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How Stingrays Became the Most Efficient Swimmers in Nature
Study shows the hydrodynamic benefits of protruding eyes and mouth in a self-propelled flexible stingray
With their compressed bodies and flexible pectoral fins, stingrays have evolved to become one of nature’s most efficient swimmers. Scientists have long wondered about the role played by their protruding eyes and mouths, which one might expect to be hydrodynamic disadvantages.
Professor Hyung Jin Sung and his colleagues have discovered how such features on simulated stingrays affect a range of forces involved in propulsion, such as pressure and vorticity. Despite what one might expect, their research team found these protruding features actually help streamline the stingrays.
‘The influence of the 3D protruding eyes and mouth on a self-propelled flexible stingray and its underlying hydrodynamic mechanism are not yet fully understood,” said Professor Sung. “In the present study, the hydrodynamic benefit of protruding eyes and mouth was explored for the first time, revealing their hydrodynamic role.”
To illustrate the complex interplay between hydrodynamic forces, the researchers set to work creating a computer model of a self-propelled flexible plate. They clamped the front end of the model and then forced it to mimic the up-and-down harmonic oscillations stingrays use to propel themselves.
To re-create the effect of the eyes and mouth on the surrounding water, the team simulated multiple rigid plates on the model. They compared this model to one without eyes and a mouth using a technique called the penalty immersed boundary method.
“Managing random fish swimming and isolating the desired purpose of the measurements from numerous factors was difficult,” Sung said. “To overcome these limitations, the penalty immersed boundary method was adopted to find the hydrodynamic benefits of the protruding eyes and mouth.”
The team discovered that the eyes and mouth generated a vortex of flow in the forward-backward , which increased negative pressure at the simulated animal’s front, and a side-to-side vortex that increased the pressure difference above and below the stingray. The result was increased thrust and accelerated cruising.
Further analysis showed that the eyes and mouth increased overall propulsion efficiency by more than 20.5% and 10.6%, respectively.
Researchers hope their work, driven by curiosity, further stokes interest in exploring fluid phenomena in nature. They are hoping to find ways to adapt this for next-generation water vehicle designs based more closely on marine animals.
This study was supported by the National Research Foundation of Korea and the State Scholar Fund from the China Scholarship Council.
-ProfileProfessor Hyung Jin SungDepartment of Mechanical EngineeringKAIST
-PublicationHyung Jin Sung, Qian Mao, Ziazhen Zhao, Yingzheng Liu, “Hydrodynamic benefits of protruding eyes and mouth in a self-propelled flexible stingray,” Aug.31, 2021, Physics of Fluids
(https://doi.org/10.1063/5.0061287)
-News release from the American Institute of Physics, Aug.31, 2021
2021.09.06 View 7040 -
Quantum Emitters: Beyond Crystal Clear to Single-Photon Pure
‘Nanoscale Focus Pinspot’ can quench only the background noise without changing the optical properties of the quantum emitter and the built-in photonic structure
Photons, fundamental particles of light, are carrying these words to your eyes via the light from your computer screen or phone. Photons play a key role in the next-generation quantum information technology, such as quantum computing and communications. A quantum emitter, capable of producing a single, pure photon, is the crux of such technology but has many issues that have yet to be solved, according to KAIST researchers.
A research team under Professor Yong-Hoon Cho has developed a technique that can isolate the desired quality emitter by reducing the noise surrounding the target with what they have dubbed a ‘nanoscale focus pinspot.’ They published their results on June 24 in ACS Nano.
“The nanoscale focus pinspot is a structurally nondestructive technique under an extremely low dose ion beam and is generally applicable for various platforms to improve their single-photon purity while retaining the integrated photonic structures,” said lead author Yong-Hoon Cho from the Department of Physics at KAIST.
