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KAIST Proposes AI Training Method that will Drastically Shorten Time for Complex Quantum Mechanical Calculations
- Professor Yong-Hoon Kim's team from the School of Electrical Engineering succeeded for the first time in accelerating quantum mechanical electronic structure calculations using a convolutional neural network (CNN) model
- Presenting an AI learning principle of quantum mechanical 3D chemical bonding information, the work is expected to accelerate the computer-assisted designing of next-generation materials and devices
The close relationship between AI and high-performance scientific computing can be seen in the fact that both the 2024 Nobel Prizes in Physics and Chemistry were awarded to scientists for their AI-related research contributions in their respective fields of study. KAIST researchers succeeded in dramatically reducing the computation time for highly sophisticated quantum mechanical computer simulations by predicting atomic-level chemical bonding information distributed in 3D space using a novel AI approach.
KAIST (President Kwang-Hyung Lee) announced on the 30th of October that Professor Yong-Hoon Kim's team from the School of Electrical Engineering developed a 3D computer vision artificial neural network-based computation methodology that bypasses the complex algorithms required for atomic-level quantum mechanical calculations traditionally performed using supercomputers to derive the properties of materials.
< Figure 1. Various methodologies are utilized in the simulation of materials and materials, such as quantum mechanical calculations at the nanometer (nm) level, classical mechanical force fields at the scale of tens to hundreds of nanometers, continuum dynamics calculations at the macroscopic scale, and calculations that mix simulations at different scales. These simulations are already playing a key role in a wide range of basic research and application development fields in combination with informatics techniques. Recently, there have been active efforts to introduce machine learning techniques to radically accelerate simulations, but research on introducing machine learning techniques to quantum mechanical electronic structure calculations, which form the basis of high-scale simulations, is still insufficient. >
The quantum mechanical density functional theory (DFT) calculations using supercomputers have become an essential and standard tool in a wide range of research and development fields, including advanced materials and drug design, as they allow fast and accurate prediction of material properties.
*Density functional theory (DFT): A representative theory of ab initio (first principles) calculations that calculate quantum mechanical properties from the atomic level.
However, practical DFT calculations require generating 3D electron density and solving quantum mechanical equations through a complex, iterative self-consistent field (SCF)* process that must be repeated tens to hundreds of times. This restricts its application to systems with only a few hundred to a few thousand atoms.
*Self-consistent field (SCF): A scientific computing method widely used to solve complex many-body problems that must be described by a number of interconnected simultaneous differential equations.
Professor Yong-Hoon Kim’s research team questioned whether recent advancements in AI techniques could be used to bypass the SCF process. As a result, they developed the DeepSCF model, which accelerates calculations by learning chemical bonding information distributed in a 3D space using neural network algorithms from the field of computer vision.
< Figure 2. The deepSCF methodology developed in this study provides a way to rapidly accelerate DFT calculations by avoiding the self-consistent field process (orange box) that had to be performed repeatedly in traditional quantum mechanical electronic structure calculations through artificial neural network techniques (green box). The self-consistent field process is a process of predicting the 3D electron density, constructing the corresponding potential, and then solving the quantum mechanical Cohn-Sham equations, repeating tens to hundreds of times. The core idea of the deepSCF methodology is that the residual electron density (δρ), which is the difference between the electron density (ρ) and the sum of the electron densities of the constituent atoms (ρ0), corresponds to chemical bonding information, so the self-consistent field process is replaced with a 3D convolutional neural network model. >
The research team focused on the fact that, according to density functional theory, electron density contains all quantum mechanical information of electrons, and that the residual electron density — the difference between the total electron density and the sum of the electron densities of the constituent atoms — contains chemical bonding information. They used this as the target for machine learning.
They then adopted a dataset of organic molecules with various chemical bonding characteristics, and applied random rotations and deformations to the atomic structures of these molecules to further enhance the model’s accuracy and generalization capabilities. Ultimately, the research team demonstrated the validity and efficiency of the DeepSCF methodology on large, complex systems.
< Figure 3. An example of applying the deepSCF methodology to a carbon nanotube-based DNA sequence analysis device model (top left). In addition to classical mechanical interatomic forces (bottom right), the residual electron density (top right) and quantum mechanical electronic structure properties such as the electronic density of states (DOS) (bottom left) containing information on chemical bonding are rapidly predicted with an accuracy corresponding to the standard DFT calculation results that perform the SCF process. >
Professor Yong-Hoon Kim, who supervised the research, explained that his team had found a way to map quantum mechanical chemical bonding information in a 3D space onto artificial neural networks. He noted, “Since quantum mechanical electron structure calculations underpin materials simulations across all scales, this research establishes a foundational principle for accelerating material calculations using artificial intelligence.”
Ryong-Gyu Lee, a PhD candidate in the School of Electrical Engineering, served as the first author of this research, which was published online on October 24 in Npj Computational Materials, a prestigious journal in the field of material computation. (Paper title: “Convolutional network learning of self-consistent electron density via grid-projected atomic fingerprints”)
This research was conducted with support from the KAIST High-Risk Research Program for Graduate Students and the National Research Foundation of Korea’s Mid-career Researcher Support Program.
2024.10.30 View 801 -
KAIST develops an artificial muscle device that produces force 34 times its weight
- Professor IlKwon Oh’s research team in KAIST’s Department of Mechanical Engineering developed a soft fluidic switch using an ionic polymer artificial muscle that runs with ultra-low power to lift objects 34 times greater than its weight.
