Artificial+Intelligence
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KAIST’s Robo-Dog “RaiBo” runs through the sandy beach
KAIST (President Kwang Hyung Lee) announced on the 25th that a research team led by Professor Jemin Hwangbo of the Department of Mechanical Engineering developed a quadrupedal robot control technology that can walk robustly with agility even in deformable terrain such as sandy beach.
< Photo. RAI Lab Team with Professor Hwangbo in the middle of the back row. >
Professor Hwangbo's research team developed a technology to model the force received by a walking robot on the ground made of granular materials such as sand and simulate it via a quadrupedal robot. Also, the team worked on an artificial neural network structure which is suitable in making real-time decisions needed in adapting to various types of ground without prior information while walking at the same time and applied it on to reinforcement learning. The trained neural network controller is expected to expand the scope of application of quadrupedal walking robots by proving its robustness in changing terrain, such as the ability to move in high-speed even on a sandy beach and walk and turn on soft grounds like an air mattress without losing balance.
This research, with Ph.D. Student Soo-Young Choi of KAIST Department of Mechanical Engineering as the first author, was published in January in the “Science Robotics”. (Paper title: Learning quadrupedal locomotion on deformable terrain).
Reinforcement learning is an AI learning method used to create a machine that collects data on the results of various actions in an arbitrary situation and utilizes that set of data to perform a task. Because the amount of data required for reinforcement learning is so vast, a method of collecting data through simulations that approximates physical phenomena in the real environment is widely used.
In particular, learning-based controllers in the field of walking robots have been applied to real environments after learning through data collected in simulations to successfully perform walking controls in various terrains.
However, since the performance of the learning-based controller rapidly decreases when the actual environment has any discrepancy from the learned simulation environment, it is important to implement an environment similar to the real one in the data collection stage. Therefore, in order to create a learning-based controller that can maintain balance in a deforming terrain, the simulator must provide a similar contact experience.
The research team defined a contact model that predicted the force generated upon contact from the motion dynamics of a walking body based on a ground reaction force model that considered the additional mass effect of granular media defined in previous studies.
Furthermore, by calculating the force generated from one or several contacts at each time step, the deforming terrain was efficiently simulated.
The research team also introduced an artificial neural network structure that implicitly predicts ground characteristics by using a recurrent neural network that analyzes time-series data from the robot's sensors.
The learned controller was mounted on the robot 'RaiBo', which was built hands-on by the research team to show high-speed walking of up to 3.03 m/s on a sandy beach where the robot's feet were completely submerged in the sand. Even when applied to harder grounds, such as grassy fields, and a running track, it was able to run stably by adapting to the characteristics of the ground without any additional programming or revision to the controlling algorithm.
In addition, it rotated with stability at 1.54 rad/s (approximately 90° per second) on an air mattress and demonstrated its quick adaptability even in the situation in which the terrain suddenly turned soft.
The research team demonstrated the importance of providing a suitable contact experience during the learning process by comparison with a controller that assumed the ground to be rigid, and proved that the proposed recurrent neural network modifies the controller's walking method according to the ground properties.
The simulation and learning methodology developed by the research team is expected to contribute to robots performing practical tasks as it expands the range of terrains that various walking robots can operate on.
The first author, Suyoung Choi, said, “It has been shown that providing a learning-based controller with a close contact experience with real deforming ground is essential for application to deforming terrain.” He went on to add that “The proposed controller can be used without prior information on the terrain, so it can be applied to various robot walking studies.”
This research was carried out with the support of the Samsung Research Funding & Incubation Center of Samsung Electronics.
