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Dongwon Chairman Donates ₩50 Billion to Fund AI Graduate School
Dongwon Group Honorary Chairman and Founder Jae-chul Kim donated his private property worth ₩50 billion (US $46 million) to KAIST on December 16. Honorary Chairman Kim’s gift will fund the KAIST Graduate School of AI (GSAI), which was established last year. The KAIST GSAI will be re-named the ‘Kim Jae-chul Graduate School of AI’ to honor Honorary Chairman Kim.
This is the third major donation that KAIST has received this year following KAIST Development Foundation Chairman Soo-Young Lee’s ₩67.6 billion in real estate in July and another ₩10 billion from a KAIST alumnus, Chairman Byeong-Gyu Chang of Krafton, in January.
“KAIST, as the cradle that trains Korea’s best talents in science and technology, has been at the forefront of leading national development over the past 50 years. I hope that KAIST will also strive to nurture global talents who excel in AI innovation and steer Korea’s new advancements to lead the Fourth Industrial Revolution,” said Honorary Chairman Kim during the donation ceremony at KAIST’s main campus in Daejeon.
The ceremony was held in strict compliance with Level Two social distancing guidelines and measures in response to the persistent coronavirus. Less than 50 people, including Honorary Chairman Kim’s family, President Sung-Chul Shin, and professors from key posts at KAIST, attended the ceremony.
Dongwon Group is one of the leading fishery companies in Korea, established in 1969 by Honorary Chairman Kim. He recalled memories of his childhood as he explained the background of the donation, saying, “When I was young, I searched for Korea’s future in the world’s oceans. However, a new future lies in the ‘oceans of data.’”
“I have been pondering how I could further contribute to my country, and realized that bringing up talented individuals in the AI and data science-related fields is important. I hope that my donation today will aid the take-off of KAIST’s great voyage towards becoming a global “flagship” in the new eras to come,” Honorary Chairman Kim added.
To this, President Shin responded acclaiming the noblesse oblige held by Honorary Chairman Kim to further develop Korea’s science and technology and make Korea into a leader in AI innovation.
“We will always keep KAIST’s role and mission close to our hearts and do our best to make KAIST into a global hub for talent cultivation and R&D in AI, based on Honorary Chairman Kim’s donation,” said President Shin.
With Honorary Chairman Kim’s donation, the KAIST GSAI will first expand its faculty in both quantity and quality. By expanding the number of full-time, highly qualified professors to 40 by 2030, the School will train the most talented personnel in fusion and convergence AI.
The KAIST GSAI opened in August 2019 as the first school in Korea to be selected as part of the ‘2019 Graduate School for AI Support Project’ by the Ministry of Science and ICT. The current faculty is composed of 13 full-time professors including ex-researchers from AI labs of global conglomerates including Google, IBM Watson, and Microsoft, as well as eight adjunct professors, making a total of 21 faculty members. There are currently 138 students attending the School, including 79 master’s students, 17 in the integrated MS-PhD program, and 42 PhD candidates.
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2020.12.16 View 10515 -
KAIST and Google Partner to Develop AI Curriculum
Two KAIST professors, Hyun Wook Ka from the School of Transdisciplinary Studies and Young Jae Jang from the Department of Industrial and Systems Engineering, were recipients of Google Education Grants that will support the development of new AI courses integrating the latest industrial technology. This collaboration is part of the KAIST-Google Partnership, which was established in July 2019 with the goal of nurturing AI talent at KAIST.
The two proposals -- Professor Ka’s ‘Cloud AI-Empowered Multimodal Data Analysis for Human Affect Detection and Recognition’ and Professor Jang’s ‘Learning Smart Factory with AI’-- were selected by the KAIST Graduate School of AI through a school-wide competition held in July. The proposals then went through a final review by Google and were accepted. The two professors will receive $7,500 each for developing AI courses using Google technology for one year.
