AI
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Chairman Soo-Young Lee Named Among the Heroes of Philanthropy in Asia
Chairman Soo-Young Lee from the KAIST Development Foundation was named one of 15 philanthropists who made the biggest donations in the Asia-Pacific region by Forbes Asia on November 11.
The annual Heroes of Philanthropy list features the 15 the most generous individual philanthropists who are donating from their personal fortunes, not through companies. This year, the biggest philanthropies donated to make a difference in wide arrays of sectors such as Covid-19 relief to education and the arts.
Chairman Lee donated totaling 68 billion KRW to KAIST in July. Her donation marked the largest donation KAIST has ever received. She is one of two Korean philanthropists that Forbes selected. Honorary Chairman of GS Caltex Dong-Soo Huh also made the list.
Her donation will establish the Soo-Young Lee Science Education Foundation to support ‘the Singularity Professor program’ that KAIST is launching. She expressed confidence that her donation will fund KAIST researchers to make breakthroughs that will lead to a Nobel Prize.
“Without the advancement of science and technology, Korea cannot be one of the top countries in the world. I believe KAIST can make it with our all supports,” she frequently said when asked why she selected KAIST for her donation.
Chairman Lee previously made generous donations in 2012 and 2016 and said she plans to make another gift to KAIST in the very near future.
2020.11.13 View 6454 -
KAIST Receives $57 Million Donation to Enhance Research
The largest amount since the opening of KAIST will fund ‘Singularity Professors’
KAIST Development Foundation Chairman Soo-Young Lee made a gift of real estate estimated at approximately $57 million on July 23. This is the largest donation KAIST has received since it was founded in 1971.
The fund will establish the “Soo-Young Lee Science Education Foundation” and the proceeds of the foundation will go to the “Singularity Professors” as necessary resources to help make discoveries and design new approaches to accelerate breakthroughs.
“KAIST should be the institute that will produce first Korean Nobel laureate in the field of science. I hope this fund will be utilized to enable Korea to stand out in this challenging time by accomplishing breakthroughs nobody has never imagined,” said Chairman Lee during the donation ceremony at KAIST’s campus in Daejeon.
This is Chairman Lee’s third donation following the $6.7 million donation in 2012 and the $830,000 donation in 2016. Chairman Lee began her career as a journalist in 1963. In 1981, she started her own business by launching Kwangwon Ranch and became a successful businesswoman. In 1988, Chairman Lee established the real estate company Kwangwon Industries. After receiving an honorary doctorate from KAIST in 2012, she has served as the chairman of the KAIST Development Foundation from 2013. Chairman Lee expressed her intention to make another donation to KAIST in the near future during the news conference.
“People matter most for advancing the world. KAIST has a very distinct mission to foster the brightest minds and will drive the nation to move forward. I have worked with KAIST for quite long time so that I have a strong belief that KAIST is the one that will not only make contributions to Korea but also to all humanity,” she explained.
“For example, about one-fourth of the R&D manpower at Samsung Electronics is from KAIST. In 2019, Samsung Electronics recorded a revenue of approximately $206 billion which accounted for about 16% of national GDP. KAIST is the one that fosters global talents who are working at global company such as Samsung and many others.”
KAIST President Sung-Chul Shin also expressed his deep respect for Chairman Lee’s decision, saying that the entire KAIST community will make every effort to keep up Chairman Lee’s noble idea encouraging KAIST to push forward and help realize KAIST’s role and mission.
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2020.07.23 View 8701 -
COVID-19 Update: Fall Semester to Continue Offering Classes Online
KAIST announced that the university would continue online classes through the fall semester. However, the university will conduct additional in-person classes for upper-level undergraduate lab classes and some graduate courses where on-site interaction was deemed to be highly necessary. Some 600-level graduate courses at the Daejeon campus and graduate courses at the Seoul campus will carry out both in-person and online classes. The fall semester will start from August 31.
Provost and Executive Vice President Kwang Hyung Lee announced the fall semester plan in his letter to the entire student body on July 9. He said that the university decided to continue with online classes in consideration of the safety of KAIST community members and the current status of the COVID-19 spread. However, he said the new plan will help students choose class options between in-person and online classes.
“Although the number of classes with two versions is limited, we believe this will help many students continue learning without the sustained face-to-face contact that is inherent in residential education,” Provost Lee said.
