as co-first authors.
Collaborating authors include Professor Joshua Agar (Drexel University), Professors Chris Wolverton and Peter Voorhees (Northwestern University), Professor Peter Littlewood (University of St Andrews), and Professor Sergei Kalinin (University of Tennessee).
Paper Title: Artificial Intelligence for Materials Discovery, Development, and Optimization
DOI: 10.1021/acsnano.5c04200
This work was supported by the National Research Foundation of Korea (NRF) with funding from the Ministry of Science and ICT (RS-2023-00247245).
"KAIST Opens Up! Cutting-Edge Research Sites Revealed... 'OPEN KAIST 2025' to be Held
< 2025 OPEN KAIST Poster >
KAIST announced on the 23rd of October that it will hold the 'OPEN KAIST 2025' event, which publicly opens research labs, experiment rooms, and research centers on campus, for two days starting from October 30th at the main campus in Daejeon.
OPEN KAIST, which began in 2001 and marks its 13th event this year, is a representative research exhibition event operated biennially by the KAIST College of Engineering (Dean Jae Woo Lee), aiming for programs where citizens can directly experience the research environment and encounter science more closely.
This year, 16 departments and the KAIST Satellite Technology Research Center are participating, operating a total of 39 programs across five areas: △Experience/Demonstration △Lab Tour △Lecture △Department Introduction △Achievement Exhibition. In particular, the opportunities to directly observe and learn about core future fields such as AI, drones, brain science, nuclear energy, and semiconductors have been greatly enhanced.
Professor Jun Han's lab in the School of Computing will introduce technology where AI understands 3D space and constructs virtual environments. Participants will confirm the process of objects in a video being rearranged through a demonstration and learn about the role of AI in future society and the direction of development for spatial perception technology.
Professor Hyochoong Bang's lab in the Department of Aerospace Engineering will unveil next-generation drone technologies, including multicopters, unmanned helicopters, and Vertical Take-Off and Landing (VTOL) aircraft. Participants will understand their characteristics and usage environments, observe the already flight-tested technologies up close, and get a panoramic view of the changes the drone industry will bring.
Professor Minee Choi's lab in the Department of Brain and Cognitive Sciences offers an opportunity to experience the relationship between the brain and behavior. Participants will use an online application to create their own mini-brain, virtually examine the effects of exercise or vitamin intake on the brain, and directly experience research equipment and the experimental environment.
The Department of Mathematical Sciences has prepared two special lectures for youth. The lecture ‘Secrets Hidden in the Growth Data Patterns of Mammals’ will explore universal mathematical rules within the growth data of various mammals, from the American shrew mole weighing barely 10g to the blue whale exceeding 200 tons. The subsequent lecture, ‘Can This Knot Really Be Undone? — A Mathematical Way to Understand Space’, will explain the mathematical thought process for understanding space, using everyday knots like shoelaces as examples, tailored to the youth's level.
The Department of Nuclear and Quantum Engineering program includes radiation detection practice and a look at the potential utilization of next-generation nuclear technologies such as SMRs and microreactors. The Department of Industrial Design will introduce how design research connects to solving real-life problems through lab tours and exhibitions.
The Semiconductor Research Facility Tour allows participants to directly enter a cleanroom to observe the process equipment and manufacturing stages, experiencing the completion process of ultrafine semiconductors.
In addition, a variety of other programs are prepared, including a lecture by Professor Hyungjun Kim of the Moon Soul Graduate School of Future Strategy titled ‘Meta-Earth: Climate Crisis and Earth's Changes through Data’, the Department of Civil and Environmental Engineering’s ‘Centrifuge Modeling Test: Earthquake Research using Centrifugal Force’, and a game development special lecture and exhibition by the School of Computing's game production club 'Haze'.
< OPEN KAIST Event Scene >
Jae Woo Lee, Dean of the College of Engineering, stated, "We prepared this event to open up KAIST's education and research sites and provide visitors with an opportunity to directly experience and communicate about challenging and creative science and technology innovation."
KAIST President Kwang Hyung Lee said, "OPEN KAIST is a meaningful occasion to share the research environment with the public," and "I hope this event serves as an opportunity for youth and citizens to feel the value of science and foster dreams of future challenges."
For individual visitors, 'OPEN KAIST 2025' can be freely viewed according to the on-site situation by referring to the booklet distributed at the information desk on the day of the event, without prior application. Detailed schedules and programs can be checked on the website (https://openkaist.ac.kr).**
Ultra High Speed Optical Measurement Technology Developed
< (From left) Tae Jin Ha, CEO of VIRNECT, Kwang Hyung Lee, President of KAIST >
An open platform for industry-academia-research collaboration, which has accumulated K-Metaverse technology capabilities that break down the boundaries between reality and virtuality and share experiences beyond the limits of time and space, is expected to be built on our university campus.
Our university announced on the 13th that it’s signing an agreement for the establishment and operation of a 'Virtual Convergence Research Center' with the Graduate School of Metaverse and VIRNECT Co., Ltd. (CEO Tae Jin Ha), a domestic augmented/virtual reality (XR) specialized company and a startup founded by a KAIST alumnus.
The Virtual Convergence Research Center, which will be newly constructed on our university campus, plans to prepare for the future participation of related government-funded research institutes, and is expected to function as a national strategic hub that creates future growth engines for the Republic of Korea, going beyond simple industry-academia cooperation. VIRNECT Co., Ltd. plans to create the research center as an open research collaboration platform in which domestic and international industry, academia, and research institutes jointly participate with KAIST.
This research center is expected to experiment with the convergence of reality and virtuality and establish itself as a global hub for the 'K-Metaverse Innovation Ecosystem' where technology development, talent cultivation, and industrial diffusion are in a virtuous cycle.
VIRNECT Co., Ltd. was founded by KAIST alumnus Tae Jin Ha, listed on KOSDAQ in 2023, and won the CES Innovation Award for developing the industrial AI smart goggles 'VisionX'. It has grown into a representative domestic spatial computing company based on various industrial innovation technologies such as AI/XR solutions and digital twin. Synergistic co-prosperity with KAIST is anticipated through this collaboration.