- Its light weight and small size make it applicable to various industrial fields such as soft electronics, smart textiles, and biomedical devices by controlling fluid flow with high precision, even in narrow spaces.
Soft robots, medical devices, and wearable devices have permeated our daily lives. KAIST researchers have developed a fluid switch using ionic polymer artificial muscles that operates at ultra-low power and produces a force 34 times greater than its weight. Fluid switches control fluid flow, causing the fluid to flow in a specific direction to invoke various movements.
KAIST (President Kwang-Hyung Lee) announced on the 4th of January that a research team under Professor IlKwon Oh from the Department of Mechanical Engineering has developed a soft fluidic switch that operates at ultra-low voltage and can be used in narrow spaces.
Artificial muscles imitate human muscles and provide flexible and natural movements compared to traditional motors, making them one of the basic elements used in soft robots, medical devices, and wearable devices. These artificial muscles create movements in response to external stimuli such as electricity, air pressure, and temperature changes, and in order to utilize artificial muscles, it is important to control these movements precisely.
Switches based on existing motors were difficult to use within limited spaces due to their rigidity and large size. In order to address these issues, the research team developed an electro-ionic soft actuator that can control fluid flow while producing large amounts of force, even in a narrow pipe, and used it as a soft fluidic switch.
< Figure 1. The separation of fluid droplets using a soft fluid switch at ultra-low voltage. >
The ionic polymer artificial muscle developed by the research team is composed of metal electrodes and ionic polymers, and it generates force and movement in response to electricity. A polysulfonated covalent organic framework (pS-COF) made by combining organic molecules on the surface of the artificial muscle electrode was used to generate an impressive amount of force relative to its weight with ultra-low power (~0.01V).
As a result, the artificial muscle, which was manufactured to be as thin as a hair with a thickness of 180 µm, produced a force more than 34 times greater than its light weight of 10 mg to initiate smooth movement. Through this, the research team was able to precisely control the direction of fluid flow with low power.
< Figure 2. The synthesis and use of pS-COF as a common electrode-electrolyte host for electroactive soft fluid switches. A) The synthesis schematic of pS-COF. B) The schematic diagram of the operating principle of the electrochemical soft switch. C) The schematic diagram of using a pS-COF-based electrochemical soft switch to control fluid flow in dynamic operation. >
Professor IlKwon Oh, who led this research, said, “The electrochemical soft fluidic switch that operate at ultra-low power can open up many possibilities in the fields of soft robots, soft electronics, and microfluidics based on fluid control.” He added, “From smart fibers to biomedical devices, this technology has the potential to be immediately put to use in a variety of industrial settings as it can be easily applied to ultra-small electronic systems in our daily lives.”
The results of this study, in which Dr. Manmatha Mahato, a research professor in the Department of Mechanical Engineering at KAIST, participated as the first author, were published in the international academic journal Science Advances on December 13, 2023. (Paper title: Polysulfonated Covalent Organic Framework as Active Electrode Host for Mobile Cation Guests in Electrochemical Soft Actuator)
This research was conducted with support from the National Research Foundation of Korea's Leader Scientist Support Project (Creative Research Group) and Future Convergence Pioneer Project.
* Paper DOI: https://www.science.org/doi/abs/10.1126/sciadv.adk9752
2024.01.11 View 6411 -
KAIST’s Robo-Dog “RaiBo” runs through the sandy beach
KAIST (President Kwang Hyung Lee) announced on the 25th that a research team led by Professor Jemin Hwangbo of the Department of Mechanical Engineering developed a quadrupedal robot control technology that can walk robustly with agility even in deformable terrain such as sandy beach.
< Photo. RAI Lab Team with Professor Hwangbo in the middle of the back row. >
Professor Hwangbo's research team developed a technology to model the force received by a walking robot on the ground made of granular materials such as sand and simulate it via a quadrupedal robot. Also, the team worked on an artificial neural network structure which is suitable in making real-time decisions needed in adapting to various types of ground without prior information while walking at the same time and applied it on to reinforcement learning. The trained neural network controller is expected to expand the scope of application of quadrupedal walking robots by proving its robustness in changing terrain, such as the ability to move in high-speed even on a sandy beach and walk and turn on soft grounds like an air mattress without losing balance.
This research, with Ph.D. Student Soo-Young Choi of KAIST Department of Mechanical Engineering as the first author, was published in January in the “Science Robotics”. (Paper title: Learning quadrupedal locomotion on deformable terrain).
Reinforcement learning is an AI learning method used to create a machine that collects data on the results of various actions in an arbitrary situation and utilizes that set of data to perform a task. Because the amount of data required for reinforcement learning is so vast, a method of collecting data through simulations that approximates physical phenomena in the real environment is widely used.
In particular, learning-based controllers in the field of walking robots have been applied to real environments after learning through data collected in simulations to successfully perform walking controls in various terrains.
However, since the performance of the learning-based controller rapidly decreases when the actual environment has any discrepancy from the learned simulation environment, it is important to implement an environment similar to the real one in the data collection stage. Therefore, in order to create a learning-based controller that can maintain balance in a deforming terrain, the simulator must provide a similar contact experience.
The research team defined a contact model that predicted the force generated upon contact from the motion dynamics of a walking body based on a ground reaction force model that considered the additional mass effect of granular media defined in previous studies.