Professor Ka’s curriculum aims to provide a rich learning experience for students by providing basic knowledge on data science and AI and helping them obtain better problem solving and application skills using practical and interdisciplinary data science and AI technology.
Professor Jang’s curriculum is designed to solve real-world manufacturing problems using AI and it will be field-oriented. Professor Jang has been managing three industry-academic collaboration centers in manufacturing and smart factories within KAIST and plans to develop his courses to go beyond theory and be centered on case studies for solving real-world manufacturing problems using AI.
Professor Jang said, “Data is at the core of smart factories and AI education, but there is often not enough of it for the education to be effective. The KAIST Advanced Manufacturing Laboratory has a testbed for directly acquiring data generated from real semiconductor automation equipment, analyzing it, and applying algorithms, which enables truly effective smart factory and AI education.”
KAIST signed a partnership with Google in July 2019 to foster global AI talent and is operating various programs to train AI experts and support excellent AI research for two years.
The Google AI Focused Research Award supports world-class faculty performing cutting-edge research and was previously awarded to professors Sung Ju Hwang from the Graduate School of AI and Steven Whang from the School of Electrical Engineering along with Google Cloud Platform (GCP) credits. These two professors have been collaborating with Google teams since October 2018 and recently extended their projects to continue through 2021.
In addition, a Google Ph.D. Fellowship was awarded to Taesik Gong from the School of Computing in October this year, and three Student Travel Grants were awarded to Sejun Park from the School of Electrical Engineering, Chulhyung Lee from the Department of Mathematical Sciences, and Sangyun Lee from the School of Computing earlier in March. Five students were also recommended for the Google Internship program in March.
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2020.12.11 View 15193 -
Taesik Gong Named Google PhD Fellow
PhD candidate Taesik Gong from the School of Computing was named a 2020 Google PhD Fellow in the field of machine learning.
The Google PhD Fellowship Program has recognized and supported outstanding graduate students in computer science and related fields since 2009. Gong is one of two Korean students chosen as the recipients of Google Fellowships this year. A total of 53 students across the world in 12 fields were awarded this fellowship.
Gong’s research on condition-independent mobile sensing powered by machine learning earned him this year’s fellowship. He has published and presented his work through many conferences including ACM SenSys and ACM UbiComp, and has worked at Microsoft Research Asia and Nokia Bell Labs as a research intern. Gong was also the winner of the NAVER PhD Fellowship Award in 2018.
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2020.10.15 View 14497 -
Tinkering with Roundworm Proteins Offers Hope for Anti-aging Drugs
- The somatic nuclear protein kinase VRK-1 increases the worm’s lifespan through AMPK activation, and this mechanism can be applied to promoting human longevity, the study reveals. -
KAIST researchers have been able to dial up and down creatures’ lifespans by altering the activity of proteins found in roundworm cells that tell them to convert sugar into energy when their cellular energy is running low. Humans also have these proteins, offering up the intriguing possibilities for developing longevity-promoting drugs. These new findings were published on July 1 in Science Advances.
The roundworm Caenorhabditis elegans (C. elegans), a millimeter-long nematode commonly used in lab testing, enjoyed a boost in its lifespan when researchers tinkered with a couple of proteins involved in monitoring the energy use by its cells.
The proteins VRK-1 and AMPK work in tandem in roundworm cells, with the former telling the latter to get to work by sticking a phosphate molecule, composed of one phosphorus and four oxygen atoms, on it. In turn, AMPK’s role is to monitor energy levels in cells, when cellular energy is running low. In essence, VRK-1 regulates AMPK, and AMPK regulates the cellular energy status.
Using a range of different biological research tools, including introducing foreign genes into the worm, a group of researchers led by Professor Seung-Jae V. Lee from the Department of Biological Sciences at KAIST were able to dial up and down the activity of the gene that tells cells to produce the VRK-1 protein. This gene has remained pretty much unchanged throughout evolution. Most complex organisms have this same gene, including humans.