Spatial computing and XR technology are areas where global big techs like Apple, Meta, Google, Microsoft, and Samsung are engaged in fierce competition for dominance, paying attention to them as the next-generation AI platforms. With major countries such as the US and China investing enormous capital and capabilities, the launch of the KAIST Virtual Convergence Research Center is evaluated as a strategic response for South Korea not to fall behind in the competition of the post-metaverse era.
The research center plans to lead both industrial productivity and social innovation as an R&BD (Research & Business Development) hub that integrates core technologies such as digital twin, metaverse, spatial/physical intelligence, and wearable XR. Furthermore, it will quickly verify the applicability to industrial sites and support the creation of new industries through a full-cycle system covering education, research, demonstration, commercialization, and diffusion.
Moreover, the research center will create national synergy by being closely linked with government policies. Strengthening the link between education and research, fostering a sustainable metaverse ecosystem, and expanding global leadership through an open industry-academia-research platform align with the government's strategy for advancing the virtual convergence industry.
< Executives from both organizations attending the signing ceremony >
VIRNECT CEO Tae Jin Ha said, "The long-term cooperation with KAIST is a stepping stone for us to leap forward as a game-changer in the global XR industry," adding, "We will strengthen virtual convergence technology competitiveness through research and education infrastructure and accelerate commercialization through demonstration."
Professor Woontack Woo, Dean of the Graduate School of Metaverse, emphasized, "The Virtual Convergence Research Center will serve as an open platform where industry, academia, and research institutes jointly experiment with K-Metaverse innovation, and a 'Meta Power Plant' that cultivates future core personnel and disseminates research results to the industry."
KAIST President Kwang Hyung Lee said, "This agreement is a strategic investment to secure global leadership by breaking down the boundaries between research and industry, going beyond simply creating a new research center," and "KAIST will spare no support for the research center."
With the future designation of the KAIST Virtual Convergence Research Center as a government-specialized graduate school/research center for the virtual convergence industry and increased industry cooperation, it will establish itself as a national innovation platform that concentrates South Korea's metaverse capabilities. This is expected to lead to the creation of new value for the future society and the strengthening of national competitiveness, going beyond simple technology development.
Chemobiological Platform Enables Renewable Conversion of Sugars into Core Aromatic Hydrocarbons of Petroleum
<(From Left) Professor Sun Kyu Han, Ph.D candidate Tae Wan Kim, Professor Kyeong Rok Choi, Professor Sang Yup Lee>
With growing concerns over fossil fuel depletion and the environmental impacts of petrochemical production, scientists are actively exploring renewable strategies to produce essential industrial chemicals. A collaborative research team—led by Distinguished Professor Sang Yup Lee, Senior Vice President for Research, from the Department of Chemical and Biomolecular Engineering, together with Professor Sunkyu Han from the Department of Chemistry at the Korea Advanced Institute of Science and Technology (KAIST)—has developed an integrated chemobiological platform that converts renewable carbon sources such as glucose and glycerol into oxygenated precursors, which are subsequently deoxygenated in the same solvent system to yield benzene, toluene, ethylbenzene, and p-xylene (BTEX), which are fundamental aromatic hydrocarbons used in fuels, polymers, and consumer products.
<Figure 1. Schematic representation of the chemobiological synthesis of BTEX from glucose or glycerol in Escherichia coli>
From Sugars to Aromatic Hydrocarbons of Petroleum
The researchers designed four metabolically engineered strains of Escherichia coli, each programmed to produce a specific oxygenated precursor—phenol, benzyl alcohol, 2-phenylethanol, or 2,5-xylenol. These intermediates are generated through tailored genetic modifications, such as deletion of feedback-regulated enzymes, overexpression of pathway-specific genes, and introduction of heterologous enzymes to expand metabolic capabilities.
During fermentation, the products were continuously extracted into the organic solvent isopropyl myristate (IPM). Acting as a dual-function solvent, IPM not only mitigated the toxic effects of aromatic compounds on cell growth but also served directly as the reaction medium for downstream chemical upgrading. By eliminating the need for intermediate purification, solvent exchange, or distillation, this solvent-integrated system streamlined the conversion of renewable feedstocks into valuable aromatics.
Overcoming Chemical Barriers in An Unconventional Solvent
A central innovation of this work lies in adapting chemical deoxygenation reactions to function efficiently within IPM—a solvent rarely used in organic synthesis. Traditional catalysts and reagents often proved ineffective under these conditions due to solubility limitations or incompatibility with biologically derived impurities.
Through systematic optimization, the team established mild and selective catalytic strategies compatible with IPM. For example, phenol was successfully deoxygenated to benzene in up to 85% yield using a palladium-based catalytic system, while benzyl alcohol was efficiently converted to toluene after activated charcoal pretreatment of the IPM extract. More challenging transformations, such as converting 2-phenylethanol to ethylbenzene, were achieved through a mesylation–reduction sequence adapted to the IPM phase. Likewise, 2,5-xylenol derived from glycerol was converted to p-xylene in 62% yield via a two-step reaction, completing the renewable synthesis of the full BTEX spectrum.
A Sustainable, Modular Framework
Beyond producing BTEX, the study establishes a generalizable framework for integrating microbial biosynthesis with chemical transformations in a continuous solvent environment. This modular approach reduces energy demand, minimizes solvent waste, and enables process intensification—key factors for scaling up renewable chemical production.
The high boiling point of IPM (>300 °C) simplifies product recovery, as BTEX compounds can be isolated by fractional distillation while the solvent is readily recycled. Such a design is consistent with the principles of green chemistry and the circular economy, providing a practical alternative to fossil-based petrochemical processes.
Toward A Carbon-Neutral Future
Dr. Xuan Zou, the first author of this paper, explaind, “By coupling the selectivity of microbial metabolism with the efficiency of chemical catalysis, this platform establishes a renewable pathway to some of the most widely used building blocks in the chemical industry. Future efforts will focus on optimizing metabolic fluxes, extending the platform to additional aromatic targets, and adopting greener catalytic systems.”