Furthermore, by calculating the force generated from one or several contacts at each time step, the deforming terrain was efficiently simulated.
The research team also introduced an artificial neural network structure that implicitly predicts ground characteristics by using a recurrent neural network that analyzes time-series data from the robot's sensors.
The learned controller was mounted on the robot 'RaiBo', which was built hands-on by the research team to show high-speed walking of up to 3.03 m/s on a sandy beach where the robot's feet were completely submerged in the sand. Even when applied to harder grounds, such as grassy fields, and a running track, it was able to run stably by adapting to the characteristics of the ground without any additional programming or revision to the controlling algorithm.
In addition, it rotated with stability at 1.54 rad/s (approximately 90° per second) on an air mattress and demonstrated its quick adaptability even in the situation in which the terrain suddenly turned soft.
The research team demonstrated the importance of providing a suitable contact experience during the learning process by comparison with a controller that assumed the ground to be rigid, and proved that the proposed recurrent neural network modifies the controller's walking method according to the ground properties.
The simulation and learning methodology developed by the research team is expected to contribute to robots performing practical tasks as it expands the range of terrains that various walking robots can operate on.
The first author, Suyoung Choi, said, “It has been shown that providing a learning-based controller with a close contact experience with real deforming ground is essential for application to deforming terrain.” He went on to add that “The proposed controller can be used without prior information on the terrain, so it can be applied to various robot walking studies.”
This research was carried out with the support of the Samsung Research Funding & Incubation Center of Samsung Electronics.
< Figure 1. Adaptability of the proposed controller to various ground environments. The controller learned from a wide range of randomized granular media simulations showed adaptability to various natural and artificial terrains, and demonstrated high-speed walking ability and energy efficiency. >
< Figure 2. Contact model definition for simulation of granular substrates. The research team used a model that considered the additional mass effect for the vertical force and a Coulomb friction model for the horizontal direction while approximating the contact with the granular medium as occurring at a point. Furthermore, a model that simulates the ground resistance that can occur on the side of the foot was introduced and used for simulation. >
2023.01.26 View 11510 -
Yuji Roh Awarded 2022 Microsoft Research PhD Fellowship
KAIST PhD candidate Yuji Roh of the School of Electrical Engineering (advisor: Prof. Steven Euijong Whang) was selected as a recipient of the 2022 Microsoft Research PhD Fellowship.
< KAIST PhD candidate Yuji Roh (advisor: Prof. Steven Euijong Whang) >
The Microsoft Research PhD Fellowship is a scholarship program that recognizes outstanding graduate students for their exceptional and innovative research in areas relevant to computer science and related fields. This year, 36 people from around the world received the fellowship, and Yuji Roh from KAIST EE is the only recipient from universities in Korea. Each selected fellow will receive a $10,000 scholarship and an opportunity to intern at Microsoft under the guidance of an experienced researcher.
Yuji Roh was named a fellow in the field of “Machine Learning” for her outstanding achievements in Trustworthy AI. Her research highlights include designing a state-of-the-art fair training framework using batch selection and developing novel algorithms for both fair and robust training. Her works have been presented at the top machine learning conferences ICML, ICLR, and NeurIPS among others. She also co-presented a tutorial on Trustworthy AI at the top data mining conference ACM SIGKDD. She is currently interning at the NVIDIA Research AI Algorithms Group developing large-scale real-world fair AI frameworks.
The list of fellowship recipients and the interview videos are displayed on the Microsoft webpage and Youtube.
The list of recipients: https://www.microsoft.com/en-us/research/academic-program/phd-fellowship/2022-recipients/
Interview (Global): https://www.youtube.com/watch?v=T4Q-XwOOoJc
Interview (Asia): https://www.youtube.com/watch?v=qwq3R1XU8UE
[Highlighted research achievements by Yuji Roh: Fair batch selection framework]
[Highlighted research achievements by Yuji Roh: Fair and robust training framework]
2022.10.28 View 8614 -
Anonymous Donor Makes a Gift of Property Valued at 30 Billion KRW
The KAIST Development Foundation announced on May 9 that an anonymous donor in his 50s made a gift of real estate valued at 30 billion KRW. This is the first donation from an anonymous benefactor on such a grand scale. The benefactor expressed his wishes to fund scholarships for students in need and R&D for medical and bio sciences.
According to the Development Foundation official, the benefactor is reported to have said that he felt burdened that he earned much more than he needed and was looking for the right way to share his assets. The benefactor refused to hold an official donation ceremony and meeting with high-level university administrators.
The donor believes that KAIST is filled with young and dynamic energy, saying, “I would like to help KAIST move forward and create breakthroughs that will benefit the nation as well as all humanity.”
Before making up his mind to give his asset to KAIST, he had planned to establish his own social foundation but he changed his mind. “I decided that an investment in education would be the best investment,” he said. He explained that he was inspired by his KAIST graduate friend who is running a company. He was deeply motivated to help KAIST after witnessing the KAIST graduate’s passion for conducting his business.
After receiving the gift, KAIST President Kwang Hyung Lee was thankful for the full support and trust of the benefactor. “We will spare no effort to foster next-generation talents and advance science and technology in the field of biomedicine.”