In-person classes conducted in the fall semester will also be provided online for students who are not available for in-person classes. Students may choose the type of the classes they prefer according to their situation, among only the courses that will offer two versions. Professors will decide if they will conduct two versions of their classes. The Office of Academic Affairs is collecting the professors’ applications for conducting both versions until July 24.
KAIST offered real-time online classes and pre-recorded KLMS (KAIST Learning Management System) classes during the spring semester with a very limited number of in-person lab classes for graduate courses and these two versions of online class will continue for fall semester.
Provost Lee asked the students who will take the in-person classes to strictly observe all precaution measures as the university will do its best to abide by the government guidelines against the Covid-19 in preparation for the fall semester.
“We will continue to make appropriate and safe accommodations for them,” said Provost Lee.
Those who need to reside in on-campus dormitories are required to be approved for moving. The applications will open after all the in-person class schedules are fixed next month. However, students who were approved for staying in the dormitories last semester can move in without additional approval procedures for the fall semester.
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2020.07.10 View 8213 -
New Insights into How the Human Brain Solves Complex Decision-Making Problems
A new study on meta reinforcement learning algorithms helps us understand how the human brain learns to adapt to complexity and uncertainty when learning and making decisions. A research team, led by Professor Sang Wan Lee at KAIST jointly with John O’Doherty at Caltech, succeeded in discovering both a computational and neural mechanism for human meta reinforcement learning, opening up the possibility of porting key elements of human intelligence into artificial intelligence algorithms. This study provides a glimpse into how it might ultimately use computational models to reverse engineer human reinforcement learning.
This work was published on Dec 16, 2019 in the journal Nature Communications. The title of the paper is “Task complexity interacts with state-space uncertainty in the arbitration between model-based and model-free learning.”
Human reinforcement learning is an inherently complex and dynamic process, involving goal setting, strategy choice, action selection, strategy modification, cognitive resource allocation etc. This a very challenging problem for humans to solve owing to the rapidly changing and multifaced environment in which humans have to operate. To make matters worse, humans often need to often rapidly make important decisions even before getting the opportunity to collect a lot of information, unlike the case when using deep learning methods to model learning and decision-making in artificial intelligence applications.
In order to solve this problem, the research team used a technique called 'reinforcement learning theory-based experiment design' to optimize the three variables of the two-stage Markov decision task - goal, task complexity, and task uncertainty. This experimental design technique allowed the team not only to control confounding factors, but also to create a situation similar to that which occurs in actual human problem solving.
Secondly, the team used a technique called ‘model-based neuroimaging analysis.’ Based on the acquired behavior and fMRI data, more than 100 different types of meta reinforcement learning algorithms were pitted against each other to find a computational model that can explain both behavioral and neural data. Thirdly, for the sake of a more rigorous verification, the team applied an analytical method called ‘parameter recovery analysis,’ which involves high-precision behavioral profiling of both human subjects and computational models.
In this way, the team was able to accurately identify a computational model of meta reinforcement learning, ensuring not only that the model’s apparent behavior is similar to that of humans, but also that the model solves the problem in the same way as humans do.
The team found that people tended to increase planning-based reinforcement learning (called model-based control), in response to increasing task complexity. However, they resorted to a simpler, more resource efficient strategy called model-free control, when both uncertainty and task complexity were high. This suggests that both the task uncertainty and the task complexity interact during the meta control of reinforcement learning. Computational fMRI analyses revealed that task complexity interacts with neural representations of the reliability of the learning strategies in the inferior prefrontal cortex.
These findings significantly advance understanding of the nature of the computations being implemented in the inferior prefrontal cortex during meta reinforcement learning as well as providing insight into the more general question of how the brain resolves uncertainty and complexity in a dynamically changing environment. Identifying the key computational variables that drive prefrontal meta reinforcement learning, can also inform understanding of how this process might be vulnerable to break down in certain psychiatric disorders such as depression and OCD. Furthermore, gaining a computational understanding of how this process can sometimes lead to increased model-free control, can provide insights into how under some situations task performance might break down under conditions of high cognitive load.
Professor Lee said, “This study will be of enormous interest to researchers in both the artificial intelligence and human/computer interaction fields since this holds significant potential for applying core insights gleaned into how human intelligence works with AI algorithms.”