Lead author of the study Sangsoon Park and his colleagues confirmed that the overexpression, or increased production, of the VRK-1 protein boosted the lifespan of the C. elegans, which normally lives just two to three weeks, and the inhibition of VRK-1 production reduced its lifespan.
The research team found that the activity of the VRK-1-to-AMPK cellular-energy monitoring process is increased in low cellular energy status by reduced mitochondrial respiration, the set of metabolic chemical reactions that make use of the oxygen the worm breathes to convert macronutrients from food into the energy “currency” that cells spend to do everything they need to do.
It is already known that mitochondria, the energy-producing engine rooms in cells, play a crucial role in aging, and declines in the functioning of mitochondria are associated with age-related diseases. At the same time, the mild inhibition of mitochondrial respiration has been shown to promote longevity in a range of species, including flies and mammals.
When the research team performed similar tinkering with cultured human cells, they found they could also replicate this ramping up and down of the VRK-1-to-AMPK process that occurs in roundworms.
“This raises the intriguing possibility that VRK-1 also functions as a factor in governing human longevity, and so perhaps we can start developing longevity-promoting drugs that alter the activity of VRK-1,” explained Professor Lee.
At the very least, the research points us in an interesting direction for investigating new therapeutic strategies to combat metabolic disorders by targeting the modulation of VRK-1. Metabolic disorders involve the disruption of chemical reactions in the body, including diseases of the mitochondria.
But before metabolic disorder therapeutics or longevity drugs can be contemplated by scientists, further research still needs to be carried out to better understand how VRK-1 works to activate AMPK, as well as figure out the precise mechanics of how AMPK controls cellular energy.
This work was supported by the National Research Foundation (NRF), and the Ministry of Science and ICT (MSIT) of Korea.
Image credit: Seung-Jae V. LEE, KAIST.
Image usage restrictions: News organizations may use or redistribute this image, with proper attribution, as part of news coverage of this paper only.
Publication:
Park, S., et al. (2020) ‘VRK-1 extends life span by activation of AMPK via phosphorylation’. Science Advances, Volume 6. No. 27, eaaw7824. Available online at https://doi.org/10.1126/sciadv.aaw7824
Profile: Seung-Jae V. Lee, Ph.D.
Professor
seungjaevlee@kaist.ac.kr
https://sites.google.com/view/mgakaist
Molecular Genetics of Aging Laboratory
Department of Biological Sciences
Korea Advanced Institute of Science and Technology (KAIST)
https://www.kaist.ac.krDaejeon 34141, Korea
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2020.07.31 View 14139 -
Simple Molecular Reagents to Treat Alzheimer’s Disease
- Researchers report minimalistic principles for designing small molecules with multiple reactivities against dementia. -
Sometimes the most complex problems actually have very simple solutions. A group of South Korean researchers reported an efficient and effective redox-based strategy for incorporating multiple functions into simple molecular reagents against neurodegenerative disorders. The team developed redox-active aromatic molecular reagents with a simple structural composition that can simultaneously target and modulate various pathogenic factors in complex neurodegenerative disorders such as Alzheimer’s disease.
Alzheimer’s disease is one of the most prevalent neurodegenerative disorders, affecting one in ten people over the age of 65. Early-onset dementia also increasingly affects younger people.
A number of pathogenic elements such as reactive oxygen species, amyloid-beta, and metal ions have been suggested as potential causes of Alzheimer’s disease. Each element itself can lead to Alzheimer’s disease, but interactions between them may also aggravate the patient’s condition or interfere with the appropriate clinical care.
For example, when interacting with amyloid-beta, metal ions foster the aggregation and accumulation of amyloid-beta peptides that can induce oxidative stress and toxicity in the brain and lead to neurodegeneration.
Because these pathogenic factors of Alzheimer’s disease are intertwined, developing therapeutic agents that are capable of simultaneously regulating metal ion dyshomeostasis, amyloid-beta agglutination, and oxidative stress responses remains a key to halting the progression of the disease.