< Figure 1. Adaptability of the proposed controller to various ground environments. The controller learned from a wide range of randomized granular media simulations showed adaptability to various natural and artificial terrains, and demonstrated high-speed walking ability and energy efficiency. >
< Figure 2. Contact model definition for simulation of granular substrates. The research team used a model that considered the additional mass effect for the vertical force and a Coulomb friction model for the horizontal direction while approximating the contact with the granular medium as occurring at a point. Furthermore, a model that simulates the ground resistance that can occur on the side of the foot was introduced and used for simulation. >
2023.01.26 View 12848 -
Overview of the 30-year history of metabolic engineering
< Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering at KAIST >
A research team comprised of Gi Bae Kim, Dr. So Young Choi, Dr. In Jin Cho, Da-Hee Ahn, and Distinguished Professor Sang Yup Lee from the Department of Chemical and Biomolecular Engineering at KAIST reported the 30-year history of metabolic engineering, highlighting examples of recent progress in the field and contributions to sustainability and health. Their paper “Metabolic engineering for sustainability and health” was published online in the 40th anniversary special issue of Trends in Biotechnology on January 10, 2023.
Metabolic engineering, a discipline of engineering that modifies cell phenotypes through molecular and genetic-level manipulations to improve cellular activities, has been studied since the early 1990s, and has progressed significantly over the past 30 years. In particular, metabolic engineering has enabled the engineering of microorganisms for the development of microbial cell factories capable of efficiently producing chemicals and materials as well as degrading recalcitrant contaminants.
This review article revisited how metabolic engineering has advanced over the past 30 years, from the advent of genetic engineering techniques such as recombinant DNA technologies to recent breakthroughs in systems metabolic engineering and data science aided by artificial intelligence. The research team highlighted momentous events and achievements in metabolic engineering, providing both trends and future directions in the field. Metabolic engineering’s contributions to bio-based sustainable chemicals and clean energy, health, and bioremediation were also reviewed. Finally, the research team shared their perspectives on the future challenges impacting metabolic engineering than must be overcome in order to achieve advancements in sustainability and health.
Distinguished Professor Sang Yup Lee said, “Replacing fossil resource-based chemical processes with bio-based sustainable processes for the production of chemicals, fuels, and materials using metabolic engineering has become our essential task for the future. By looking back on the 30+ years of metabolic engineering, we aimed to highlight the contributions of metabolic engineering to achieve sustainability and good health.” He added, “Metabolic engineering will play an increasingly important role as a key solution to the climate crisis, environmental pollution, food and energy shortages, and health problems in aging societies.”
< Figure: Metabolic Engineering Timeline >
2023.01.25 View 8490 -
UAE Space Program Leaders named to be the 1st of the honorees of KAIST Alumni Association's special recognition for graduates of foreign nationality
The KAIST Alumni Association (Chairman, Chil-Hee Chung) announced on the 12th that the winners of the 2023 KAIST Distinguished Alumni Award and International Alumni Award has been selected.
The KAIST Distinguished Alumni Award, which produced the first recipient in 1992, is an award given to alumni who have contributed to the development of the nation and society, or who have glorified the honor of their alma mater with outstanding academic achievements and social and/or communal contributions.
On a special note, this year, there has been an addition to the honors, “the KAIST Distinguished International Alumni Award” to honor and encourage overseas alumni who are making their marks in the international community that will boost positive recognition of KAIST in the global setting and will later become a bridge that will expedite Korea's international efforts in the future.
As of 2022, the number of international students who succeeded in earning KAIST degrees has exceeded 1,700, and they are actively doing their part back in their home countries as leaders in various fields in which they belong, spanning from science and technology, to politics, industry and other corners of the society.
(From left) Omran Sharaf, the Assistant Minister of UAE Foreign Affairs and International Cooperation for Advanced Science and Technology, Amer Al Sayegh the Director General of Space Project at MBRSC, and Mohammed Al Harmi the Director General of Administration at MBRSC (Photos provided by the courtesy of MBRSC)
To celebrate and honor their outstanding achievements, the KAIST Alumni Association selected a team of three alumni of the United Arab Emirates (UAE) to receive the Distinguished International Alumni Award for the first time. The named honorees are Omran Sharaf, a master’s graduate from the Graduate School of Science and Technology Policy, and Amer Al Sayegh and Mohammed Al Harmi, master’s graduates of the Department of Aerospace Engineering - all three of the class of 2013 in leading positions in the UAE space program to lead the advancement of the science and technology of the country.