This work was funded by the National Institute on Drug Abuse, the National Research Foundation of Korea, the Ministry of Science and ICT, Samsung Research Funding Center of Samsung Electronics.
Figure 1 (modified from the figures of the original paper doi:10.1038/s41467-019-13632-1). Computations implemented in the inferior prefrontal cortex during meta reinforcement learning. (A) Computational model of human prefrontal meta reinforcement learning (left) and the brain areas whose neural activity patterns are explained by the latent variables of the model. (B) Examples of behavioral profiles. Shown on the left is choice bias for different goal types and on the right is choice optimality for task complexity and uncertainty. (C) Parameter recoverability analysis. Compared are the effect of task uncertainty (left) and task complexity (right) on choice optimality.
-Profile
Professor Sang Wan Lee
sangwan@kaist.ac.kr
Department of Bio and Brain Engineering
Director, KAIST Center for Neuroscience-inspired AI
KAIST Institute for Artificial Intelligence (http://aibrain.kaist.ac.kr)
KAIST Institute for Health, Science, and Technology
KAIST (https://www.kaist.ac.kr)
2020.01.31 View 5922 -
AI Graduate School to Take the Lead in Shaping the Future of AI
KAIST opened its AI Graduate School on August 26 with its first cohort of 22 Master’s and 10 PhD students for the 2019 fall semester. The new graduate school will provide students with a multidisciplinary curriculum incorporating the five key fields of healthcare, autonomous vehicles, manufacturing, security, and emerging technologies, and will offer 18 courses this semester.
KAIST was selected as one of the first three AI graduate schools that the Korean government will financially endorse to nurture top-tier AI specialists. The government will provide 9 billion KRW and KAIST will invest an additional 4.2 billion KRW in the school over the next five years.
KAIST aims to foster top-tiered AI engineers who will work for advancing emergent technologies for the Fourth Industrial Revolution. The school will produce original technologies by driving high-risk, innovative AI research projects and will be the main supplier of highly competent engineers who will lead the industry and advance the global market.
KAIST has a long history of AI research and has a top-level AI education and research infrastructure. In 1990, KAIST launched the first AI research center in Korea. Since then, KAIST has taken the lead in the field by making breakthroughs in intelligent sensing information systems and AI platforms. About 20 percent of the faculty members at KAIST, or about 120 professors, are conducting AI-related research while offering 136 AI-related courses.
The Dean of the AI Graduate School, Song Chong, said, “Our faculty members are the cream of the crop and are all in their early 40s. Although we started with only eight professors, we will employ 20 full-time professors by 2023 and will spare no effort to make the world’s best AI research hub and develop the brightest minds.”
Dean Chong said that three professors are already listed in the top ten when measured by the number of publications from the top two AI conferences, Neural Information Processing System (NIPS) and ICML (International Conference on Machine Learning). KAIST has several highly recognized faculty members who have published more than 10 NIPS/ICML papers over nine years, winning numerous awards including the ACM Sigmetrics Rising Star Award, Google AI Focused Research Award, and INFORMS Applied Probability Best Publication Award.
The number of students attempting to gain admission to the school is also very high. The admission office said that the percentage of applicants being offered admission stood at 9.1 percent. From next year, the school plans to increase the number of enrollments to 40 Master’s and 20 PhD students.
The school will also open the AI Graduate School Research Center in Songnam City next month and expand its collaboration with local companies in the Songnam and Pangyo region, both emerging techno and ICT valleys. With the placement of 60 research personnel in the center, the school plans to play a leading role in building the companies’ technical competitiveness.
The government’s keen interest was well highlighted with the attendance of many dignitaries including the Mayor of Daejeon City Tae-Jong Huh, Vice Minister of Science and ICT Won-Ki Min, and National Assemblyman Sang-Min Lee.
KAIST President Sung-Chul Shin stressed the importance of AI as a growth engine, saying, “AI will be a game changer and a key enabler of major industries. But the winner takes all in industry. Therefore, without producing the world’s top technology, we will not survive in the global market. To foster highly competitive specialists who will take the lead in this industry, we will educate students who can converge multiple disciplines and contribute to national growth and beyond in the years ahead.”