To produce single photons from solid state materials, the researchers used wide-bandgap semiconductor quantum dots — fabricated nanoparticles with specialized potential properties, such as the ability to directly inject current into a small chip and to operate at room temperature for practical applications. By making a quantum dot in a photonic structure that propagates light, and then irradiating it with helium ions, researchers theorized that they could develop a quantum emitter that could reduce the unwanted noisy background and produce a single, pure photon on demand.
Professor Cho explained, “Despite its high resolution and versatility, a focused ion beam typically suppresses the optical properties around the bombarded area due to the accelerated ion beam’s high momentum. We focused on the fact that, if the focused ion beam is well controlled, only the background noise can be selectively quenched with high spatial resolution without destroying the structure.”
In other words, the researchers focused the ion beam on a mere pin prick, effectively cutting off the interactions around the quantum dot and removing the physical properties that could negatively interact with and degrade the photon purity emitted from the quantum dot.
“It is the first developed technique that can quench the background noise without changing the optical properties of the quantum emitter and the built-in photonic structure,” Professor Cho asserted.
Professor Cho compared it to stimulated emission depletion microscopy, a technique used to decrease the light around the area of focus, but leaving the focal point illuminated. The result is increased resolution of the desired visual target.
“By adjusting the focused ion beam-irradiated region, we can select the target emitter with nanoscale resolution by quenching the surrounding emitter,” Professor Cho said. “This nanoscale selective-quenching technique can be applied to various material and structural platforms and further extended for applications such as optical memory and high-resolution micro displays.” Korea’s National Research Foundation and the Samsung Science and Technology Foundation supported this work.
-PublicationMinho Choi, Seongmoon Jun, and Yong-Hoon Cho et al. ACS Nano‘Nanoscale Focus Pinspot for High-Purity Quantum Emitters via Focused-Ion-Beam-Induced Luminescence Quenching,’(https://pubs.acs.org/doi/10.1021/acsnano.1c00587)
-ProfileProfessor Yong-Hoon ChoQuantum & Nanobio Photonics Laboratoryhttp://qnp.kaist.ac.kr/
Department of PhysicsKAIST
2021.09.02 View 9779 -
Genomic Data Reveals New Insights into Human Embryonic Development
KAIST researchers have used whole-genome sequencing to track the development from a single fertilized-egg to a human body
Genomic scientists at KAIST have revealed new insights into the process of human embryonic development using large-scale, whole-genome sequencing of cells and tissues from adult humans. The study, published in Nature on Aug.25, is the first to analyse somatic mutations in normal tissue across multiple organs within and between humans.
An adult human body comprises trillions of cells of more than 200 types. How a human develops from a single fertilized egg to a fully grown adult is a fundamental question in biomedical science. Due to the ethical challenges of performing studies on human embryos, however, the details of this process remain largely unknown.
To overcome these issues, the research team took a different approach. They analysed genetic mutations in cells taken from adult human post-mortem tissue. Specifically, they identified mutations that occur spontaneously in early developmental cell divisions. These mutations, also called genomic scars, act like unique genetic fingerprints that can be used to trace the embryonic development process.
The study, which looked at 334 single-cell colonies and 379 tissue samples from seven recently deceased human body donors, is the largest single-cell, whole-genome analysis carried out to date. The researchers examined the genomic scars of each individual in order to reconstruct their early embryonic cellular dynamics.
The result revealed several key characteristics of the human embryonic development process. Firstly, mutation rates are higher in the first cell division, but then decrease to approximately one mutation per cell during later cell division. Secondly, early cells contributed unequally to the development of the embryo in all informative donors, for example, at the two-cell stage, one of the cells always left more progeny cells than the other. The ratio of this was different from person to person, implying that the process varies between individuals and is not fully deterministic.
The researchers were also able to deduce the timing of when cells begin to differentiate into individual organ-specific cells. They found that within three days of fertilization, embryonic cells began to be distributed asymmetrically into tissues for the left and right sides of the body, followed by differentiation into three germ layers, and then differentiation into specific tissues and organs.