Currently, the three alums are in directorship of the Mohammed Bin Rashid Space Centre (MBRSC) with Mr. Omran Sharaf, who has recently been appointed as the Assistant Minister in charge of Advanced Science and Technology at the UAE Ministry of Foreign Affairs and International Cooperation, being the Project Director of the Emirates Mars Mission of MBRSC and Mr. Amer Al Sayegh in the Director General position in charge of Space Project and Mr. Mohammed Al Harmi, the Director General of Administration, at MBRSC.
They received technology transfer from “SatRec I”, Korea's first satellite system exporter and KAIST alumni company, for about 10 years from 2006, while carrying out their master’s studies at the same time.
Afterwards, they returned to UAE to lead the Emirates Mars Mission, which is already showing tangible progress including the successful launch of the Mars probe "Amal" (ال امل, meaning ‘Hope’ in Arabic), which was the first in the Arab world and the fifth in the world to successfully enter into orbit around Mars, and the UAE’s first independently developed Earth observation satellite "KhalifaSat".
An official from the KAIST Alumni Association said, "We selected the Distinguished International Alumni after evaluating their industrious leadership in promoting various space industry strategies, ranging from the development of Mars probes and Earth observation satellites, as well as lunar exploration, asteroid exploration, and Mars residence plans."
(From left) Joo-Sun Choi, President & CEO of Samsung Display Co. Ltd., Jung Goo Cho, the CEO of Green Power Co. Ltd., Jong Seung Park, the President of Agency for Defense Development (ADD), Kyunghyun Cho, Professor of New York University (NYU)
Also, four of the Korean graduates, Joo-Sun Choi, the CEO of Samsung Display, Jung Goo Cho, the CEO of Green Power Co. Ltd., Jong Seung Park, the President of Agency for Defense Development (ADD), and Kyunghyun Cho, a Professor of New York University (NYU), were selected as the winners of the “Distinguished Alumni Award”.
Mr. Joo-Sun Choi (Electrical and Electronic Engineering, M.S. in 1989, Ph.D. in 1995), the CEO of Samsung Display, led the successful development and mass-production of the world's first ultra-high-definition QD-OLED Displays, and preemptively transformed the structure of business of the industry and has been leading the way in technological innovation.
Mr. Jung Goo Cho (Electrical and Electronic Engineering, M.S. in 1988, Ph.D. in 1992), the CEO of Green Power Co. Ltd., developed wireless power technology for the first time in Korea in the early 2000s and applied it to semiconductor/display lines and led the wireless power charging technology in various fields, such as developing KAIST On-Line Electric Vehicles (OLEV) and commercializing the world's first wireless charger for 11kW electric vehicles.
Mr. Jong Seung Park (Mechanical Engineering, M.S. in 1988, Ph.D., in 1991), The President of ADD is an expert with abundant science and technology knowledge and organizational management capabilities. He is contributing greatly to national defense and security through science and technology.
Mr. Kyunghyun Cho (Computer Science, B.S., in 2009), the Professor of Computer Science and Data Science at NYU, is a world-renowned expert in Artificial Intelligence (AI), advancing the concept of 'Neural Machine Translation' in the field of natural language processing, to make great contributions to AI translation technology and related industries.
Chairman Chil-Hee Chung, the 26th Chair of KAIST Alumni Association “As each year goes by, I feel that the influence of KAIST alumni goes beyond science and technology to affect our society as a whole.” He went on to say, “This year, as it was more meaningful to extend the award to honor the international members of our Alums, we look forward to seeing more of our alumni continuing their social and academic endeavors to play an active role in the global stage in taking on the global challenges.”
The Ceremony for KAIST Distinguished Alumni and International Alumni Award Honorees will be conducted at the Annual New Year’s Event of KAIST Alumni Association for 2023 to be held on Friday, January 13th, at the Grand InterContinental Seoul Parnas.