2019.08.27 View 6425 -
Enhanced Natural Gas Storage to Help Reduce Global Warming
< Professor Atilhan (left) and Professor Yavuz (right) >
Researchers have designed plastic-based materials that can store natural gas more effectively. These new materials can not only make large-scale, cost-effective, and safe natural gas storage possible, but further hold a strong promise for combating global warming.
Natural gas (predominantly methane) is a clean energy alternative. It is stored by compression, liquefaction, or adsorption. Among these, adsorbed natural gas (ANG) storage is a more efficient, cheaper, and safer alternative to conventional compressed natural gas (CNG) and liquefied natural gas (LNG) storage approaches that have drawbacks such as low storage efficiency, high costs, and safety concerns. However, developing adsorptive materials that can more fully exploit the advantages of ANG storage has remained a challenging task.
A KAIST research team led by Professor Cafer T. Yavuz from the Graduate School of Energy, Environment, Water, and Sustainability (EEWS), in collaboration with Professor Mert Atilhan’s group from Texas A&M University, synthesized 29 unique porous polymeric structures with inherent flexibility, and tested their methane gas uptake capacity at high pressures. These porous polymers had varying synthetic complexities, porosities, and morphologies, and the researchers subjected each porous polymer to pure methane gas under various conditions to study the ANG performances.
Of these 29 distinct chemical structures, COP-150 was particularly noteworthy as it achieved a high deliverable gravimetric methane working capacity when cycled between 5 and 100 bar at 273 K, which is 98% of the total uptake capacity. This result surpassed the target set by the United States Department of Energy (US DOE).
COP-150 is the first ever structure to fulfil both the gravimetric and volumetric requirements of the US DOE for successful vehicular use, and the total cost to produce the COP-150 adsorbent was only 1 USD per kilogram.
COP-150 can be produced using freely available and easily accessible plastic materials, and moreover, its synthesis takes place at room temperature, open to the air, and no previous purification of the chemicals is required. The pressure-triggered flexible structure of COP-150 is also advantageous in terms of the total working capacity of deliverable methane for real applications.
The research team believed that the increased pressure flexes the network structure of COP-150 showing “swelling” behavior, and suggested that the flexibility provides rapid desorption and thermal management, while the hydrophobicity and the nature of the covalently bonded framework allow these promising materials to tolerate harsh conditions.
This swelling mechanism of expansion-contraction solves two other major issues, the team noted. Firstly, when using adsorbents based on such a mechanism, unsafe pressure spikes that may occur due to temperature swings can be eliminated. In addition, contamination can also be minimized, since the adsorbent remains contracted when no gas is stored.
Professor Yavuz said, “We envision a whole host of new designs and mechanisms to be developed based on our concept. Since natural gas is a much cleaner fuel than coal and petroleum, new developments in this realm will help switching to the use of less polluting fuels.”
Professor Atilhan agreed the most important impact of their research is on the environment. “Using natural gas more than coal and petroleum will significantly reduce greenhouse gas emissions. We believe, one day, we might see vehicles equipped with our materials that are run by a cleaner natural gas fuel,” he added.
This study, reported in Nature Energy on July 8, was supported by National Research Foundation of Korea (NRF) grants ( NRF-2016R1A2B4011027, NRF-2017M3A7B4042140, and NRF-2017M3A7B4042235).
< Suggested chemical structure of COP-150 >
< Initial ingredients (left) and final product (right) of COP-150 synthesis >
< Comparison of highest reported volumetric working capacities >
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2019.08.09 View 26783 -
Real-Time Analysis of MOF Adsorption Behavior
Researchers have developed a technology to analyze the adsorption behavior of molecules in each individual pore of a metal organic framework (MOF). This system has large specific surface areas, allowing for the real-time observation of the adsorption process of an MOF, a new material effective for sorting carbon dioxide, hydrogen, and methane.
Accurate measurements and assessments of gas adsorption isotherms are important for characterizing porous materials and developing their applications. The existing technology is only able to measure the amount of gas molecules adsorbed to the material, without directly observing the adsorption behavior.
The research team led by Professor Jeung Ku Kang from the Graduate School of Energy, Environment, Water and Sustainability (EEWS) prescribed a real time gas adsorption crystallography system by integrating an existing X-ray diffraction (XRD) measurement device that can provide structural information and a gas adsorption measurement device.