A research team led by Professor Mi Hee Lim from the Department of Chemistry at KAIST demonstrated the feasibility of structure-mechanism-based molecular design for controlling a molecule’s chemical reactivity toward the various pathological factors of Alzheimer’s disease by tuning the redox properties of the molecule.
This study, featured as the ‘ACS Editors’ Choice’ in the May 6th issue of the Journal of the American Chemical Society (JACS), was conducted in conjunction with KAIST Professor Mu-Hyun Baik’s group and Professor Joo-Young Lee’s group at the Asan Medical Center.
Professor Lim and her collaborators rationally designed and generated 10 compact aromatic molecules presenting a range of redox potentials by adjusting the electronic distribution of the phenyl, phenylene, or pyridyl moiety to impart redox-dependent reactivities against the multiple pathogenic factors in Alzheimer’s disease.
During the team’s biochemical and biophysical studies, these designed molecular reagents displayed redox-dependent reactivities against numerous desirable targets that are associated with Alzheimer’s disease such as free radicals, metal-free amyloid-beta, and metal-bound amyloid-beta.
Further mechanistic results revealed that the redox properties of these designed molecular reagents were essential for their function. The team demonstrated that these reagents engaged in oxidative reactions with metal-free and metal-bound amyloid-beta and led to chemical modifications. The products of such oxidative transformations were observed to form covalent adducts with amyloid-beta and alter its aggregation.
Moreover, the administration of the most promising candidate molecule significantly attenuated the amyloid pathology in the brains of Alzheimer’s disease transgenic mice and improved their cognitive defects.
Professor Lim said, “This strategy is straightforward, time-saving, and cost-effective, and its effect is significant. We are excited to help enable the advancement of new therapeutic agents for neurodegenerative disorders, which can improve the lives of so many patients.”
This work was supported by the National Research Foundation (NRF) of Korea, the Institute for Basic Science (IBS), and the Asan Institute for Life Sciences.
Image credit: Professor Mi Hee Lim, KAIST
Image usage restrictions: News organizations may use or redistribute this image, with proper attribution, as part of the news coverage of this paper only.
Publication:
Kim, M. et al. (2020) ‘Minimalistic Principles for Designing Small Molecules with Multiple Reactivities against Pathological Factors in Dementia.’ Journal of the American Chemical Society (JACS), Volume 142, Issue 18, pp.8183-8193. Available online at https://doi.org/10.1021/jacs.9b13100
Profile:
Mi Hee Lim
Professor
miheelim@kaist.ac.kr
http://sites.google.com/site/miheelimlab
Lim Laboratory
Department of Chemistry
KAIST
Profile:
Mu-Hyun Baik
Professor
mbaik2805@kaist.ac.kr
https://baik-laboratory.com/
Baik Laboratory
Department of Chemistry
KAIST
Profile:
Joo-Yong Lee
Professor
jlee@amc.seoul.kr
Asan Institute for Life Sciences
Asan Medical Center
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2020.05.11 View 19018 -
A Study Finds Neuropeptide Somatostatin Enhances Visual Processing
Researchers have confirmed that neuropeptide somatostatin can improve cognitive function in the brain. A research group of Professor Seung-Hee Lee from the Department of Biological Sciences at KAIST found that the application of neuropeptide somatostatin improves visual processing and cognitive behaviors by reducing excitatory inputs to parvalbumin-positive interneurons in the cortex.
This study, reported at Science Advances on April 22nd (EST), sheds a new light on the therapeutics of neurodegenerative diseases. According to a recent study in Korea, one in ten seniors over 65 is experiencing dementia-related symptoms in their daily lives such like memory loss, cognitive decline, and motion function disorders. Professor Lee believes that somatostatin treatment can be directly applied to the recovery of cognitive functions in Alzheimer’s disease patients.