In addition, Distinguished Professor Sang Yup Lee noted “As the global demand for BTEX and related chemicals continues to grow, this innovation provides both a scientific and industrial foundation for reducing reliance on petroleum-based processes. It marks an important step toward lowering the carbon footprint of the fuel and chemical sectors while ensuring a sustainable supply of essential aromatic hydrocarbons.”
This research was supported by the Development of Platform Technologies of Microbial Cell Factories for the Next-Generation Biorefineries Project (2022M3J5A1056117) and the Development of Advanced Synthetic Biology Source Technologies for Leading the Biomanufacturing Industry Project (RS-2024-00399424), funded by the National Research Foundation supported by the Korean Ministry of Science and ICT. This study was published in the latest issue of the Proceedings of the National Academy of Sciences of the United States of America (PNAS).
KAIST Exports Global License for New Drug Candidate for Intractable Epilepsy Worth 750 Billion KRW
<(From Left) Professor Jeong Ho Lee, CEO Cheolwon Park, Principal Researcher Sang-min Park>
KAIST (President Kwang Hyung Lee) announced on the 9th of October that Sovargen (co-led by CEOs Cheolwon Park and Jeong Ho Lee), a faculty startup led by Professor Jeong Ho Lee of the KAIST Graduate School of Medical Science and Engineering, has successfully achieved a global technology export deal worth a total of 750 billion KRW. The deal involves an innovative RNA-based new drug candidate for the treatment of intractable epilepsy.
This achievement is drawing attention as a representative example of how groundbreaking discoveries from KAIST’s fundamental medical science research can evolve into actual drug development and global market expansion.
Professor Jeong Ho Lee’s research team was the first in the world to identify that the cause of severe brain diseases such as intractable epilepsy and malignant brain tumors lies in brain somatic mutations—acquired mutations that occur in neural stem cells. Their findings were published in Nature (2015) and Nature Medicine (2018).
Later, together with Cheolwon Park of Sovargen, an expert in drug development, they discovered an RNA-based therapeutic—an Antisense Oligonucleotide (ASO)—that directly targets MTOR, a key mutated gene responsible for epilepsy. Through a large-scale technology transfer agreement with a global pharmaceutical company, they also demonstrated the drug’s commercial potential.
This achievement is particularly significant in that it was led by Professor Jeong Ho Lee, a physician-scientist (M.D.-Ph.D.) who integrates intensive basic research with translational studies and venture entrepreneurship.
An idea that originated in a basic research lab has developed into the world’s first innovative drug (first-in-class) candidate through a startup, creating a virtuous cycle that connects back to the global market.
Sovargen’s Principal Researcher Sang Min Park (KAIST Graduate School of Medical Science and Engineering alumnus) stated, “From identifying the disease cause to developing a new drug and exporting the technology globally, this achievement was made possible entirely through the power of Korean science.” Sovargen CEO Cheolwon Park added, “This success was made possible thanks to the strong support of President Kwang Hyung Lee and key KAIST leaders for both the Graduate School of Medical Science and Engineering and faculty-led startups.”
Professor Jeong Ho Lee commented, “While traditional medical schools in Korea are centered around clinical practice, KAIST fosters a research culture focused on innovation and industrialization. This enabled us to achieve both groundbreaking basic research and global new drug technology export.” He continued, “This success serves as an excellent example of the future direction of KAIST’s medical science research.”
Experts have evaluated this accomplishment as one that opens new therapeutic possibilities for patients suffering from intractable epilepsy—conditions that previously had no treatment options—while also demonstrating that Korean medical science and biotech ventures are capable of competing on the global stage in innovative new drug development.
KAIST President Kwang Hyung Lee remarked, “This achievement is a representative example of how KAIST’s research philosophy—‘from fundamentals to industry’—has been realized in the field of medical science.” He added, “KAIST will continue to pursue bold fundamental research to lead innovations that advance human health and the future bioindustry.”
Next Generation Robots Roaming Shipyards and City Centers
< Diden Robotics Research Team Co., Ltd (Leftmost person in the front row is CEO Joon-Ha Kim)>
KAIST announced on the September 30th that domestic robot startups, founded on KAIST research achievements, are driving new innovation at shipyards and urban worksites.
An industrial walking robot that freely climbs walls and ceilings and a humanoid walking robot that walks through downtown Gangnam are attracting attention as they enter the stage of commercialization. The stars are DIDEN Robotics Co., Ltd. and Eurobotics Co., Ltd.
Diden Robotics is providing a new breakthrough in the industrial automation market, including the shipbuilding industry, by commercializing its innovative 'Seungwol (Ascend and Cross) Robot' technology, which allows it to move freely and work on steel walls and ceilings. Eurobotics is commercializing world-class humanoid walking technology, and this achievement is scheduled to be officially presented at the international humanoid robot conference, 'Humanoids 2025,' to be held on October 1st.
< Diden Robot's Outer Plate (Longi) and Welding Test >
Diden Robotics is a robotics startup jointly founded in March 2024 by four alumni from the KAIST Mechanical Engineering Hu-bo Lab DRCD research team (Professor Hae-Won Park). Its flagship product, 'DIDEN 30,' is a quadrupedal robot designed for use in high-risk work environments that are difficult for humans to access, combining autonomous driving technology, a foot-shaped leg structure, and magnetic feet.
The 'DIDEN 30' successfully completed the 'Longitudinal (longi) Overcoming Test,' in which it stepped over steel stiffeners (longitudinals) densely installed as part of the structure at a ship construction site, proving its potential for field deployment. Currently, the company is conducting research to enhance its functionality so it can stably pass through access holes, the narrow entryways inside ships. It is also pushing for performance improvements so it can be deployed for real tasks such as welding, inspection, and painting starting in the second half of 2026.
A next-generation bipedal walking robot, 'DIDEN Walker,' is also under development. Targeting the completion of a prototype in the fourth quarter of 2025, it is being designed for stable walking in cramped and complex industrial environments. Plans are also underway to equip it with an upper-body manipulator for automated welding in the shipbuilding industry.