2023.01.12 View 11646 -
KAIST-NYU Digital Governance Forum Held
KAIST (President Kwang Hyung Lee) held the 'KAIST-NYU Digital Governance Forum' at the Korea Press Center in the morning of October 28th, 2022.
This forum was held in continuation to discuss the objectives of the 'Digital Vision Forum' that was hosted by New York University (NYU) back in September in the United States, and is the first public event to be held through joint efforts by KAIST and NYU since the signage of the 'KAIST-NYU Joint Campus' was presented at the New York forum.
< Signage of KAIST-NYU Joint Campus >
This forum was promoted based on the consensus of the two universities to create an international forum of solidarity to solve global challenges and seek new governance in the era of digital transformation.
Digital innovation technology is expected to bring economic and industrial benefits as well as political, social and ethical risks such as accelerating the digital divide, among others. In particular, in a time of global digital transformation, as the competition for digital and AI supremacy based on technology nationalism catches fire, there is an emergent need for a global governance system in which digital innovation and the value of freedom co-exist. With the consensus formed through this forum with NYU, KAIST plans to focus on detailing the vision for future digital cooperation that encompasses various stakeholders in our society.
To this end, President Kwang Hyung Lee of KAIST and President Andrew Hamilton of NYU led the forum with keynote addresses with President Hamilton taking part virtually, followed by NYU Professor Matthew Liao, a world-renowned scholar specialized in the ethics in the field of science and technology, and Jason Allford, Special Representative of the World Bank Group to Korea, presenting on relevant topics for discussion.
From KAIST, Professor Kyung Ryul Park of the Graduate School of Science and Technology Policy and Director So Young Kim of the Korea Policy Center for the Fourth Industrial Revolution, followed with their presentations. A panel discussion on governance in the period of digital transformation was also held, led by Professor Dongman Lee, the Dean of the College of Engineering.
To kick things off, Professor Matthew Liao of NYU proposed a normative system that can harmonize technology and social ethics while explaining various ethical issues following the technological development of artificial intelligence.
Jason Allford, Special Representative of the World Bank Group to Korea, outlined the changing roles of government in the digital era from the perspective of transparency and government efficiency and explained global development strategies through various cases of digital innovations by international organizations.
Professor Kyung Ryul Park of the Graduate School of Science and Technology Policy at KAIST emphasized that the core of new digital governance is not only innovative technology but also the participation and harmony of various stakeholders at home at abroad and brought up the importance of multi-dimensional international solidarity based on digital transformation that goes beyond the flat ‘technological geopolitics.’
Professor So Young Kim, the Director of the Korea Policy Center for the Fourth Industrial Revolution at KAIST, commented on the current government's digital platform strategy and emphasized the need for a leading digital transformation strategy that goes beyond the governance of the existing government.
Edward Mermelstein, the Commissioner for International Affairs of New York City, said, “The City of New York, shall also provide active support for the cooperative governance initiative organized by KAIST in Korea. As the conversation progresses further, we can draw up plans to organize international organizations to support the effort, likely to be named ‘Digitization for Good’, and we can go on to consider future collaboration,” to express the city’s willingness and anticipation for active cooperation.
Andrew Hamilton, the President of NYU, said "NYU is thrilled by the partnership we are embarking upon with KAIST, which goes hand in hand with our global tradition, and is based upon our bedrock commitment to the free movement of people and ideas.” He added that “As data-driven software, AI, and social networks become even more essential parts of our daily lives, I am confident that today’s discussions will lead to new and promising insights.”
President Kwang Hyung Lee of KAIST said, “It is significant that we are to cooperate with New York University to prepare a venue to assess the changes of the forth coming era at a time in which digital technology, government platforms, and public data are attracting attention as a medium that can create various social and economic value.”
President Lee added, “KAIST and NYU, the two institutions in cross-continental partnership to lead innovations in higher education via the creation of a joint campus, have joined forces to host this forum to create an opportunity to envision the future of a cooperative governance that is inclusive of key players like the government, businesses, the civil societies, academia, and international organizations.”