Professor Lee started this study noting the fact that the level of somatostatin expression was dramatically decreased in the cerebral cortex and cerebrospinal fluid of Alzheimer’s disease patients
Somatostatin-expressing neurons in the cortex are known to exert the dendritic inhibition of pyramidal neurons via GABAergic transmission. Previous studies focused on their inhibitory effects on cortical circuits, but somatostatin-expressing neurons can co-release somatostatin upon activation. Despite the abundant expression of somatostatin and its receptors in the cerebral cortex, it was not known if somatostatin could modulate cognitive processing in the cortex.
The research team demonstrated that the somatostatin treatment into the cerebral cortex could enhance visual processing and cognitive behaviors in mice. The research team combined behaviors, in vivo and in vitro electrophysiology, and electron microscopy techniques to reveal how the activation of somatostatin receptors in vivo enhanced the ability of visual recognition in animals. Interestingly, somatostatin release can reduce excitatory synaptic transmission to another subtype of GABAergic interneurons, parvalbumin (PV)-expressing neurons.
As somatostatin is a stable and safe neuropeptide expressed naturally in the mammalian brain, it was safe to be injected into the cortex and cerebrospinal fluid, showing a potential application to drug development for curing cognitive disorders in humans.
Professor Lee said, “Our research confirmed the key role of the neuropeptide SST in modulating cortical function and enhancing cognitive ability in the mammalian brain. I hope new drugs can be developed based on the function of somatostatin to treat cognitive disabilities in many patients suffering from neurological disorders.”
This study was supported by the National Research Foundation of Korea.
Publication:
Song, Y. H et al. (2020) ‘Somatostatin enhances visual processing and perception by suppressing excitatory inputs to parvalbumin-positive interneurons in V1’, Science Advances, 6(17). Available online at https://doi.org/10.1126/sciadv.aaz0517
Profile:
Seung-Hee Lee
Associate Professor
shlee1@kaist.ac.kr
https://sites.google.com/site/leelab2013/
Sensory Processing Lab (SPL)
Department of Biological Sciences (BIO)
Korea Advanced Institute of Science and Technology (KAIST)
Profile:
You-Hyang Song
Researcher (Ph.D.)
dbgidtm17@kaist.ac.kr
SPL, KAIST BIO
Profile:
Yang-Sun Hwang
Researcher (M.S.)
hys940129@kaist.ac.kr
SPL, KAIST BIO
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2020.04.23 View 15536 -
Coordination Chemistry and Alzheimer’s Disease
It has become evident recently that the interactions between copper and amyloid-b neurotoxically impact the brain of patients with Alzheimer’s disease. KAIST researchers have reported a new strategy to alter the neurotoxicity in Alzheimer’s disease by using a rationally designed chemical reagent.
This strategy, developed by Professor Mi Hee Lim from the Department of Chemistry, can modify the coordination sphere of copper bound to amyloid-b, effectively inhibiting copper’s binding to amyloid-b and altering its aggregation and toxicity. Their study was featured in PNAS last month.
The researchers developed a small molecule that is able to directly interact with the coordination sphere of copper–amyloid-b complexes followed by modifications via either covalent conjugation, oxidation, or both under aerobic conditions. The research team simply utilized copper–dioxygen chemistry to design a chemical reagent.
Answering how peptide modifications by a small molecule occur remains very challenging. The system includes transition metals and amyloidogenic proteins and is quite heterogeneous, since they are continuously being changed. It is critical to carefully check the multiple variables such as the presence of dioxygen and the type of transition metal ions and amyloidogenic proteins in order to identify the underlying mechanisms and target specificity of the chemical reagent.
The research team employed various biophysical and biochemical methods to determine the mechanisms for modifications on the coordination sphere of copper–Aꞵ complexes. Among them, peptide modifications were mainly analyzed using electrospray ionization-mass spectrometry.
Mass spectrometry (MS) has been applied to verify such peptide modifications by calculating the shift in exact mass. The research team also performed collision-induced dissociation (CID) of the target ion detected by MS to pinpoint which amino acid residue is specifically modified. The CID fragmentizes the amide bond located between the amino acid residues. This fragmental analysis allows us to identify the specific sites of peptide modifications.