Diden Robotics is accelerating the advancement of its proprietary 'Physical AI' technology. The core is the self-developed AI learning platform, 'DIDEN World,' which applies an offline reinforcement learning method where the AI generates optimal motion data in a virtual simulation beforehand and learns without trial and error, increasing learning efficiency and stability.
< Diden Robot (DIDEN 30) >
Furthermore, to actually implement the AI technology, the company is internalizing its hardware and advancing its 3D recognition technology, which serves as the robot's 'eyes.' It is aiming for a completely autonomous walking system that requires no worker intervention by 2026, using technology such as 3D mapping based on four cameras.
In addition to this technological development, Diden Robotics successfully performed the longitudinal overcoming, Seungwol test, and welding work on blocks under construction through a joint development with Samsung Heavy Industries in September. This is a significant achievement, meaning Diden Robotics' technology has been validated in actual industrial settings, moving beyond the laboratory level.
Meanwhile, Diden Robotics is collaborating with major domestic shipyards, including Samsung Heavy Industries, HD Hyundai Samho, Hanwha Ocean, and HD Korea Shipbuilding & Offshore Engineering, to develop site-customized robots.
Joon-Ha Kim, CEO of Diden Robotics, stated, "The successful tests at the Samsung Heavy Industries site proved the practicality and stability of our technology. We will establish ourselves as a leading company in solving labor shortages and driving automation in the shipbuilding industry."
< (Eurobotics Research Team Co., Ltd.)(Leftmost person in the top row is CEO Byung-ho Yoo) >
Eurobotics is an autonomous walking startup jointly founded by three alumni from Professor Hyun Myung's research team at KAIST. It is promoting the commercialization of autonomous walking technology for indoor and outdoor industrial sites, including rough terrain. In a recently released video, a humanoid equipped with control technology developed by Eurobotics attracted attention by walking naturally through the crowd in downtown Gangnam.
The core technology is the 'Blind Walking Controller.' It determines locomotion based only on internal information without external sensors like cameras or LiDAR, enabling stable walking regardless of day, night, or weather. The robot performs locomotion by 'imagining' the terrain without precise terrain modeling, demonstrating robust performance with the same controller across various environments such as sidewalks, downhill slopes, and stairs.
This technology originated from the quadrupedal walking competition at the 2023 International Conference on Robotics and Automation (ICRA), where Professor Myung's lab participated, and proved its world-class capability by winning, beating MIT by a large margin. At the time, Byungg-ho Yoo, CEO of Eurobotics, led the team, and Co-CTOs Min-ho Oh and Dong-kyu Lee directly participated in developing the core autonomous walking technology. Based on this, they continued further development tailored to the humanoid environment and have entered the commercialization stage.
< Eurobotics' Humanoid Walking >
Byung-ho Yoo, CEO of Eurobotics, emphasized, "This video is the first step toward complete humanoid autonomous walking. We will develop KAIST's research achievements into technologies that can be immediately utilized in industrial settings."
Hyeonmin Bae, Head of the KAIST Startup Center, said, "We will provide close support from the initial stages to help the on-campus robotics industry grow actively and assist them in settling down stably."
Kwang Hyung Lee, President of KAIST, stated, "This achievement is a representative case showing that KAIST's fundamental technologies are rapidly spreading to industrial fields through startups. KAIST will continue to actively support innovative entrepreneurship based on challenging research and help lead the global robotics industry."
※ https://2025humanoids.org https://www.seoulairobot.com/
3D Printing Becomes Stronger and More Economical with Light and AI
<(Front) Ph.D. candidate Jisoo Nam, (Back row, from left) Ph.D. candidate Boxin Chen, Professor Miso Kim>
Photocurable 3D printing, widely used for everything from dental treatments to complex prototype manufacturing, is fast and precise but has the limitation of being fragile and easily broken by impact. A KAIST research team has developed a new technology to overcome this weakness, paving the way for the more robust and economical production of everything from medical implants to precision machine parts.
KAIST (President Kwang Hyung Lee) announced on the 29th that Professor Miso Kim's research team in the Department of Mechanical Engineering has developed a new technology that fundamentally resolves the durability limitations of photocurable 3D printing.
Digital Light Processing (DLP)-based 3D printing is a technique that uses light to solidify liquid resin (polymer) to rapidly manufacture precise structures, used in various fields such as dentistry and precision machinery. While traditional injection molding offers excellent durability, it requires significant time and cost for mold fabrication. In contrast, photocurable 3D printing allows for flexible shape realization but has a durability drawback.
Professor Kim's team solved this problem by combining two key elements:
A new photocurable resin material that absorbs shock and vibration while allowing for a wide range of properties from rubber to plastic.
A machine learning-based design technology that automatically assigns optimal strength to each part of the structure.
<Figure 1. Schematic of a new manufacturing technology for high-durability photocurable 3D printing using light-controlled gradient structures. This approach integrates the development of stiffness-controllable viscoelastic polyurethane acrylate (PUA) materials, machine learning-based property gradient optimization, and grayscale DLP 3D printing. The technology enhances damping performance and alleviates stress concentration, providing an integrated solution for high reliability, durability, and customized manufacturing. It demonstrates potential applications in structural components subjected to repetitive loads such as joints, automotive interior parts, and precision machinery components>
The research team developed a Polyurethane Acrylate (PUA) material incorporating dynamic bonds, which significantly increases shock and vibration absorption capability compared to existing materials. Furthermore, they successfully applied 'grayscale DLP' technology, which controls the light intensity to achieve different strengths from a single resin composition, thereby assigning customized strength to specific areas within the structure. This concept is inspired by the harmonious and different roles played by bone and cartilage in the human body.
A machine learning algorithm automatically proposes the optimal strength distribution by analyzing the structure and load conditions. This organically connects material development and structural design, enabling customized strength distribution.