2022.05.11 View 4240 -
Nanoscale Self-Assembling Salt-Crystal ‘Origami’ Balls Envelop Liquids
Mechanical engineers have devised a ‘crystal capillary origami’ technique where salt crystals spontaneously encapsulate liquid droplets
Researchers have developed a technique whereby they can spontaneously encapsulate microscopic droplets of water and oil emulsion in a tiny sphere made of salt crystals—sort of like a minute, self-constructing origami soccer ball filled with liquid. The process, which they are calling ‘crystal capillary origami,’ could be used in a range of fields from more precise drug delivery to nanoscale medical devices.The technique is described in a paper appearing in the journal Nanoscale on September 21.
Capillary action, or ‘capillarity,’ will be familiar to most people as the way that water or other liquids can move up narrow tubes or other porous materials seemingly in defiance of gravity (for example within the vascular systems of plants, or even more simply, the drawing up of paint between the hairs of a paintbrush). This effect is due to the forces of cohesion (the tendency of a liquid’s molecules to stick together), which results in surface tension, and adhesion (their tendency to stick to the surface of other substances). The strength of the capillarity depends on the chemistry of the liquid, the chemistry of the porous material, and on the other forces acting on them both. For example, a liquid with lower surface tension than water would not be able to hold up a water strider insect.
Less well known is a related phenomenon, elasto-capillarity, that takes advantage of the relationship between capillarity and the elasticity of a very tiny flat sheet of a solid material. In certain circumstances, the capillary forces can overcome the elastic bending resistance of the sheet.
This relationship can be exploited to create ‘capillary origami,’ or three-dimensional structures. When a liquid droplet is placed on the flat sheet, the latter can spontaneously encapsulate the former due to surface tension. Capillary origami can take on other forms including wrinkling, buckling, or self-folding into other shapes. The specific geometrical shape that the 3D capillary origami structure ends up taking is determined by both the chemistry of the flat sheet and that of the liquid, and by carefully designing the shape and size of the sheet.
There is one big problem with these small devices, however. “These conventional self-assembled origami structures cannot be completely spherical and will always have discontinuous boundaries, or what you might call ‘edges,’ as a result of the original two-dimensional shape of the sheet,” said Kwangseok Park, a lead researcher on the project. He added, “These edges could turn out to be future defects with the potential for failure in the face of increased stress.” Non-spherical particles are also known to be more disadvantageous than spherical particles in terms of cellular uptake.
Professor Hyoungsoo Kim from the Department of Mechanical Engineering explained, “This is why researchers have long been on the hunt for substances that could produce a fully spherical capillary origami structure.”
The authors of the study have demonstrated such an origami sphere for the first time. They showed how instead of a flat sheet, the growth of salt-crystals can perform capillary origami action in a similar manner. What they call ‘crystal capillary origami’ spontaneously constructs a smooth spherical shell capsule from these same surface tension effects, but now the spontaneous encapsulation of a liquid is determined by the elasto-capillary conditions of growing crystals.
Here, the term ‘salt’ refers to a compound of one positively charged ion and another negatively charged. Table salt, or sodium chloride, is just one example of a salt. The researchers used four other salts: calcium propionate, sodium salicylate, calcium nitrate tetrahydrate, and sodium bicarbonate to envelop a water-oil emulsion. Normally, a salt such as sodium chloride has a cubical crystal structure, but these four salts form plate-like structures as crystallites or ‘grains’ (the microscopic shape that forms when a crystal first starts to grow) instead. These plates then self-assemble into perfect spheres.
Using scanning electron microscopy and X-ray diffraction analysis, they investigated the mechanism of such formation and concluded that it was ‘Laplace pressure’ that drives the crystallite plates to cover the emulsion surface. Laplace pressure describes the pressure difference between the interior and exterior of a curved surface caused by the surface tension at the interface between the two substances, in this case between the salt water and the oil.
The researchers hope that these self-assembling nanostructures can be used for encapsulation applications in a range of sectors, from the food industry and cosmetics to drug delivery and even tiny medical devices.
-Publication
Kwangseok Park, Hyoungsoo Kim “Crystal capillary origami capsule with self-assembled nanostructure,” Nanoscale, 13(35), 14656-14665 (DOI: 10.1039/d1nr02456f)
-Profile
Professor Hyoungsoo Kim
Fluid and Interface Laboratory
http://fil.kaist.ac.kr
Department of Mechanical Engineering
KAIST
2021.11.04 View 7418 -
Wearable Device to Monitor Sweat in Real Time
An on-skin platform for the wireless monitoring of flow rate, cumulative loss, and temperature of sweat in real time
An electronic patch can monitor your sweating and check your health status. Even more, the soft microfluidic device that adheres to the surface of the skin, captures, stores, and performs biomarker analysis of sweat as it is released through the eccrine glands.
This wearable and wireless electronic device developed by Professor Kyeongha Kwon and her collaborators is a digital and wireless platform that could help track the so-called ‘filling process’ of sweat without having to visually examine the device. The platform was integrated with microfluidic systems to analyze the sweat’s components.
To monitor the sweat release rate in real time, the researchers created a ‘thermal flow sensing module.’ They designed a sophisticated microfluidic channel to allow the collected sweat to flow through a narrow passage and a heat source was placed on the outer surface of the channel to induce a heat exchange between the sweat and the heated channel.
As a result, the researchers could develop a wireless electronic patch that can measure the temperature difference in a specific location upstream and downstream of the heat source with an electronic circuit and convert it into a digital signal to measure the sweat release rate in real time. The patch accurately measured the perspiration rate in the range of 0-5 microliters/minute (μl/min), which was considered physiologically significant. The sensor can measure the flow of sweat directly and then use the information it collected to quantify total sweat loss. Moreover, the device features advanced microfluidic systems and colorimetric chemical reagents to gather pH measurements and determine the concentration of chloride, creatinine, and glucose in a user's sweat.