The copper and amyloid-b complexes represent a pathological connection between metal ions and amyloid-b in Alzheimer’s disease. Recent findings indicate that copper and amyloid-b can directly contribute toward neurodegeneration by producing toxic amyloid-b oligomers and reactive oxygen species.
Professor Lim said, “This study illustrates the first experimental evidence that the 14th histidine residue in copper–amyloid-b complexes can be specifically modified through either covalent conjugation, oxidation, or both. Considering the neurotoxic implications of the interactions between copper and amyloid-b, such modifications at the coordination sphere of copper in amyloid-b could effectively alter its properties and toxicity.”
“This multidisciplinary study with an emphasis on approaches, reactivities, and mechanisms looks forward to opening a new way to develop candidates of anti-neurodegenerative diseases,” she added. The National Research Foundation of Korea funded this research.
2020.03.03 View 9096 -
KAIST and Google Jointly Develop AI Curricula
KAIST selected the two professors who will develop AI curriculum under the auspices of the KAIST-Google Partnership for AI Education and Research. The Graduate School of AI announced the two authors among the 20 applicants who will develop the curriculum next year. They will be provided 7,500 USD per subject.
Professor Changho Suh from the School of Electrical Engineering and Professor Yong-Jin Yoon from the Department of Mechanical Engineering will use Google technology such as TensorFlow, Google Cloud, and Android to create the curriculum.
Professor Suh’s “TensorFlow for Information Theory and Convex Optimization “will be used for curriculum in the graduate courses and Professor Yoon’s “AI Convergence Project Based Learning (PBL)” will be used for online courses. Professor Yoon’s course will explore and define problems by utilizing AI and experiencing the process of developing products that use AI through design thinking, which involves product design, production, and verification. Professor Suh’s course will discus“information theory and convergence,” which uses basic sciences and engineering as well as AI, machine learning, and deep learning.
2019.12.04 View 17811 -
Sungjoon Park Named Google PhD Fellow
PhD candidate Sungjoon Park from the School of Computing was named a 2019 Google PhD Fellow in the field of natural language processing. The Google PhD fellowship program has recognized and supported outstanding graduate students in computer science and related fields since 2009. Park is one of three Korean students chosen as the recipients of Google Fellowships this year. A total of 54 students across the world in 12 fields were awarded this fellowship.
Park’s research on computational psychotherapy using natural language processing (NLP) powered by machine learning earned him this year’s fellowship. He presented of learning distributed representations in Korean and their interpretations during the 2017 Annual Conference of the Association for Computational Linguistics and the 2018 Conference on Empirical Methods in Natural Language Processing. He also applied machine learning-based natural language processing into computational psychotherapy so that a trained machine learning model could categorize client's verbal responses in a counseling dialogue. This was presented at the Annual Conference of the North American Chapter of the Association for Computational Linguistics.
More recently, he has been developing on neural response generation model and the prediction and extraction of complex emotion in text, and computational psychotherapy applications.
2019.09.17 View 11350 -
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 7529 -
KAIST-Google Partnership for AI Education and Research
Google has agreed to support KAIST students and professors in the fields of AI research and education. President Sung-Chul Shin and Google Korea Country Director John Lee signed the collaboration agreement during a ceremony on July 19 at KAIST.
Under the agreement, Google will fund the Google AI-Focused Research Awards Program, the PhD Fellowship Program, and Student Travel Grants for KAIST. In addition, Google will continue to provide more academic and career building opportunities for students, including Google internship programs.
KAIST and Google has been collaborating for years. Professor Steven Whang at the School of Electrical Engineering and Professor Sung Ju Hwang at the School of Computing won the AI-Focused Award in 2018 and conduct their researches on "Improving Generalization and Reliability of Any Deep Neural Networks" and "Automatic and Acitionable Model Analysis for TFX," respectively. Outstanding PhD students have been recognized through the PhD Fellowship Program. However, this new collaboration agreement will focus on research, academic development, and technological innovation in AI.