“It is an impressive scientific achievement that, within 20 years of the completion of human genome project, genomic technology has advanced to the extent that we are now able to accurately identify mutations in a single-cell genome,” said Professor Young Seok Ju from the Graduate School of Medical Science and Engineering at KAIST. “This technology will enable us to track human embryogenesis at even higher resolutions in the future.”
The techniques used in this study could be used to improve our understanding of rare diseases caused by abnormalities in embryonic development, and to design new precision diagnostics and treatments for patients.
The research was completed in collaboration with Kyungpook National University Hospital, the Korea Institute of Science and Technology Information, Catholic University of Korea School of Medicine, Genome Insights Inc, and Immune Square Inc. This work was supported by the Suh Kyungbae Foundation, the Ministry of Health and Welfare of Korea, the National Research Foundastion of Korea.
-PublicationSeongyeol Park, Nanda Mali, Ryul Kim et al. ‘Clonal dynamics in early human embryogenesis inferred from somatic mutation’ Nature Online ahead of print, Aug. 25, 2021 (https://doi.org/10.1038/s41586-021-03786-8)
-ProfileProfessor Young Seok JuLab of Cancer Genomics (https://www.julab.kaist.ac.kr/)Graduate School of Medical Science and EngineeringKAIST
2021.08.31 View 8573 -
KAIST KPC4IR Presents the AI Global Guide for Healthcare
The benchmark for the responsible usage of AI technology in the healthcare sector will promote clarity and high standards for technological applications
The KAIST Korea Policy Center for the Fourth Industrial Revolution (KPC4IR) published 'Using AI to Support Healthcare Decisions: A Guide for Society.' This global guide is designed to serve as a benchmark for the responsible usage of AI technologies, and will promote clarity and high standards for technological applications in the healthcare sector. The guide details what should be considered when making clinical decisions to help reduce the chances of the AI giving false or misleading results.
The KPC4IR presented the guide in collaboration with the Lloyd’s Register Foundation Institute for the Public Understanding of Risk at the National University of Singapore (NUS IPUR) and Sense about Science, a non-profit organization in the UK specialized in science communication, during the 2021 SIG-KDD (Special Interest Group on Knowledge Discovery and Data Mining) Conference on August 15.
AI technology is being widely used in the healthcare sector and has already proved its accuracy and efficiency in diagnosing and predicting diseases. Despite its huge impact on our daily lives in every sector of society, AI technology has some drawbacks and comes with risks, especially due to biased algorithms.
“We focused on the ‘reliability’ of AI applications in the healthcare sector to make all data well represented, in good quality. The technology will eventually innovate to better serve the people’s new demand, especially critical demands for safety and precision in healthcare services. This global guide will help both developers and people’s understanding of the appropriate technology applications,” says Director So Young Kim at the KPC4IR.
The guide, for instance, says that to scrutinize quality and reliability, the source of the data must be clearly known; the data must have been collected or selected for the purpose it’s being used for; the limitations and assumptions for that purpose have been clearly stated; the biases have been addressed; and it has been properly tested in the real world. It also reflects the importance of the representativeness of data that will affect the accuracy of the AI applications.
“By being transparent and demonstrating the steps taken to check that the AI is reliable, researchers and developers can help give people confidence about providing their data,” the guide states.
For this guide, the KPC4IR and its collaborators collected data after working with numerous experts from the Graduate School of AI at KAIST, the Science and Technology Policy Institute in Korea, Asan Medical Center in Seoul, Seoul National University Bundang Hospital, and AI solution companies.
2021.08.17 View 7807 -
Brain-Inspired Highly Scalable Neuromorphic Hardware Presented
Neurons and synapses based on single transistor can dramatically reduce the hardware cost and accelerate the commercialization of neuromorphic hardware
KAIST researchers fabricated a brain-inspired highly scalable neuromorphic hardware by co-integrating single transistor neurons and synapses. Using standard silicon complementary metal-oxide-semiconductor (CMOS) technology, the neuromorphic hardware is expected to reduce chip cost and simplify fabrication procedures.