Specifically, the system allowed the observation of a mesoporous MOF that has multiple pores rather than a single pore structure. The research team categorized the adsorption behaviors of MOF molecules by pore type, followed by observations and measurements, resulting in the identification of a stepwise adsorption process that was previously not possible to analyze.
Further, the team systematically and quantitatively analyzed how the pore structure and the type of adsorption molecule affect the adsorption behavior to suggest what type of MOF structure is appropriate as a storage material for each type of adsorption behavior.
Professor Kang said, “We quantitatively analyzed each pore molecule in real time to identify the effects of chemical and structural properties of pores on adsorption behavior.” He continued, “By understanding the real-time adsorption behavior of molecules at the level of the pores that form the material, rather than the whole material, we will be able to apply this technology to develop a new high-capacity storage material.”
This research was published in Nature Chemistry online on May 13, 2019 under the title ‘Isotherms of Individual Pores by Gas Adsorption Crystallography’.
(Figure. Schematic illustration of molecules adsorbed on metal organic frameworks with different pores of various structures, where the In-situ X-ray crystallography has been developed to classify each pore structure and analyze the position of the molecule to determine the amount of molecules adsorbed to each pore.)
2019.06.18 View 39057 -
5 Biomarkers for Overcoming Colorectal Cancer Drug Resistance Identified
< Professor Kwang-Hyun Cho's Team >
KAIST researchers have identified five biomarkers that will help them address resistance to cancer-targeting therapeutics. This new treatment strategy will bring us one step closer to precision medicine for patients who showed resistance.
Colorectal cancer is one of the most common types of cancer worldwide. The number of patients has surpassed 1 million, and its five-year survival rate significantly drops to about 20 percent when metastasized. In Korea, the surge of colorectal cancer has been the highest in the last 10 years due to increasing Westernized dietary patterns and obesity. It is expected that the number and mortality rates of colorectal cancer patients will increase sharply as the nation is rapidly facing an increase in its aging population.
Recently, anticancer agents targeting only specific molecules of colon cancer cells have been developed. Unlike conventional anticancer medications, these selectively treat only specific target factors, so they can significantly reduce some of the side-effects of anticancer therapy while enhancing drug efficacy.
Cetuximab is the most well-known FDA approved anticancer medication. It is a biomarker that predicts drug reactivity and utilizes the presence of the ‘KRAS’ gene mutation. Cetuximab is prescribed to patients who don’t carry the KRAS gene mutation.
However, even in patients without the KRAS gene mutation, the response rate of Cetuximab is only about fifty percent, and there is also resistance to drugs after targeted chemotherapy. Compared with conventional chemotherapy alone, the life expectancy only lasts five months on average.
In research featured in the FEBS Journal as the cover paper for the April 7 edition, the KAIST research team led by Professor Kwang-Hyun Cho at the Department of Bio and Brain Engineering presented five additional biomarkers that could increase Cetuximab responsiveness using systems biology approach that combines genomic data analysis, mathematical modeling, and cell experiments. The experimental inhibition of newly discovered biomarkers DUSP4, ETV5, GNB5, NT5E, and PHLDA1 in colorectal cancer cells has been shown to overcome Cetuximab resistance in KRAS-normal genes. The research team confirmed that when suppressing GNB5, one of the new biomarkers, it was shown to overcome resistance to Cetuximab regardless of having a mutation in the KRAS gene.
Professor Cho said, “There has not been an example of colorectal cancer treatment involving regulation of the GNB5 gene.” He continued, “Identifying the principle of drug resistance in cancer cells through systems biology and discovering new biomarkers that could be a new molecular target to overcome drug resistance suggest real potential to actualize precision medicine.”
This study was supported by the National Research Foundation of Korea (NRF) and funded by the Ministry of Science and ICT (2017R1A2A1A17069642 and 2015M3A9A7067220).
Image 1. The cover of FEBS Journal for April 2019
2019.05.27 View 59100 -
KAIST Unveils the Hidden Control Architecture of Brain Networks
(Professor Kwang-Hyun Cho and his team)
A KAIST research team identified the intrinsic control architecture of brain networks. The control properties will contribute to providing a fundamental basis for the exogenous control of brain networks and, therefore, has broad implications in cognitive and clinical neuroscience.