The 'KAIST-NYU Digital Governance Forum' was broadcast live on KAIST’s Official YouTube Channel from 9:30 am on the 28th of October (Korea Standard Time) with simultaneous interpretation provided in both Korean and English. A recording of the video is available online for everyone to watch free of charge.
KAIST’s YouTube Channel: https://www.youtube.com/c/KAISTofficial
Forum Recording with English interpretation: https://youtu.be/Vs31i7BtfEw
2022.10.28 View 6117 -
NYC-KAIST Cooperation Agreement Signed in New York for KAIST NYU Joint Campus
A ceremony was held to celebrate the signing of the Cooperative Agreement between NYC and KAIST and the presentation of the signage for KAIST NYU Joint Campus at NYU’s Kimmel Center in Manhattan.
KAIST President Kwang Hyung Lee (left) and NYU President Andrew Hamilton (right)
KAIST (President Kwang Hyung Lee) signed a cooperative agreement with the City of New York and had an official showing of the signage for the Joint Campus of KAIST and New York University (NYU) on September 21 at 4:00 pm (Eastern Standard Time) at NYU’s Kimmel Center in New York City with the NYC Mayor Eric Adams, the Korean Minister of Science and ICT Dr. Lee Jong-ho, NYU Chairman William Berkley, NYU President Andrew Hamilton, and other distinguished guests in attendance.
KAIST and NYU signed a Memorandum of Understanding in June about building a joint campus in an effort to educate global talent. As a follow-up measure, NYU has provided KAIST with space to begin joint research programs and held a ceremony to present the signage designed for the future KAIST NYU Campus. In line with these efforts, KAIST has also signed an agreement with New York City, the administrative authority in charge of the establishment of the campus, for mutual cooperation.
NYU is a prestigious university headquartered in Manhattan, New York. It has nurtured outstanding talents in the humanities, art, and basic sciences, including 38 Nobel Prize winners, 5 Fields Prize winners, 26 Pulitzer Prize winners, and 38 Academy Award winners to be deserving of the evaluation.
The proposed joint campus is to be centered on science, technology, engineering, and mathematics (STEM) by combining NYU's excellent basic sciences and convergence research capabilities with KAIST's globally renowned science and technology capabilities. The joint initiative is expected to launch in 2023; its programs will focus on areas such as AI Basic Science, AI Convergence Brain Science, AI-Applied Cyber Security, Cyber Security, and Sustainable High-Tech Smart City/Climate Change in order to lead the Digital Era and to solve the problems that surfaced following the COVID-19 pandemic. In addition, in order to prepare for the Post-AI Era, it was decided to create the “New Engineering” program for undergraduate program that employs a hyper-convergence learning model that combines project-based, problem-solving learning (PBL, PSL) pedagogy.
▲ Biomedical Engineering- Research and development of technology to respond to the entire cycle (prevention-treatment-diagnosis-prediction) for a new infectious disease (Disease X) by converging new technologies such as IT and NT with biomedical technologies
▲ AI Convergence Neuroscience- Research on brain-machine interaction and brain-based machine learning through AI technology convergence
▲ AI Science- Algorithm development and in-depth research in preparation for the post AI era
▲ Sustainability and Climate Change- R&DB for advanced smart cities, sustainability for the global environment and carbon zero
▲ Next-generation Wireless Communications- From ICT to AIT: Research on 6G/7G related technologies, new communications theories, and etc.
▲ Cyber Security- Advanced research on protection of digital information and information safety/reliability
KAIST President Kwang Hyung Lee (left) and NYC Mayor Eric Adams (right)
The KAIST NYU Joint Campus has started enlisting professors and researchers from both institutions to participate in the collaboration. The campus will also function as the headquarter that will oversee the operation of the joint research program. At Daejeon, KAIST is also setting up a location for NYU on its main campus to provide space for NYU researchers upon their visit to KAIST.