The research team led by Yang-Kyu Choi and Sung-Yool Choi produced a neurons and synapses based on single transistor for highly scalable neuromorphic hardware and showed the ability to recognize text and face images. This research was featured in Science Advances on August 4.
Neuromorphic hardware has attracted a great deal of attention because of its artificial intelligence functions, but consuming ultra-low power of less than 20 watts by mimicking the human brain. To make neuromorphic hardware work, a neuron that generates a spike when integrating a certain signal, and a synapse remembering the connection between two neurons are necessary, just like the biological brain. However, since neurons and synapses constructed on digital or analog circuits occupy a large space, there is a limit in terms of hardware efficiency and costs. Since the human brain consists of about 1011 neurons and 1014 synapses, it is necessary to improve the hardware cost in order to apply it to mobile and IoT devices.
To solve the problem, the research team mimicked the behavior of biological neurons and synapses with a single transistor, and co-integrated them onto an 8-inch wafer. The manufactured neuromorphic transistors have the same structure as the transistors for memory and logic that are currently mass-produced. In addition, the neuromorphic transistors proved for the first time that they can be implemented with a ‘Janus structure’ that functions as both neuron and synapse, just like coins have heads and tails.
Professor Yang-Kyu Choi said that this work can dramatically reduce the hardware cost by replacing the neurons and synapses that were based on complex digital and analog circuits with a single transistor. "We have demonstrated that neurons and synapses can be implemented using a single transistor," said Joon-Kyu Han, the first author. "By co-integrating single transistor neurons and synapses on the same wafer using a standard CMOS process, the hardware cost of the neuromorphic hardware has been improved, which will accelerate the commercialization of neuromorphic hardware,” Han added.This research was supported by the National Research Foundation (NRF) and IC Design Education Center (IDEC).
-PublicationJoon-Kyu Han, Sung-Yool Choi, Yang-Kyu Choi, et al.“Cointegration of single-transistor neurons and synapses by nanoscale CMOS fabrication for highly scalable neuromorphic hardware,” Science Advances (DOI: 10.1126/sciadv.abg8836)
-ProfileProfessor Yang-Kyu ChoiNano-Oriented Bio-Electronics Labhttps://sites.google.com/view/nobelab/
School of Electrical EngineeringKAIST
Professor Sung-Yool ChoiMolecular and Nano Device Laboratoryhttps://www.mndl.kaist.ac.kr/
School of Electrical EngineeringKAIST
2021.08.05 View 10229 -
Prof. Changho Suh Named the 2021 James L. Massey Awardee
Professor Changho Suh from the School of Electrical Engineering was named the recipient of the 2021 James L.Massey Award. The award recognizes outstanding achievement in research and teaching by young scholars in the information theory community. The award is named in honor of James L. Massey, who was an internationally acclaimed pioneer in digital communications and revered teacher and mentor to communications engineers.
Professor Suh is a recipient of numerous awards, including the 2021 James L. Massey Research & Teaching Award for Young Scholars from the IEEE Information Theory Society, the 2019 AFOSR Grant, the 2019 Google Education Grant, the 2018 IEIE/IEEE Joint Award, the 2015 IEIE Haedong Young Engineer Award, the 2013 IEEE Communications Society Stephen O. Rice Prize, the 2011 David J. Sakrison Memorial Prize (the best dissertation award in UC Berkeley EECS), the 2009 IEEE ISIT Best Student Paper Award, the 2020 LINKGENESIS Best Teacher Award (the campus-wide Grand Prize in Teaching), and the four Departmental Teaching Awards (2013, 2019, 2020, 2021).