Although efficiency and robustness are often regarded as having a trade-off relationship, the human brain usually exhibits both attributes when it performs complex cognitive functions. Such optimality must be rooted in a specific coordinated control of interconnected brain regions, but the understanding of the intrinsic control architecture of brain networks is lacking.
Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering and his team investigated the intrinsic control architecture of brain networks. They employed an interdisciplinary approach that spans connectomics, neuroscience, control engineering, network science, and systems biology to examine the structural brain networks of various species and compared them with the control architecture of other biological networks, as well as man-made ones, such as social, infrastructural and technological networks.
In particular, the team reconstructed the structural brain networks of 100 healthy human adults by performing brain parcellation and tractography with structural and diffusion imaging data obtained from the Human Connectome Project database of the US National Institutes of Health.
The team developed a framework for analyzing the control architecture of brain networks based on the minimum dominating set (MDSet), which refers to a minimal subset of nodes (MD-nodes) that control the remaining nodes with a one-step direct interaction. MD-nodes play a crucial role in various complex networks including biomolecular networks, but they have not been investigated in brain networks.
By exploring and comparing the structural principles underlying the composition of MDSets of various complex networks, the team delineated their distinct control architectures. Interestingly, the team found that the proportion of MDSets in brain networks is remarkably small compared to those of other complex networks. This finding implies that brain networks may have been optimized for minimizing the cost required for controlling networks. Furthermore, the team found that the MDSets of brain networks are not solely determined by the degree of nodes, but rather strategically placed to form a particular control architecture.
Consequently, the team revealed the hidden control architecture of brain networks, namely, the distributed and overlapping control architecture that is distinct from other complex networks. The team found that such a particular control architecture brings about robustness against targeted attacks (i.e., preferential attacks on high-degree nodes) which might be a fundamental basis of robust brain functions against preferential damage of high-degree nodes (i.e., brain regions).
Moreover, the team found that the particular control architecture of brain networks also enables high efficiency in switching from one network state, defined by a set of node activities, to another – a capability that is crucial for traversing diverse cognitive states.
Professor Cho said, “This study is the first attempt to make a quantitative comparison between brain networks and other real-world complex networks. Understanding of intrinsic control architecture underlying brain networks may enable the development of optimal interventions for therapeutic purposes or cognitive enhancement.”
This research, led by Byeongwook Lee, Uiryong Kang and Hongjun Chang, was published in iScience (10.1016/j.isci.2019.02.017) on March 29, 2019.
Figure 1. Schematic of identification of control architecture of brain networks.
Figure 2. Identified control architectures of brain networks and other real-world complex networks.
2019.04.23 View 38378 -
KAIST-KU Joint Research Center for Smart Healthcare & Transportation
(President Shin shakes hands with KU acting Presidedent Arif Al Hammdi at the KAIST-KU Joint Research Center opening ceremony on April 8.)
KAIST opened the KAIST-Khalifa University Joint Research Center with Khalifa University on April 8. The opening ceremony was held at Khalifa University and was attended by President Sung-Chul Shin and Khalifa University Acting President Arif Al Hammadi.
The new research center reflects the evolution of the long-established partnership between the two institutions. The two universities have already made very close collaborations in research and education in the fields of nuclear and quantum engineering.
The launch of this center expanded their fields of collaboration to smart healthcare and smart transportation, key emerging sectors in the Fourth Industrial Revolution. President Shin signed an MOU with the UAE Minister of State for Advanced Science Sarah Amiri and Khalifa University to expand mutual collaboration in technology development and fostering human capital last year.
The center will conduct research and education on autonomous vehicles, infrastructure for autonomous vehicle operation, wireless charging for electric vehicles, and infrastructure for electric autonomous vehicles. As for smart healthcare, the center will focus on healthcare robotics as well as sensors and wearable devices for personal healthcare services.
President Shin, who accompanied a research team from the Graduate School of Green Transportation, said, “We are very delighted to enter into this expanded collaboration with KU. This partnership justifies our long-standing collaboration in the areas of emerging technologies in the Fourth Industrial Revolution while fostering human capital.”
KU Acting President Arif Al Hammadi added, “The outcome of these research projects will establish the status of both institutions as champions of the Fourth Industrial Revolution, bringing benefits to our communities. We believe the new research center will further consolidate our status as a globally active, research-intensive academic institution, developing international collaborations that benefit the community in general.”