Professor Kwon said that these indicators could be used to diagnose various diseases related with sweating such as cystic fibrosis, diabetes, kidney dysfunction, and metabolic alkalosis. “As the sweat flowing in the microfluidic channel is completely separated from the electronic circuit, the new patch overcame the shortcomings of existing flow rate measuring devices, which were vulnerable to corrosion and aging,” she explained.
The patch can be easily attached to the skin with flexible circuit board printing technology and silicone sealing technology. It has an additional sensor that detects changes in skin temperature. Using a smartphone app, a user can check the data measured by the wearable patch in real time.
Professor Kwon added, “This patch can be widely used for personal hydration strategies, the detection of dehydration symptoms, and other health management purposes. It can also be used in a systematic drug delivery system, such as for measuring the blood flow rate in blood vessels near the skin’s surface or measuring a drug’s release rate in real time to calculate the exact dosage.”
-PublicationKyeongha Kwon, Jong Uk Kim, John A. Rogers, et al. “An on-skin platform for wireless monitoring of flow rate, cumulative loss and temperature of sweat in real time.” Nature Electronics (doi.org/10.1038/s41928-021-00556-2)
-ProfileProfessor Kyeongha KwonSchool of Electrical EngineeringKAIST
2021.06.25 View 8067 -
‘Game&Art: Auguries of Fantasy’ Features Future of the Metaverse
‘Game & Art: Auguries of Fantasy,’ a special exhibition combining art and technology will feature the new future of metaverse fantasy. The show will be hosted at the Daejeon Creative Center at the Daejeon Museum of Art through September 5.
This show exhibits a combination of science and technology with culture and arts, and introduces young artists whose creativity will lead to new opportunities in games and art. The Graduate School of Culture Technology was designated as a leading culture content academy in 2020 by the Ministry of Culture, Sports & Tourism and the Korea Creative Content Agency for fostering the R&D workforce in creative culture technology.
NCsoft sponsored the show and also participated as an artist. It combined its game-composing elements and technologies with other genres, including data for game construction, scenarios for forming a worldview, and game art and sound. All of the contents can be experienced online in a virtual space as well as offline, and can be easily accessed through personal devices.
Characterized by the themes ‘timeless’ and ‘spaceless’ which connect the past, present, and future, and space created in the digital world. The exhibition gives audience members an opportunity to experience freedom beyond the constraints of time and space under the theme of a fantasy reality created by games and art.
"Computer games, which began in the 1980s, have become cultural content that spans generations, and games are now the fusion field for leading-edge technologies including computer graphics, sound, human-computer interactions, big data, and AI. They are also the best platform for artistic creativity by adding human imagination to technology," said Professor Joo-Han Nam from the Graduate School of Culture Technology, who led the project.
"Our artists wanted to convey various messages to our society through works that connect the past, present, and future through games."
Ju-young Oh's "Unexpected Scenery V2" and "Hope for Rats V2" display game-type media work that raises issues surrounding technology, such as the lack of understanding behind various scientific achievements, the history of accidental achievements, and the side effects of new conveniences.
Tae-Wan Kim, in his work themed ‘healing’ combined the real-time movement of particles which follows the movements of people recorded as digital data. Metadata is collected by sensors in the exhibition space, and floating particle forms are evolved into abstract graphic designs according to audio-visual responses.
Meanwhile, ‘SOS’ is a collaboration work from six KAIST researchers (In-Hwa Yeom, Seung-Eon Lee, Seong-Jin Jeon, Jin-Seok Hong, Hyung-Seok Yoon, and Sang-Min Lee). SOS is based on diverse perspectives embracing phenomena surrounding contemporary natural resources. Audience members follow a gamified path between the various media-elements composing the art’s environment. Through this process, the audience can experience various emotions such as curiosity, suspicion, and recovery.
‘Diversity’ by Sung-Hyun Kim uses devices that recognize the movements of hands and fingers to provide experiences exploring the latent space of game play images learned by deep neural networks. Image volumes generated by neural networks are visualized through physics-based, three-dimensional, volume-rendering algorithms, and a series of processes were implemented based on the self-written code.
2021.06.21 View 7208 -
Krafton Matches Alumni Donations to Raise 11 Billion KRW for SW Developers
Alumni donations from the School of Computing, including Baemin and Devsisters, continue to grow
Alumni from the KAIST School of Computing who are current and former developers at the leading game company Krafton, established by KAIST alumna Byung-Gyu Chang, made an agreement to help raise 11 billion KRW during a ceremony on June 4. The funds raised in the matching grant will be used to nurture software developers.
Krafton Chairman Chang donated 10 billion won last January. His donation inspired other alumni working at Krafton as well as its former developers. Eleven KAIST alumni raised 5.5 billion KRW in two months and discussed the matching grant idea with Chairman Chang.
The Krafton matching grant ceremony was attended by President Kwang Hyung Lee, Provost and Executive Vice President Seung Seob Lee, Vice President for Research Sang Yup Lee, Head of the School of Computing Sukyoung Ryu, Krafton Chairman Byung-gyu Chang, and KAIST alumnus from Krafton Seung-woo Shin. Other alumni donors including Krafton CEO Changhan Kim joined the ceremony online.