Dr. Suh is an IEEE Information Theory Society Distinguished Lecturer, the General Chair of the Inaugural IEEE East Asian School of Information Theory, and a Member of the Young Korean Academy of Science and Technology. He is also an Associate Editor of Machine Learning for the IEEE Transactions on Information Theory, the Editor for the IEEE Information Theory Newsletter, a Column Editor for IEEE BITS the Information Theory Magazine, an Area Chair of NeurIPS 2021, and on the Senior Program Committee of IJCAI 2019–2021.
2021.07.27 View 7787 -
VP Sang Yup Lee Honored with the Pony Chung Innovation Award
Vice President for Research Sang Yup Lee became the recipient of the Innovation Award by the Pony Chung Foundation that was established to honor the late Se-yung Chung, the former chairman of Hyundai Development Company. He will receive 200 million KRW in prize money. Chairman Chung developed Korea’s first domestically manufactured automobile, ‘Pony,’ in the mid-1970s that became the cornerstone of Korea’s auto industry today.
Distinguished Professor Lee, from the Department of Chemical and Biomolecular Engineering, is a pioneering scholar in the field of systems metabolic engineering who developed various micro-organisms for producing a wide range of fuels, chemicals, materials, and natural compounds.
He recently was elected as a foreign member of the Royal Society in the UK and is the first Korean ever elected into the National Academy of Inventors (NAI) in the US as well as one of 13 scholars elected as an International Member of both the National Academy of Sciences (NAS) and the National Academy of Engineering (NAE) in the US.
2021.07.13 View 9486 -
Professor Heung-Sun Sim the MSIT Scientist of July
Professor Heung-Sun Sim from the Department of Physics was selected as the Scientist of July by the Ministry of Science and ICT. Professor Sim was recognized for his research of the Kondo effect, which opened a novel way to engineer spin screening and entanglement by directly observing a quantum phenomenon known as a Kondo screening cloud. His research revealed that the cloud can mediate interactions between distant spins confined in quantum dots, which is a necessary protocol for semiconductor spin-based quantum information processing. This phenomenon is essentially a cloud that masks magnetic impurities in a material. It was known to exist but its spatial extension had never been observed, creating controversy over whether such an extension actually existed. The research was reported in Nature in March 2020. With this award, Professor Sim received 10 million KRW in prize money.
2021.07.12 View 7164 -
Repurposed Drugs Present New Strategy for Treating COVID-19
Virtual screening of 6,218 drugs and cell-based assays identifies best therapeutic medication candidates
A joint research group from KAIST and Institut Pasteur Korea has identified repurposed drugs for COVID-19 treatment through virtual screening and cell-based assays. The research team suggested the strategy for virtual screening with greatly reduced false positives by incorporating pre-docking filtering based on shape similarity and post-docking filtering based on interaction similarity. This strategy will help develop therapeutic medications for COVID-19 and other antiviral diseases more rapidly. This study was reported at the Proceedings of the National Academy of Sciences of the United States of America (PNAS).
Researchers screened 6,218 drugs from a collection of FDA-approved drugs or those under clinical trial and identified 38 potential repurposed drugs for COVID-19 with this strategy. Among them, seven compounds inhibited SARS-CoV-2 replication in Vero cells. Three of these drugs, emodin, omipalisib, and tipifarnib, showed anti-SARS-CoV-2 activity in human lung cells, Calu-3.
Drug repurposing is a practical strategy for developing antiviral drugs in a short period of time, especially during a global pandemic. In many instances, drug repurposing starts with the virtual screening of approved drugs. However, the actual hit rate of virtual screening is low and most of the predicted drug candidates are false positives.
The research group developed effective filtering algorithms before and after the docking simulations to improve the hit rates. In the pre-docking filtering process, compounds with similar shapes to the known active compounds for each target protein were selected and used for docking simulations. In the post-docking filtering process, the chemicals identified through their docking simulations were evaluated considering the docking energy and the similarity of the protein-ligand interactions with the known active compounds.
The experimental results showed that the virtual screening strategy reached a high hit rate of 18.4%, leading to the identification of seven potential drugs out of the 38 drugs initially selected.