The KAIST NYU Joint Campus, which has begun to take basic shape with the space for collaboration rendered this time, is to be upgraded to “KAIST New York Campus” in the future to function also as an industry-academic cooperation campus in which that promotes strategic cooperation with industries and expands start-up opportunities. To this end, the related procedures from the detailing of the establishment plans through a preliminary feasibility studies, to deliberation and decision on whether to proceed with the establishment by the KAIST Board of Trustees, will be taken.
The KAIST NYU Campus is expected to serve as a stepping stone for the outstanding talents of KAIST to pursue their dreams in the global market and research environment while seizing the attention of the world-class talents drawn to New York at the same time. In addition, by combining NYU's strong basic academic capabilities with KAIST’s strengths, it is expected to contribute to achieving 'global innovation' by creating synergies in various fields such as education, research, and entrepreneurship. The future KAIST-NYU Campus is also expected to encompass an industry-academic cooperation campus with industrial partners and startups.
Meanwhile, KAIST is planning to expand its excellent scientific and technological capabilities to the global stage through the cooperative agreement with New York City, and to prepare a pathway for KAIST students, faculty, and startups to enter their respective fields in the global markets. In the future, KAIST plans to explore areas of cooperation in different fields, such as education, economy, society, and culture, to prepare and implement detailed cooperation plans.
< KAIST-New York City Cooperation Items (Example) >
▲ Education: Joint degree program with a university in New York City, training of key talents in the field of artificial intelligence, etc.
▲ Economy: A hub for technology startups, job creation in the tech sector, etc.
▲ Society: Economics, finance, media-related engineering research, etc.
▲ Culture: Diversity-based culture and art-tech research, etc.▲ Etc: Joint research in the field of artificial intelligence healthcare, etc.
As a global mecca for startups, education, and investment, New York has a well-developed global network for cultural diversity and successful career development, and has great power to attract various resources including funds and talented individuals. Based on this, it has established itself as a mecca of global tech companies and global top media groups, and is building the reputation as 'Silicon Alley' in addition to its legends of the ‘Wall Street'.
Dr. Andrew Hamilton, the president of NYU, said, “We’re delighted by our newly established partnership with KAIST. We see great potential in the opportunities to collaborate on development of courses, research, cutting edge technologies, university-level courses, degrees, entrepreneurship initiatives and industrial partnerships, and exchanges. We believe this partnership is very much in line with NYU’s commitment to global engagement and will make important contributions to New York’s tech sector. It’s exciting to think how much NYU and KAIST have much to learn from one another, and how much we may accomplish together.”
New York City Mayor Eric Adams said, “We’re proud to have helped facilitate this partnership between KAIST and New York University, which will be a real win for students and help drive continued innovation in our city.” He added, “From the time that senior members of our administration learned about this opportunity during a recent trip to South Korea, we have worked closely with KAIST to develop strategies for increasing their presence and investments in New York. This is the start of a relationship that I am confident will bring even more academic, business, and technological opportunities to the five boroughs.”
Dr. Kwang Hyung Lee, the president of KAIST, urged, “Based on the KAIST-NYU partnership, we must create an interdisciplinary hyper-convergence model of collaboration and use cutting-edge tools to create an innovative model for new type of problem-solving engineering education to prepare to solve the challenges facing the world.” He went on to stress, “The new fusion engineering degree program will leverage the unique strengths of the two institutions to provide a uniquely colored education not found anywhere else.” In addition, he added, “KAIST will utilize the advantages that are unique to the global city of New York to contribute to advancing the science and technology research in New York City and creating jobs in the tech sector to lead the renaissance of Silicon Alley.”
2022.09.27 View 11489 -
Shaping the AI Semiconductor Ecosystem
- As the marriage of AI and semiconductor being highlighted as the strategic technology of national enthusiasm, KAIST's achievements in the related fields accumulated through top-class education and research capabilities that surpass that of peer universities around the world are standing far apart from the rest of the pack.