Google plans to support research in the fields of deep learning, cloud machine learning, and voice technologies. Google will fund the development of two educational programs based on Google open source technology each year for two years that will be used in the new AI Graduate School opening for the fall semester.
John Lee of Google Korea said, “This partnership lays a solid foundation for deeper collaboration.” President Shin added, “This partnership will not only advance Korea’s global competitiveness in AI-powered industries but also contribute to the global community by nurturing talents in this most extensive discipline.”
2019.07.22 View 10558 -
Deep Learning-Powered 'DeepEC' Helps Accurately Understand Enzyme Functions
(Figure: Overall scheme of DeepEC)
A deep learning-powered computational framework, ‘DeepEC,’ will allow the high-quality and high-throughput prediction of enzyme commission numbers, which is essential for the accurate understanding of enzyme functions.
A team of Dr. Jae Yong Ryu, Professor Hyun Uk Kim, and Distinguished Professor Sang Yup Lee at KAIST reported the computational framework powered by deep learning that predicts enzyme commission (EC) numbers with high precision in a high-throughput manner.
DeepEC takes a protein sequence as an input and accurately predicts EC numbers as an output. Enzymes are proteins that catalyze biochemical reactions and EC numbers consisting of four level numbers (i.e., a.b.c.d) indicate biochemical reactions. Thus, the identification of EC numbers is critical for accurately understanding enzyme functions and metabolism.
EC numbers are usually given to a protein sequence encoding an enzyme during a genome annotation procedure. Because of the importance of EC numbers, several EC number prediction tools have been developed, but they have room for further improvement with respect to computation time, precision, coverage, and the total size of the files needed for the EC number prediction.
DeepEC uses three convolutional neural networks (CNNs) as a major engine for the prediction of EC numbers, and also implements homology analysis for EC numbers if the three CNNs do not produce reliable EC numbers for a given protein sequence. DeepEC was developed by using a gold standard dataset covering 1,388,606 protein sequences and 4,669 EC numbers.
In particular, benchmarking studies of DeepEC and five other representative EC number prediction tools showed that DeepEC made the most precise and fastest predictions for EC numbers. DeepEC also required the smallest disk space for implementation, which makes it an ideal third-party software component.
Furthermore, DeepEC was the most sensitive in detecting enzymatic function loss as a result of mutations in domains/binding site residue of protein sequences; in this comparative analysis, all the domains or binding site residue were substituted with L-alanine residue in order to remove the protein function, which is known as the L-alanine scanning method.
This study was published online in the Proceedings of the National Academy of Sciences of the United States of America (PNAS) on June 20, 2019, entitled “Deep learning enables high-quality and high-throughput prediction of enzyme commission numbers.”
“DeepEC can be used as an independent tool and also as a third-party software component in combination with other computational platforms that examine metabolic reactions. DeepEC is freely available online,” said Professor Kim.
Distinguished Professor Lee said, “With DeepEC, it has become possible to process ever-increasing volumes of protein sequence data more efficiently and more accurately.”
This work was supported by the Technology Development Program to Solve Climate Changes on Systems Metabolic Engineering for Biorefineries from the Ministry of Science and ICT through the National Research Foundation of Korea. This work was also funded by the Bio & Medical Technology Development Program of the National Research Foundation of Korea funded by the Korean government, the Ministry of Science and ICT.
Profile:
-Professor Hyun Uk Kim (ehukim@kaist.ac.kr)
https://sites.google.com/view/ehukim
Department of Chemical and Biomolecular Engineering
-Distinguished Professor Sang Yup Lee (leesy@kaist.ac.kr)
Department of Chemical and Biomolecular Engineering
http://mbel.kaist.ac.kr
2019.07.09 View 41083