“We plan to conduct further preclinical trials for optimizing drug concentrations as one of the three candidates didn’t resolve the toxicity issues in preclinical trials,” said Woo Dae Jang, one of the researchers from KAIST.
“The most important part of this research is that we developed a platform technology that can rapidly identify novel compounds for COVID-19 treatment. If we use this technology, we will be able to quickly respond to new infectious diseases as well as variants of the coronavirus,” said Distinguished Professor Sang Yup Lee.
This work was supported by the KAIST Mobile Clinic Module Project funded by the Ministry of Science and ICT (MSIT) and the National Research Foundation of Korea (NRF). The National Culture Collection for Pathogens in Korea provided the SARS-CoV-2 (NCCP43326).
-PublicationWoo Dae Jang, Sangeun Jeon, Seungtaek Kim, and Sang Yup Lee. Drugs repurposed for COVID-19 by virtual screening of 6,218 drugs and cell-based assay. Proc. Natl. Acad. Sci. U.S.A. (https://doi/org/10.1073/pnas.2024302118)
-ProfileDistinguished Professor Sang Yup LeeMetabolic &Biomolecular Engineering National Research Laboratoryhttp://mbel.kaist.ac.kr
Department of Chemical and Biomolecular EngineeringKAIST
2021.07.08 View 12963 -
Study of T Cells from COVID-19 Convalescents Guides Vaccine Strategies
Researchers confirm that most COVID-19 patients in their convalescent stage carry stem cell-like memory T cells for months
A KAIST immunology research team found that most convalescent patients of COVID-19 develop and maintain T cell memory for over 10 months regardless of the severity of their symptoms. In addition, memory T cells proliferate rapidly after encountering their cognate antigen and accomplish their multifunctional roles. This study provides new insights for effective vaccine strategies against COVID-19, considering the self-renewal capacity and multipotency of memory T cells.
COVID-19 is a disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. When patients recover from COVID-19, SARS-CoV-2-specific adaptive immune memory is developed. The adaptive immune system consists of two principal components: B cells that produce antibodies and T cells that eliminate infected cells. The current results suggest that the protective immune function of memory T cells will be implemented upon re-exposure to SARS-CoV-2.
Recently, the role of memory T cells against SARS-CoV-2 has been gaining attention as neutralizing antibodies wane after recovery. Although memory T cells cannot prevent the infection itself, they play a central role in preventing the severe progression of COVID-19. However, the longevity and functional maintenance of SARS-CoV-2-specific memory T cells remain unknown.
Professor Eui-Cheol Shin and his collaborators investigated the characteristics and functions of stem cell-like memory T cells, which are expected to play a crucial role in long-term immunity. Researchers analyzed the generation of stem cell-like memory T cells and multi-cytokine producing polyfunctional memory T cells, using cutting-edge immunological techniques.
This research is significant in that revealing the long-term immunity of COVID-19 convalescent patients provides an indicator regarding the long-term persistence of T cell immunity, one of the main goals of future vaccine development, as well as evaluating the long-term efficacy of currently available COVID-19 vaccines.
The research team is presently conducting a follow-up study to identify the memory T cell formation and functional characteristics of those who received COVID-19 vaccines, and to understand the immunological effect of COVID-19 vaccines by comparing the characteristics of memory T cells from vaccinated individuals with those of COVID-19 convalescent patients.
PhD candidate Jae Hyung Jung and Dr. Min-Seok Rha, a clinical fellow at Yonsei Severance Hospital, who led the study together explained, “Our analysis will enhance the understanding of COVID-19 immunity and establish an index for COVID-19 vaccine-induced memory T cells.”
“This study is the world’s longest longitudinal study on differentiation and functions of memory T cells among COVID-19 convalescent patients. The research on the temporal dynamics of immune responses has laid the groundwork for building a strategy for next-generation vaccine development,” Professor Shin added. This work was supported by the Samsung Science and Technology Foundation and KAIST, and was published in Nature Communications on June 30.