The economic efficiency is also noteworthy. Previously, expensive 'multi-material printing' technology was required to achieve diverse material properties, but this new technology yields the same effect with a single material and a single process, significantly reducing production costs. It eliminates the need for complex equipment or material management, and the AI-based structural optimization shortens research and development time and product design costs.
Professor Miso Kim explained, "This technology simultaneously expands the degrees of freedom in material properties and structural design. Patient-specific implants will become more durable and comfortable, and precision machine parts can be manufactured more robustly." She added, "The fact that it secures economic viability by realizing various strengths with a single material and single process is highly significant," and "We anticipate its utilization across various industrial fields such as biomedical, aerospace, and robotics."
The research was spearheaded by Professor Miso Kim's team at the KAIST Department of Mechanical Engineering, with Ph.D. candidate Jisoo Nam as the first author. Boxin Chen, a student from Sungkyunkwan University, also contributed to the collaborative research. The findings were published online on July 16 in the world-renowned journal in materials science, Advanced Materials (IF 26.8). Recognizing the research's excellence, it was also selected for the journal's Frontispiece.
Paper Title: Machine Learning-Driven Grayscale Digital Light Processing for Mechanically Robust 3D-Printed Gradient Materials
DOI: 10.1002/adma.202504075
The achievements of this research have brought Professor Miso Kim significant international attention, as she simultaneously received the 'Wiley Rising Star Award' and the 'Wiley Women in Materials Science Award' in July 2025, hosted by the international academic publisher Wiley.
The Wiley Rising Star Award is given to emerging researchers with the potential for academic leadership, and the Wiley Women in Materials Science Award is a prestigious honor established to celebrate outstanding female scientists in the field of materials science.
<Figure 2. Frontispiece image (scheduled for Issue 42). Multi-property structure fabricated using a photocurable 3D printer. By varying the projector light intensity by location, stronger light creates rigid regions while weaker light forms flexible ones. AI designs an optimized pattern for the structural shape to prevent fracture and reinforce the overall strength.>
This research was supported by the National Research Foundation of Korea (NRF) grants funded by the Korean government (MSIT) (Nos. NRF-2021R1A2C2095767, RS-2023-00254689, and RS-2024-00433654).
KAIST Develops Semiconductor Neuron that Remembers and Responds Like the Brain
<(From left, clockwise) Professor Kyung Min Kim, Min-Gu Lee, Dae-Hee Kim, Dr. Han-Chan Song, Tae-Uk Ko, Moon-Gu Choi, and Eun-Young Kim>
The human brain does more than simply regulate synapses that exchange signals; individual neurons also process information through “intrinsic plasticity,” the adaptive ability to become more sensitive or less sensitive depending on context. Existing artificial intelligence semiconductors, however, have struggled to mimic this flexibility of the brain. A KAIST research team has now developed next-generation, ultra-low-power semiconductor technology that implements this ability as well, drawing significant attention.
KAIST (President Kwang Hyung Lee) announced on September 28 that a research team led by Professor Kyung Min Kim of the Department of Materials Science and Engineering developed a “Frequency Switching Neuristor” that mimics “intrinsic plasticity,” a property that allows neurons to remember past activity and autonomously adjust their response characteristics.
“Intrinsic plasticity” refers to the brain’s adaptive ability- for example, becoming less startled when hearing the same sound repeatedly, or responding more quickly to a specific stimulus after repeated training. The “Frequency Switching Neuristor” is an artificial neuron device that autonomously adjusts the frequency of its signals, much like how the brain becomes less startled by repeated stimuli or, conversely, increasingly sensitive through training.
The research team combined a “volatile Mott memristor,” which reacts momentarily before returning to its original state, with a “non-volatile memristor,” which remembers input signals for long periods of time. This enabled the implementation of a device that can freely control how often a neuron fires (its spiking frequency).
<Figure 1. Conceptual comparison between a neuron and a frequency-tunable neuristor. The intrinsic plasticity of brain neurons regulates excitability through ion channels. Similarly, the frequency-tunable neuristor uses a volatile Mott device to generate current spikes, while a non-volatile VCM device adjusts resistance states to realize comparable frequency modulation characteristics>
In this device, neuronal spike signals and memristor resistance changes influence each other, automatically adjusting responses. Put simply, it reproduces within a single semiconductor device how the brain becomes less startled by repeated sounds or more sensitive to repeated stimuli.
To verify the effectiveness of this technology, the researchers conducted simulations with a “sparse neural network.” They found that, through the neuron’s built-in memory function, the system achieved the same performance with 27.7% less energy consumption compared to conventional neural networks.
They also demonstrated excellent resilience: even if some neurons were damaged, intrinsic plasticity allowed the network to reorganize itself and restore performance. In other words, artificial intelligence using this technology consumes less electricity while maintaining performance, and it can compensate for partial circuit failures to resume normal operation.
Professor Kyung Min Kim, who led the research, stated, “This study implemented intrinsic plasticity, a core function of the brain, in a single semiconductor device, thereby advancing the energy efficiency and stability of AI hardware to a new level. This technology, which enables devices to remember their own state and adapt or recover even from damage, can serve as a key component in systems requiring long-term stability, such as edge computing and autonomous driving.”
This research was carried out with Dr. Woojoon Park (now at Forschungszentrum Jülich, Germany) and Dr. Hanchan Song (now at ETRI) as co-first authors, and the results were published online on August 18 in Advanced Materials (IF 26.8), a leading international journal in materials science.
※ Paper title: “Frequency Switching Neuristor for Realizing Intrinsic Plasticity and Enabling Robust Neuromorphic Computing,” DOI: 10.1002/adma.202502255
This research was supported by the National Research Foundation of Korea and Samsung Electronics.
KAIST, Cancer Cell Nuclear Hypertrophy May Suppress Spread
<(From Left) Ph.D candidate Saemyeong Hong, Dr. Changgon Kim, Professor Joon Kim, Professor Ji Hun Kim>
In tissue biopsies, cancer cells are frequently observed to have nuclei (the cell's genetic information storage) larger than normal. Until now, this was considered a sign that the cancer was worsening, but the exact cause and effect had not been elucidated. In this study, the KAIST research team found that cancer cell nuclear hypertrophy is not a cause of malignancy but a temporary response to replication stress, and that it can, in fact, suppress metastasis. This discovery is expected to lead to the development of new diagnostic and therapeutic strategies for cancer and metastasis inhibition.