Krafton CEO Changhan Kim said, “Just as our alma mater played an important role in growing our company, we hope that our donation could help support good developers. This will not only help our company, but advance our industry.”
KAIST and Krafton also signed a business agreement to foster competitive developers. Krafton said it plans to continue giving back to society through the matching grant program.
Head of the School of Computing Sukyoung Ryu thanked Chairman Chang and alumni who took part in the fund raising, saying, “To take the lead in rapidly changing computer technology, we desperately need more top students, faculty members, and facilities. We need more resources and infrastructure for interdisciplinary research.”
The School of Computing has seen significant growth recently. Its number of undergraduate students has increased from 450 in 2016 to more than 900 in 2021. With this donation, the school will expand its current buildings to provide diverse educational and mentoring programs in more spacious facilities.
Seung-woo Shin (Class of ’92), who joined Krafton’s matching grant, said, “I have always been thankful for the people I met and what I learned at KAIST. I was moved by the idea of giving back to the school.”
Seong-jung Ryu (Class of ’97) said, “This donation reminded me of the good times I had back then. I thought it was crucial that the department’s facilities be extended, so I naturally wanted to take part.”
Alumni donations, especially from the School of Computing, have also continued to grow more recently. Woowa Brothers Corp. CEO Beom-Jun Kim, the developer of the meal delivery app ‘Baemin’ donated 100 million KRW in April. Baemin became the most used app in the country during the COVID-19 pandemic.
He explained, “I have been thinking about ways to give something to the next generation, rather than ‘paying back’ those who helped me in the past.”
Encouraged by Baemin’s donation, alumni couple Ha-Yeon Seo and Dong-Hun Hahn from the School of Computing and eleven alumni engineers working at Devsisters Corp. also followed suit.
2021.06.09 View 8279 -
Education, a Silver Lining in the Dark COVID-19 Cloud
If there is a silver lining behind the COVID-19 pandemic clouds engulfing the world in darkness, it would be ‘education’. The disruption caused by the pandemic has reminded us of the skills that students need in this unpredictable world and raised public awareness of guaranteeing continuous, fair, and quality learning opportunities. Educational innovation can become a positive and powerful catalyst to transform the world for a better future in the post-COVID era.
According to the speakers at the virtual forum co-hosted by the Global Strategy Institute (GSI) and Korea Policy Center for the Fourth Industrial Revolution (KPC4IR) at KAIST on June 24, the recent transition to remote education amplifies the existing socio-economic disparities between the haves and the have-nots, and narrowing the digital divide is the most urgent challenge that should be addressed in this ever-evolving technology-dominating era. They also called for students to be resilient despite the numerous uncertainties ahead of them and prepare new skill sets to better adjust to new environments.
KAIST launched the GSI as its think tank in February of this year. The GSI aims to identify global issues proactively and help make breakthroughs well aligned with solid science and technology-based policies. The second forum of the KAIST GSI, following its inaugural forum in April, was held under the theme “Envisioning the Future of Education for a Non-Contact Society in the Post-Coronavirus Era”.
In his opening remarks, KAIST President Sung-Chul Shin stressed that “distance teaching and learning will eventually become integral components of our future education system”. He then called for close collaboration between the public and private sectors to better shape the future of digital education. President Shin said that global cooperation is also needed to continue offering inclusive, quality education that can equally benefit every student around the world. “We should never let a crisis go to waste, and the COVID-19 pandemic is no exception,” he added.
CEO of Minerva Schools Ben Nelson described the current coronavirus crisis as “an earthquake happening deep down on the ocean floor – we don’t feel it, but it can cause a devastating tsunami.” He continued, “Online learning can totally change the current education system forever.”
Saying that blended education, which combines online and offline classes, will be the new norm in the post-coronavirus era, Coursera CEO Jeff Maggioncalda anticipates that institutions will have to offer more and more online courses and credentials, and should at the same time prepare to drive down the cost of education as students expect to pay much less in tuition and fees for online learning options. “With the economy slumping and unemployment soaring, job-relevant education will also be a must,” Maggioncalda said.
National University of Singapore President Tan Eng Chye further pointed out that future education systems should prepare students to be creative lifelong learners. President Tan encouraged students to be able to integrate knowledge and technical skills from multiple disciplines for complex problem solving, and be adaptable and resilient with bigger appetites for risks and a higher tolerance for failures. He also mentioned digital competency, empathy, and social responsibility as virtues that students in the post-coronavirus era should possess.
Rebecca Winthrop, Co-Director of the Center for Universal Education at the Brookings Institution, raised concerns over the ever-growing digital disparities caused by the recent shift to online teaching and learning, claiming that insufficient infrastructures for low-income families in developing nations are already causing added educational disparities and provoking the inequity issue around the world. “New approaches to leapfrog inequality and provide quality education equally through faster and more effective means should be studied,” she said.
In response to this, Vice President of Microsoft Anthony Salcito introduced the Microsoft Education Transformation Framework, which provides practical advice to develop strategies for digital education transformation with a holistic, long-term view implemented in discrete phases that the global community can begin today. The Framework reportedly shows how emerging technologies, such as artificial intelligence, support new approaches to building efficient and effective physical and digital infrastructure, modernizing teaching and learning, empowering research, and managing student success.
The GSI will host two more forums in September and November.