As Artificial Intelligence Semiconductor, or a system of semiconductors designed for specifically for highly complicated computation need for AI to conduct its learning and deducing calculations, (hereafter AI semiconductors) stand out as a national strategic technology, the related achievements of KAIST, headed by President Kwang Hyung Lee, are also attracting attention. The Ministry of Science, ICT and Future Planning (MSIT) of Korea initiated a program to support the advancement of AI semiconductor last year with the goal of occupying 20% of the global AI semiconductor market by 2030. This year, through industry-university-research discussions, the Ministry expanded to the program with the addition of 1.2 trillion won of investment over five years through 'Support Plan for AI Semiconductor Industry Promotion'. Accordingly, major universities began putting together programs devised to train students to develop expertise in AI semiconductors.
KAIST has accumulated top-notch educational and research capabilities in the two core fields of AI semiconductor - Semiconductor and Artificial Intelligence. Notably, in the field of semiconductors, the International Solid-State Circuit Conference (ISSCC) is the world's most prestigious conference about designing of semiconductor integrated circuit. Established in 1954, with more than 60% of the participants coming from companies including Samsung, Qualcomm, TSMC, and Intel, the conference naturally focuses on practical value of the studies from the industrial point-of-view, earning the nickname the ‘Semiconductor Design Olympics’. At such conference of legacy and influence, KAIST kept its presence widely visible over other participating universities, leading in terms of the number of accepted papers over world-class schools such as Massachusetts Institute of Technology (MIT) and Stanford for the past 17 years.
Number of papers published at the InternationalSolid-State Circuit Conference (ISSCC) in 2022 sorted by nations and by institutions
Number of papers by universities presented at the International Solid-State Circuit Conference (ISCCC) in 2006~2022
In terms of the number of papers accepted at the ISSCC, KAIST ranked among top two universities each year since 2006. Looking at the average number of accepted papers over the past 17 years, KAIST stands out as an unparalleled leader. The average number of KAIST papers adopted during the period of 17 years from 2006 through 2022, was 8.4, which is almost double of that of competitors like MIT (4.6) and UCLA (3.6). In Korea, it maintains the second place overall after Samsung, the undisputed number one in the semiconductor design field. Also, this year, KAIST was ranked first among universities participating at the Symposium on VLSI Technology and Circuits, an academic conference in the field of integrated circuits that rivals the ISSCC.
Number of papers adopted by the Symposium on VLSI Technology and Circuits in 2022 submitted from the universities
With KAIST researchers working and presenting new technologies at the frontiers of all key areas of the semiconductor industry, the quality of KAIST research is also maintained at the highest level. Professor Myoungsoo Jung's research team in the School of Electrical Engineering is actively working to develop heterogeneous computing environment with high energy efficiency in response to the industry's demand for high performance at low power. In the field of materials, a research team led by Professor Byong-Guk Park of the Department of Materials Science and Engineering developed the Spin Orbit Torque (SOT)-based Magnetic RAM (MRAM) memory that operates at least 10 times faster than conventional memories to suggest a way to overcome the limitations of the existing 'von Neumann structure'.
As such, while providing solutions to major challenges in the current semiconductor industry, the development of new technologies necessary to preoccupy new fields in the semiconductor industry are also very actively pursued. In the field of Quantum Computing, which is attracting attention as next-generation computing technology needed in order to take the lead in the fields of cryptography and nonlinear computation, Professor Sanghyeon Kim's research team in the School of Electrical Engineering presented the world's first 3D integrated quantum computing system at 2021 VLSI Symposium. In Neuromorphic Computing, which is expected to bring remarkable advancements in the field of artificial intelligence by utilizing the principles of the neurology, the research team of Professor Shinhyun Choi of School of Electrical Engineering is developing a next-generation memristor that mimics neurons.
The number of papers by the International Conference on Machine Learning (ICML) and the Conference on Neural Information Processing Systems (NeurIPS), two of the world’s most prestigious academic societies in the field of artificial intelligence (KAIST 6th in the world, 1st in Asia, in 2020)
The field of artificial intelligence has also grown rapidly. Based on the number of papers from the International Conference on Machine Learning (ICML) and the Conference on Neural Information Processing Systems (NeurIPS), two of the world's most prestigious conferences in the field of artificial intelligence, KAIST ranked 6th in the world in 2020 and 1st in Asia. Since 2012, KAIST's ranking steadily inclined from 37th to 6th, climbing 31 steps over the period of eight years. In 2021, 129 papers, or about 40%, of Korean papers published at 11 top artificial intelligence conferences were presented by KAIST. Thanks to KAIST's efforts, in 2021, Korea ranked sixth after the United States, China, United Kingdom, Canada, and Germany in terms of the number of papers published by global AI academic societies.