KAIST (President Kwang Hyung Lee) announced on the September 26th that a research team led by Professor Joon Kim of the Graduate School of Medical Science and Engineering, in collaboration with the research teams of Professor Ji Hun Kim and Professor You-Me Kim, discovered the molecular reason why the nucleus enlarges in cancer cells. This achievement provides an important clue for understanding nuclear hypertrophy, a phenomenon frequently observed in pathological examinations but whose direct cause and relationship with cancer development were unclear.
The research team confirmed that DNA replication stress (the burden and error signal that occurs when a cell copies its DNA), which is common in cancer cells, causes the 'actin' protein inside the nucleus to aggregate (polymerize), which is the direct cause of the nuclear enlargement.
<Mechanisms Inducing Nuclear Enlargement in Cancer Cells and Its Impact on Cellular Physiology>
This result suggests that the change in cancer cell nuclear size may not simply be a "trait evolved by the cancer cell for its benefit." Rather, it suggests that it is a temporary, makeshift response to stress, and that it may impose constraints on the cancer cell's potential for metastasis.
Therefore, future research needs to explore whether changes in nuclear size can become a target for cancer treatment or a clue related to the suppression of metastasis. That is, nuclear hypertrophy may be a temporary response to replication stress and should not necessarily be seen as indicating the malignancy of the cancer.
This conclusion was substantiated through: (1) Gene Function Screening (inhibiting thousands of genes sequentially to find the key genes involved in nuclear size regulation); (2) Transcriptome Analysis (confirming which gene programs are activated when the nucleus enlarges); (3) 3D Genome Structure Analysis (Hi-C), which revealed that nuclear hypertrophy is not just a size change but is connected to changes in DNA folding and gene arrangement; and (4) Mouse Xenograft Models (confirming that cancer cells with enlarged nuclei actually have reduced motility and metastatic ability).
Professor Joon Kim of the Graduate School of Medical Science and Engineering said, "We confirmed that DNA replication stress disrupts the nuclear size balance, explaining the underlying mechanism of long-standing pathological observations," adding, "The possibility of utilizing nuclear structural changes as a new indicator for cancer diagnosis and metastasis prediction has now opened up."
Dr. Changgon Kim (currently a Hematology and Oncology specialist at Korea University Anam Hospital) and Saemyeong Hong, a PhD candidate from the KAIST Graduate School of Medical Science and Engineering, participated as co-first authors in this study. The results were published online in the international journal PNAS (Proceedings of the National Academy of Sciences of the United States of America) on September 9th.
※ Paper Title: Replication stress-induced nuclear hypertrophy alters chromatin topology and impacts cancer cell fitness ※ DOI: https://doi.org/10.1073/pnas.2424709122
Meanwhile, this research was supported by the Mid-career Researcher Program and the Engineering Research Center (ERC) program of the National Research Foundation of Korea.
Thinking outside the box to Fabricate Customized 3D Neural Chips
<(From Left) Professor Yoonkey Nam, Dr. Dongjo Yoon from the Department of Bio and Brain Engineering>
Cultured neural tissues have been widely used as a simplified experimental model for brain research. However, existing devices for growing and recording neural tissues, which are manufactured using semiconductor processes, have limitations in terms of shape modification and the implementation of three-dimensional (3D) structures.
By "thinking outside the box," a KAIST research team has successfully created a customized 3D neural chip. They first used a 3D printer to fabricate a hollow channel structure, then used capillary action to automatically fill the channels with conductive ink, creating the electrodes and wiring. This achievement is expected to significantly increase the design freedom and versatility of brain science and brain engineering research platforms.
On the 25th, KAIST announced that a research team led by Professor Yoonkey Nam from the Department of Bio and Brain Engineering has successfully developed a platform technology that overcomes the limitations of traditional semiconductor-based manufacturing. This technology allows for the precise fabrication of "3D microelectrode array" (neural interfaces with multiple microelectrodes arranged in a 3D space to measure and stimulate the electrophysiological signal of neurons) in various customized forms for in vitro culture chips.
Existing 3D microelectrode array fabrication, based on semiconductor processes, has limited 3D design freedom and is expensive. While 3D printing-based fabrication techniques have recently been proposed to overcome these issues, they still have limitations in terms of 3D design freedom for various in vitro neural network structures because they follow the traditional sequence of "conductive material patterning → insulator coating → electrode opening."
The KAIST research team leveraged the excellent 3D design freedom provided by 3D printing technology and its ability to use printed materials as insulators. By reversing the traditional process, they established an innovative method that allows for more flexible design and functional measurement of 3D neuronal network models for in vitro culture.
<Schematic Diagram of an Integrated Cell Culture Substrate-Microelectrode Array Platform for In Vitro Cultured 3D Neural Network Models>
First, they used a 3D printer to print a hollow 3D insulator with micro-tunnels. This structure was designed to serve as a stable scaffold for conductive materials in 3D space while also supporting the creation of various 3D neuronal networks. They then demonstrated that by using capillary action to fill these internal micro-tunnels with conductive ink, they could create a 3D scaffold-microelectrode array with more freely arranged microelectrodes within a complex 3D culture support structure.
The new platform can be used to create various chip shapes, such as probe-type, cube-type, and modular-type, and supports the fabrication of electrodes using different materials like graphite, conductive polymers, and silver nanoparticles. This allows for the simultaneous measurement of multichannel neural signals from both inside and outside the 3D neuronal network, enabling precise analysis of the dynamic interactions and connectivity between neurons.
Professor Nam stated, "This research, which combines 3D printing and capillary action, is an achievement that significantly expands the freedom of neural chip fabrication." He added that it will contribute to the advancement of fundamental brain science research using neural tissue, as well as applied fields like cell-based biosensors and biocomputing.