-Publication:
Jung, J.H., Rha, MS., Sa, M. et al. SARS-CoV-2-specific T cell memory is sustained in COVID-19 convalescent patients for 10 months with successful development of stem cell-like memory T cells. Nat Communications 12, 4043 (2021). https://doi.org/10.1038/s41467-021-24377-1
-Profile:
Professor Eui-Cheol Shin
Laboratory of Immunology & Infectious Diseases (http://liid.kaist.ac.kr/)
Graduate School of Medical Science and Engineering
KAIST
2021.07.05 View 12348 -
Alumni Professor Cho at NYU Endows Scholarship for Female Computer Scientists
Alumni Professor Kyunghyun Cho at New York University endowed the “Lim Mi-Sook Scholarship” at KAIST for female computer scientists in honor of his mother.
Professor Cho, a graduate of the School of Computing in 2011 completed his master’s and PhD at Alto University in Finland in 2014. He has been teaching at NYU since 2015 and received the Samsung Ho-Am Prize for Engineering this year in recognition of his outstanding researches in the fields of machine learning and AI.
“I hope this will encourage young female students to continue their studies in computer science and encourage others to join the discipline in the future, thereby contributing to building a more diverse community of computer scientists,” he said in his written message. His parents and President Kwang Hyung Lee attended the donation ceremony held at the Daejeon campus on June 24.
Professor Cho has developed neural network machine learning translation algorithm that is widely being used in translation engines. His contributions to AI-powered translations and innovation in the industry led him to win one of the most prestigious prizes in Korea.
He decided to donate his 300 million KRW prize money to fund two 100 million KRW scholarships named after each of his parents: the Lim Mi-Sook Scholarship is for female computer scientists and the Bae-Gyu Scholarly Award for Classics is in honor of his father, who is a Korean literature professor at Soongsil University in Korea. He will also fund a scholarship at Alto University.
“I recall there were less than five female students out of 70 students in my cohort during my undergraduate studies at KAIST even in later 2000s. Back then, it just felt natural that boys majored computer science and girls in biology.”
He said he wanted to acknowledge his mother, who had to give up her teaching career in the 1980s to take care of her children. “It made all of us think more about the burden of raising children that is placed often disproportionately on mothers and how it should be better distributed among parents, relatives, and society in order to ensure and maximize equity in education as well as career development and advances.”
He added, “As a small step to help build a more diverse environment, I have decided to donate to this fund to provide a small supplement to the small group of female students majoring in computer science.
2021.07.01 View 8832 -
Prof. Sang Wan Lee Selected for 2021 IBM Academic Award
Professor Sang Wan Lee from the Department of Bio and Brain Engineering was selected as the recipient of the 2021 IBM Global University Program Academic Award. The award recognizes individual faculty members whose emerging science and technology contains significant interest for universities and IBM.
Professor Lee, whose research focuses on artificial intelligence and computational neuroscience, won the award for his research proposal titled A Neuroscience-Inspired Approach for Metacognitive Reinforcement Learning. IBM provides a gift of $40,000 to the recipient’s institution in recognition of the selection of the project but not as a contract for services.
Professor Lee’s project aims to exploit the unique characteristics of human reinforcement learning. Specifically, he plans to examines the hypothesis that metacognition, a human’s ability to estimate their uncertainty level, serves to guide sample-efficient and near-optimal exploration, making it possible to achieve an optimal balance between model-based and model-free reinforcement learning.
He was also selected as the winner of the Google Research Award in 2016 and has been working with DeepMind and University College London to conduct basic research on decision-making brain science to establish a theory on frontal lobe meta-enhance learning.
"We plan to conduct joint research for utilizing brain-based artificial intelligence technology and frontal lobe meta-enhanced learning technology modeling in collaboration with an international research team including IBM, DeepMind, MIT, and Oxford,” Professor Lee said.
2021.06.25 View 11348