2019.04.09 View 7954 -
Distinguished Alumni Awardees 2018
The KAIST Alumni Association (KAA) announced four recipients of the Distinguished Alumni Awards 2018. The Distinguished Alumni Awards recognize graduates who have achieved outstanding accomplishments in their professional and personal lives, and who have been an inspiration to fellow alumni and students in Korea and around the globe. Since the establishment of the award in 1992, a total of 99 alumni at home and abroad have been honored as recipients. The awards ceremony will take place during the New Year Alumni Reception on January 19 in Seoul.
Yeungnam University President Gil-Soo Sur (’75 MS, ’78 PhD in Chemistry) has demonstrated leadership in higher education and gained trust in academia for playing a leading role in educational innovation as well as serving as an educator who has fostered outstanding research talents for decades.
Professor Kwang-Soo Kim (’77 MS, ’79 PhD in Life Science) is the director of the Molecular Neurobiology Laboratory at McLean Hospital at Harvard Medical School. He has more than 20 years of experience investigating molecular and developmental neurobiology of the midbrain dopamine neuronal system. He has contributed to developing cell replacement therapy for Parkinson’s disease and has pioneered a generation of safe human-induced pluripotent stem cells through the direct delivery of reprogrammed proteins.
Young-Hwan Moon (’82 MS, ’87 PhD in Chemistry and Biomolecular Engineering) is the CEO of Coretech, which specializes in producing specialty gases and environmental catalysts required for chemical processes. He was recognized for enhancing national competence by securing competitive technology for manufacturing products.
Young-Hyun Jun (’84 MS, ’86 PhD in Electrical Engineering), the CEO of Samsung SDI, is a globally renowned expert in memory semiconductors. By bringing about innovative technology to enhance productivity and processes, he led Samsung Electronics to become the number one company at the global level in the field of semiconductors.
2019.01.14 View 4315 -
Ultrathin Digital Camera Inspired by Xenos Peckii Eyes
(Professor Ki-Hun Jeong from the Department of Bio and Brain Engineering)
The visual system of Xenos peckii, an endoparasite of paper wasps, demonstrates distinct benefits for high sensitivity and high resolution, differing from the compound eyes of most insects. Taking their unique features, a KAIST team developed an ultrathin digital camera that emulates the unique eyes of Xenos peckii.
The ultrathin digital camera offers a wide field of view and high resolution in a slimmer body compared to existing imaging systems. It is expected to support various applications, such as monitoring equipment, medical imaging devices, and mobile imaging systems.
Professor Ki-Hun Jeong from the Department of Bio and Brain Engineering and his team are known for mimicking biological visual organs. The team’s past research includes an LED lens based on the abdominal segments of fireflies and biologically inspired anti-reflective structures.
Recently, the demand for ultrathin digital cameras has increased, due to the miniaturization of electronic and optical devices. However, most camera modules use multiple lenses along the optical axis to compensate for optical aberrations, resulting in a larger volume as well as a thicker total track length of digital cameras. Resolution and sensitivity would be compromised if these modules were to be simply reduced in size and thickness.
To address this issue, the team have developed micro-optical components, inspired from the visual system of Xenos peckii, and combined them with a CMOS (complementary metal oxide semiconductor) image sensor to achieve an ultrathin digital camera.
This new camera, measuring less than 2mm in thickness, emulates the eyes of Xenos peckii by using dozens of microprism arrays and microlens arrays. A microprism and microlens pair form a channel and the light-absorbing medium between the channels reduces optical crosstalk. Each channel captures the partial image at slightly different orientation, and the retrieved partial images are combined into a single image, thereby ensuring a wide field of view and high resolution.
Professor Jeong said, “We have proposed a novel method of fabricating an ultrathin camera. As the first insect-inspired, ultrathin camera that integrates a microcamera on a conventional CMOS image sensor array, our study will have a significant impact in optics and related fields.”
This research, led by PhD candidates Dongmin Keum and Kyung-Won Jang, was published in Light: Science & Applications on October 24, 2018.
Figure 1. Natural Xenos peckii eye and the biological inspiration for the ultrathin digital camera (Light: Science & Applications 2018)
Figure 2. Optical images captured by the bioinspired ultrathin digital camera (Light: Science & Applications 2018)
2018.12.31 View 8545