Dr. Dongjo Yoon from KAIST's Department of Bio and Brain Engineering participated as the first author of the study. The research findings were published online in the international academic journal Advanced Functional Materials (June 25th issue).
※Paper Title: Highly Customizable Scaffold-Type 3D Microelectrode Array Platform for Design and Analysis of the 3D Neuronal Network In Vitro
This research was supported by the Consolidator Grants Program and the Global Basic Research Laboratory Program of the National Research Foundation of Korea.
Simultaneous On and Off Gene Control with Gene Scissors
<(From left to right) Dr. Soo Young Moon, KAIST Institute of Life Science,Professor Ju Young Lee, Graduate School of Engineering Biology (Adjunct Professor of Biological Sciences),Dr. Myung Hyun Noh, Korea Research Institute of Chemical Technology (KRICT),Researcher Nan-Yeong An, Department of Biological Sciences>
Turning genes on and off is like flipping a light switch, controlling whether genes in a cell are active. When a gene is turned on, the production of proteins or other substances is promoted; when it's turned off, production is suppressed. Korean researchers have gone beyond the limitations of existing CRISPR technology, which focused primarily on "off" functions, by developing the world's first innovative system that can simultaneously turn genes on and off, opening a new paradigm for the synthetic biology-based bio-industry.
A joint research team led by Professor Ju Young Lee of KAIST Graduate School of Biological Engineering (Adjunct Professor of Biological Sciences) and Dr. Myung Hyun Noh of the Korea Research Institute of Chemical Technology (KRICT), an organization under the National Research Council of Science & Technology (NST) , announced on the 21st that they have developed a new dual-mode CRISPR gene editing system that can simultaneously turn on and off desired genes in E. coli.
E. coli is a representative microorganism that is easy to experiment with and can be directly applied to industrial uses. Meanwhile, CRISPR technology is considered one of the most innovative tools in 21st-century biotechnology.
In particular, bacteria, which are the foundation of synthetic biology, have a simple structure and multiply rapidly, while also being able to produce a variety of useful substances. Therefore, gene activation in bacteria is a key technology for designing "microbial factories," and its industrial value is very high.
The core of synthetic biology is to design the genetic circuits of living organisms like programming a circuit board to perform a desired function. Just as switches are turned on and off in an electronic circuit, a technology is needed to optimize metabolic pathways by activating certain genes while suppressing others. The dual-mode gene scissors developed by the research team are the key tool that enables this precise gene regulation.
Existing CRISPR gene scissors were primarily specialized for the "off" function (repression) and were excellent at blocking gene expression, but their ability to turn genes on was very limited.
Furthermore, for CRISPR to work, a specific DNA recognition sequence (PAM, protospacer adjacent motif) is required, and the narrow range of PAM recognition in existing systems limited the scope of genes that could be controlled.
In addition, while CRISPR-based activation (CRISPRa) has been somewhat developed in eukaryotic cells (human, plant, and animal cells), there were limitations in bacteria where the "on" function did not work properly due to differences in their internal transcription regulation mechanisms.
To overcome these limitations, the research team expanded the target range to access more genes and significantly improved gene activation performance by utilizing E. coli proteins. As a result, the gene scissors, which were previously "mainly for turning off," have evolved into a system that can simultaneously control both "on" and "off."
The performance verification results of the developed system were very impressive. In gene activation experiments, expression levels increased by up to 4.9 times, and in repression experiments, they could be suppressed by up to 83%.
Even more astonishing was the ability to control two different genes simultaneously. The team successfully activated one gene by 8.6 times while simultaneously repressing another by 90%.
< (Left) The principle of the dual-mode CRISPR gene scissors. When the guide RNA (gRNA) binds to the target sequence, dxCas9-CRP either promotes (CRISPRa) or inhibits (CRISPRi) the binding of RNA polymerase near the transcription start site, precisely controlling gene expression. (Center) A large-scale screening of the entire E. coli genome is conducted to identify key regulatory targets for optimizing target substance production. The metabolic pathway for producing the target substance is then re-engineered by simultaneously regulating gene expression through activation and repression. (Right) The dual-mode CRISPR gene scissors system enables systematic redesign of cell metabolism, precise reconfiguration of gene expression, and the construction of microbial strains that can perform various functions, ultimately leading to a significant increase in target substance productivity. In this study, the dual-mode CRISPR system was applied to E. coli to demonstrate the enhanced production of 'violacein,' a purple functional biopigment with anticancer effects, and its potential for expansion to other bacterial species was also confirmed. >
To demonstrate the practicality of this technology, the research team challenged themselves to increase the production of 'violacein,' a purple pigment with anticancer properties. Through large-scale experiments on all genes of E. coli, they identified genes that help in violacein production.
As a result, production increased by 2.9 times when the 'rluC' gene, which helps protein production, was turned on, and by 3.0 times when the 'ftsA' gene, which helps cell division, was turned off. When both genes were controlled simultaneously, a greater synergistic effect was observed, achieving a remarkable 3.7-fold increase in production.
Dr. Myung Hyun Noh of KRICT stated, "Precise gene activation is now possible in bacteria," and "This will greatly contribute to the development of the synthetic biology-based bio-industry."
Professor Ju Young Lee said, "This research is a successful outcome of combining gene scissors with synthetic biology to significantly enhance the efficiency of microbial production platforms," and "The ability to control a complex genetic network with a single system presents a new research paradigm." He added, "This technology has also been confirmed to work in other bacterial species and can be utilized in various fields such as the production of biopharmaceuticals, chemicals, and fuels."
< (A) A diagram of the violacein biosynthesis pathway, a functional biopigment produced from the starting material L-tryptophan through several enzymatic reactions. Violacein is a functional substance with broad applications in various industries and research fields, including medicine, healthcare, dyes, textiles, food and beverage, and cosmetics. (B) The results of a large-scale screening of gRNAs for gene activation and repression using the dual-mode CRISPR gene scissors system confirmed a 2.9-fold increase in violacein production (mg/L) upon rluC activation and a 3.0-fold increase upon ftsA repression compared to the control group. >
The results of this research, with Dr. Soo Young Moon, a postdoctoral researcher at our university's Institute of Life Science, as the first author, were published online in 'Nucleic Acids Research,' a top-tier journal in the field of molecular biology, on August 21st.