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2020.06.24 View 11875 -
Long Economic Depressions and Disparities Loom in the Wake of the COVID-19
"Global Cooperation for Managing Data Key to Mitigating the Impacts Around the World"
<Full recorded video of the GSI-IF2020>
The COVID-19 pandemic will lead to long economic depressions around the entire world. Experts predicted that the prevalent inequities among the countries, regions, and individuals will aggravate the economic crisis. However, crises always come with new opportunities and international cooperation and solidarity will help creating a new normal in the post-coronavirus era.
In a very basic but urgent step, global cooperation for managing data is the key to respond to COVID-19 since medicine and healthcare are intertwined with data science, said experts during an online international forum hosted by the Global Strategy Institute at KAIST on April 22.
KAIST launched its think-tank, the Global Strategy Institute (GSI), in February. The GSI aims to identify global issues proactively and help make breakthroughs well aligned with solid science-based policies.
The inaugural forum of the GSI focused on how the COVID-19 pandemic would impact socio-economic, scientific, and political landscapes, under the theme “Global Cooperation in the Coronavirus Era.”
In his opening remarks, KAIST President Sung-Chul Shin stressed that future global governance will be dominated by the power of science and technology. “If we can implement efficient policies together with troubleshooting technology for responding to future crises, we will emerge stronger than before,” he said.
President Shin said ‘the Korean model’, which is being recognized as a shining example for dealing with the pandemic, is the result of collaborations combining the creativity of the private sector, the public sector’s strong infrastructure, and the full support of the citizens. He added, “Without the technological prowess coming from the competent R&D power of Korea, we could not achieve these impressive results.”
“Creative collaboration among the private and public sectors, along with research universities from around the world, will help shore up global resilience against the epidemic. We should work together to build a world of growing prosperity,” President Shin said.
Prime Minister Sye-Kyun Chung, who is in charge of the Central Disaster and Safety Countermeasures Headquarters in Korea, stressed global solidarity in his welcoming remarks, saying that “We need to share information and rely on the strength of our connections, rather than retreating into nationalistic isolation.”
Peter Lee, Vice President of the Microsoft Healthcare, pointed out in his welcoming remarks three critical sectors for global cooperation: medicine and healthcare, public health and prevention, and life and the economy. He emphasized the rule of thumb for managing data, saying that data in these fields should be open, standardized, and shared among countries to combat this global pandemic.
During a keynote session, Director General of the International Vaccine Institute (IVI) Jerome Kim described the challenges that go along with developing a vaccine. Dr. Kim said that only 7% of vaccine candidates go through the clinical trial stages, and it will take five to 10 years to completely prove a new vaccine’s safety after completing three stages of clinical tests.
“It’s very challenging to develop the vaccine for COVID-19 within 12 to 15 months,” said Dr. Kim. He added that 78 out of 115 candidates are currently undergoing clinical trials around the world.
There are five groups, including Moderna, Inovio, Jenner Institute, CanSino, and the Beijing Institute of Biological Products, who are doing clinical trials in phases 1 and 2. “Given the fact that COVID-19 is a totally new type of virus, various stakeholders’ participation, such as the National Immunization Technical Advisory Groups, the WHO, and UNICEF, is needed to work together to benefit the entire world,” he pointed out.
Professor Edward Yoonjae Choi from the Graduate School of AI at KAIST shared how AI and data sciences are being utilized to interpret the major trends of the epidemic. His group mainly focuses on deep learning to model electronic health records (EHR) for disease predictions. Professor Choi said AI and machine learning would be crucial solutions and collaborative research projects will surely accelerate how quickly we can overcome the pandemic.
In addition, Dr. Kijung Shin’s group is interpreting the SIR (Susceptible, Infected, and Recovered) model in Korea to predict the number of infections and when people were infected. However, researchers noticed that they could not see the typical modeling in Korea for predicting the number of infections since the model disregarded the new variable of humans’ efforts to stop the spread the virus.
According to research by Professor Steven Whang’s group on social distancing and face mask distribution among vulnerable age groups, people in their 20s, 60s, and 70s followed the social distancing guidelines the most strictly. The research team analyzed the data provided by SK Telecom in the Gangnam district of Seoul. The data provided on people in their 70s, a group that accounted for half of all fatalities, showed that masks were generally well distributed nationwide.
Dr. Alexandros Papaspyrids, Tertiary Education Industry Director of the Asia region of Microsoft, said that despite all the disadvantages and problems related to remote education, we shouldn’t expect to return to the days before the COVID-19 any time soon. “We should accept the new normal and explore new opportunities in the new educational environment,” he said.
Hongtaek Yong, Deputy Minister at the Office of R&D Policy at the Ministry of Science and ICT presented the Korean government’s disease prevention and response policy and how they tried to mitigate the economic and social impact.
He stressed the government’s fast testing, tracing, and openness for successfully flattening the curve, adding that the government used an ICT-based approach in all aspects of their response. From early this year when the first patient was reported, the government aggressively encouraged the biotech industry to develop diagnostic kits and novel therapeutic medications.
As a result, five companies were able to produce genetic diagnostic reagents through the emergency approval. More notably, four of them are conducting massive R&D projects sponsored by the government and this is the result of the government’s continuous investment in R&D. Korea is the leader in R&D investment among the OECD countries.
According to Yong, the government’s big data project that was launched in 2017 continuously traces the trends of epidemics in Korea. The epidemiological studies based on the paths taken by suspected patients using credit card transaction made the difference in predicting the spread of the coronavirus and implementing countermeasures. The data has been provided to the Korea’s Center for Disease Control (CDC).