Paper Title: Dual-mode CRISPRa/i for genome-scale metabolic rewiring in Escherichia coli
Author Information: Soo Young Moon (KAIST, First Author), Mi Ri Kim (KRICT), Nan-Yeong An (KAIST), Myung Hyun Noh (KRICT, Corresponding Author), Ju Young Lee (KAIST, Corresponding Author) (Total of 5 authors)
DOI: 10.1093/nar/gkad818
This research was supported by the joint research and development program of the Ministry of Science and ICT, the National Research Foundation of Korea, and Boston Korea.
Next-Generation Humanoid Robot Capable of Moonwalk Developed
<From the middle of the back row, clockwise: Professor Hae-Won Park, Dongyun Kang (Ph.D. candidate), Hajun Kim (Ph.D. candidate), JongHun Choe (Ph.D. candidate), Min-su Kim (Research Professor)>
KAIST research team's independently developed humanoid robot boasts world-class driving performance, reaching speeds of 12km/h, along with excellent stability, maintaining balance even with its eyes closed or on rough terrain. Furthermore, it can perform complex human-specific movements such as duck walk and moonwalk, drawing attention as a next-generation robot platform that can be utilized in actual industrial settings. Professor Park Hae-won's research team at the Humanoid Robot Research Center (HuboLab) of KAIST's Department of Mechanical Engineering announced on the 19th that they have independently developed the lower body platform for a next-generation humanoid robot. The developed humanoid is characterized by its design tailored for human-centric environments, targeting a height (165cm) and weight (75kg) similar to that of a human. The significance of the newly developed lower body platform is immense as the research team directly designed and manufactured all core components, including motors, reducers, and motor drivers. By securing key components that determine the performance of humanoid robots with their own technology, they have achieved technological independence in terms of hardware. In addition, the research team trained an AI controller through a self-developed reinforcement learning algorithm in a virtual environment, successfully applied it to real-world environments by overcoming the Sim-to-Real Gap, thereby securing technological independence in terms of algorithms as well.
<Developed 'KAIST Humanoid' Lower Body Platform>
Currently, the developed humanoid can run at a maximum speed of 3.25m/s (approximately 12km/h) on flat ground and has a step-climbing capability of over 30cm (a performance indicator showing how high a curb, stairs, or obstacle can be overcome). The team plans to further enhance its performance, aiming for a driving speed of 4.0m/s (approximately 14km/h), ladder climbing, and over 40cm step-climbing capability.
<‘KAIST Humanoid’ Lower Body Platform running>
Professor Hae-Won Park's team is collaborating with Professor Jae-min Hwangbo's team (arms) from KAIST's Department of Mechanical Engineering, Professor Sangbae Kim's team (hands) from MIT, Professor Hyun Myung's team (localization and navigation) from KAIST's Department of Electrical Engineering, and Professor Jae-hwan Lim's team (vision-based manipulation intelligence) from KAIST's Kim Jaechul AI Graduate School to implement a complete humanoid hardware with an upper body and AI. Through this, they are developing technology to enable the robot to perform complex tasks such as carrying heavy objects, operating valves, cranks, and door handles, and simultaneously walking and manipulating when pushing carts or climbing ladders. The ultimate goal is to secure versatile physical abilities to respond to the complex demands of actual industrial sites.
<An Intermediate Result: A Single-Leg Hopping Robot Has Been Developed>
During this process, the research team also developed a single-leg 'Hopping' robot. This robot demonstrated high-level movements, maintaining balance on one leg and repeatedly hopping, and even exhibited extreme athletic abilities such as a 360-degree somersault. Especially in a situation where imitation learning was impossible due to the absence of a biological reference model, the research team achieved significant results by implementing an AI controller through reinforcement learning that optimizes the center of mass velocity while reducing landing impact. Professor Park Hae-won stated, "This achievement is an important milestone that has achieved independence in both hardware and software aspects of humanoid research by securing core components and AI controllers with our own technology," and added, "We will further develop it into a complete humanoid including an upper body to solve the complex demands of actual industrial sites and furthermore, foster it as a next-generation robot that can work alongside humans."
<Key Components of the Directly Developed Robot: (a) Reducer, (b) Motor Stator, (c) Motor Driver, (d) EtherCAT-CAN convert board>
The results of this research will be presented by JongHun Choe, a Ph.D. candidate in Mechanical Engineering, as the first author, on hardware development at 'Humanoids 2025', an international humanoid robot specialized conference held on October 1st. Additionally, Ph.D. candidates Dongyun Kang, Gijeong Kim, and JongHun Choe from Mechanical Engineering will present the AI algorithm achievements as co-first authors at 'CoRL 2025', the top conference in robot intelligence, held on September 29th. ※Paper Titles and Papers: Learning Impact-Rich Rotational Maneuvers via Centroidal Velocity Rewards and Sim-to-Real Techniques: A One-Leg Hopper Flip Case Study, Conference on Robot Learning (CoRL), Seoul, Korea 2025, Dongyun Kang, Gijeong Kim, JongHun Choe, Hajun Kim, Hae-Won Park, arxiv version: https://arxiv.org/abs/2505.12222 Design of a 3-DOF Hopping Robot with an Optimized Gearbox: An Intermediate Platform Toward Bipedal Robots, IEEE-RAS, International Conference on Humanoid Robots, Seoul, Korea, 2025, JongHun Choe, Gijeong Kim, Hajun Kim, Dongyun Kang, Min-Su Kim, Hae-Won Park, arxiv version: https://arxiv.org/abs/2505.12231 This research was supported by research funding from the Ministry of Trade, Industry and Energy and the Korea Institute of Industrial Technology Planning and Evaluation (KEIT) (RS-2024-00427719). ※ Related Video: https://youtu.be/ytWO7lldN4c