“In addition to the epidemics, we have so many other pending issues arising from digital and social equities, un-contact services, and job security. We are very open to collaborate and cooperate with other countries to deal with this global crisis,” Yong said.
During the subsequent panel discussions, David Dollar, a senior fellow at the Brookings Institution, said, “The global economy in the coronavirus era will not have a rapid V-shaped recovery, but rather will fall into a long depression for at least two years.” He pointed out that if countries practice protectionism like they did during the Great Depression, the recession will be even worse. Hence, he urged the international community, especially developed nations, to avoid protectionism, consider the economic difficulties of developing countries, and provide them with financial support.
Co-Director of the Center for Universal Education at the Brookings Institution Rebecca Winthrop raised concerns over the recent shift to online teaching and learning, claiming that insufficient infrastructures in low-income families in developing nations are already causing added educational disparities and provoking the inequity issue around the world. “The ways to provide quality education equally through faster and more effective means should be studied,” she said.
Professor Joungho Kim, the director of the KAIST GSI and the forum’s organizer, concluded the event by saying that this forum will be a valuable resource for everyone who is providing assistance to those in need, both during and after the COVID-19 pandemic.
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2020.04.22 View 18307 -
Wearable Strain Sensor Using Light Transmittance Helps Measure Physical Signals Better
KAIST researchers have developed a novel wearable strain sensor based on the modulation of optical transmittance of a carbon nanotube (CNT)-embedded elastomer. The sensor is capable of sensitive, stable, and continuous measurement of physical signals. This technology, featured in the March 4th issue of ACS Applied Materials & Interfaces as a front cover article, shows great potential for the detection of subtle human motions and the real-time monitoring of body postures for healthcare applications.
A wearable strain sensor must have high sensitivity, flexibility, and stretchability, as well as low cost. Those used especially for health monitoring should also be tied to long-term solid performance, and be environmentally stable. Various stretchable strain sensors based on piezo-resistive and capacitive principles have been developed to meet all these requirements.
Conventional piezo-resistive strain sensors using functional nanomaterials, including CNTs as the most common example, have shown high sensitivity and great sensing performance. However, they suffer from poor long-term stability and linearity, as well as considerable signal hysteresis. As an alternative, piezo-capacitive strain sensors with better stability, lower hysteresis, and higher stretchability have been suggested. But due to the fact that piezo-capacitive strain sensors exhibit limited sensitivity and strong electromagnetic interference caused by the conductive objects in the surrounding environment, these conventional stretchable strain sensors are still facing limitations that are yet to be resolved.
A KAIST research team led by Professor Inkyu Park from the Department of Mechanical Engineering suggested that an optical-type stretchable strain sensor can be a good alternative to resolve the limitations of conventional piezo-resistive and piezo-capacitive strain sensors, because they have high stability and are less affected by environmental disturbances. The team then introduced an optical wearable strain sensor based on the light transmittance changes of a CNT-embedded elastomer, which further addresses the low sensitivity problem of conventional optical stretchable strain sensors.
In order to achieve a large dynamic range for the sensor, Professor Park and his researchers chose Ecoflex as an elastomeric substrate with good mechanical durability, flexibility, and attachability on human skin, and the new optical wearable strain sensor developed by the research group actually shows a wide dynamic range of 0 to 400%.
In addition, the researchers propagated the microcracks under tensile strain within the film of multi-walled CNTs embedded in the Ecoflex substrate, changing the optical transmittance of the film. By doing so, it was possible for them to develop a wearable strain sensor having a sensitivity 10 times higher than conventional optical stretchable strain sensors.
The proposed sensor has also passed the durability test with excellent results. The sensor’s response after 13,000 sets of cyclic loading was stable without any noticeable drift. This suggests that the sensor response can be used without degradation, even if the sensor is repeatedly used for a long time and in various environmental conditions.
Using the developed sensor, the research team could measure the finger bending motion and used it for robot control. They also developed a three-axes sensor array for body posture monitoring. The sensor was able to monitor human motions with small strains such as a pulse near the carotid artery and muscle movement around the mouth during pronunciation.
Professor Park said, “In this study, our group developed a new wearable strain sensor platform that overcomes many limitations of previously developed resistive, capacitive, and optical-type stretchable strain sensors. Our sensor could be widely used in a variety of fields including soft robotics, wearable electronics, electronic skin, healthcare, and even entertainment.”
This work was supported by the National Research Foundation (NRF) of Korea.
Publication:
Jimin Gu, Donguk Kwon, Junseong Ahn, and Inkyu Park. (2020) “Wearable Strain sensors Using Light Transmittance Change of Carbon Nanotube-Embedded Elastomers with Microcracks” ACS Applied Materials & Interfaces. Volume 12. Issue 9. Available online at https://doi.org/10.1021/acsami.9b18069
Profile:
Inkyu Park
Professor
inkyu@kaist.ac.kr
http://mintlab1.kaist.ac.kr
Micro/Nano Transducers Laboratory (MINT Lab)
Department of Mechanical Engineering (ME)Korea Advanced Institute of Science and Technology (KAIST)
Profile:
Jimin Gu
Ph.D. Candidate
mint9411@kaist.ac.kr
http://mintlab1.kaist.ac.kr
MINT Lab
KAIST ME
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2020.03.20 View 15621