Number of papers from Korea (and by KAIST) published at 11 top conferences in the field of artificial intelligence in 2021
In terms of content, KAIST's AI research is also at the forefront. Professor Hoi-Jun Yoo's research team in the School of Electrical Engineering compensated for the shortcomings of the “edge networks” by implementing artificial intelligence real-time learning networks on mobile devices. In order to materialize artificial intelligence, data accumulation and a huge amount of computation is required. For this, a high-performance server takes care of massive computation, and for the user terminals, the “edge network” that collects data and performs simple computations are used. Professor Yoo's research greatly increased AI’s processing speed and performance by allotting the learning task to the user terminal as well.
In June, a research team led by Professor Min-Soo Kim of the School of Computing presented a solution that is essential for processing super-scale artificial intelligence models. The super-scale machine learning system developed by the research team is expected to achieve speeds up to 8.8 times faster than Google's Tensorflow or IBM's System DS, which are mainly used in the industry.
KAIST is also making remarkable achievements in the field of AI semiconductors. In 2020, Professor Minsoo Rhu's research team in the School of Electrical Engineering succeeded in developing the world's first AI semiconductor optimized for AI recommendation systems. Due to the nature of the AI recommendation system having to handle vast amounts of contents and user information, it quickly meets its limitation because of the information bottleneck when the process is operated through a general-purpose artificial intelligence system. Professor Minsoo Rhu's team developed a semiconductor that can achieve a speed that is 21 times faster than existing systems using the 'Processing-In-Memory (PIM)' technology. PIM is a technology that improves efficiency by performing the calculations in 'RAM', or random-access memory, which is usually only used to store data temporarily just before they are processed. When PIM technology is put out on the market, it is expected that fortify competitiveness of Korean companies in the AI semiconductor market drastically, as they already hold great strength in the memory area.
KAIST does not plan to be complacent with its achievements, but is making various plans to further the distance from the competitors catching on in the fields of artificial intelligence, semiconductors, and AI semiconductors. Following the establishment of the first artificial intelligence research center in Korea in 1990, the Kim Jaechul AI Graduate School was opened in 2019 to sustain the supply chain of the experts in the field. In 2020, Artificial Intelligence Semiconductor System Research Center was launched to conduct convergent research on AI and semiconductors, which was followed by the establishment of the AI Institutes to promote “AI+X” research efforts.
Based on the internal capabilities accumulated through these efforts, KAIST is also making efforts to train human resources needed in these areas. KAIST established joint research centers with companies such as Naver, while collaborating with local governments such as Hwaseong City to simultaneously nurture professional manpower. Back in 2021, KAIST signed an agreement to establish the Semiconductor System Engineering Department with Samsung Electronics and are preparing a new semiconductor specialist training program. The newly established Department of Semiconductor System Engineering will select around 100 new students every year from 2023 and provide special scholarships to all students so that they can develop their professional skills. In addition, through close cooperation with the industry, they will receive special support which includes field trips and internships at Samsung Electronics, and joint workshops and on-site training.
KAIST has made a significant contribution to the growth of the Korean semiconductor industry ecosystem, producing 25% of doctoral workers in the domestic semiconductor field and 20% of CEOs of mid-sized and venture companies with doctoral degrees. With the dawn coming up on the AI semiconductor ecosystem, whether KAIST will reprise the pivotal role seems to be the crucial point of business.
2022.08.05 View 10425 -
An AI-based, Indoor/Outdoor-Integrated (IOI) GPS System to Bring Seismic Waves in the Terrains of Positioning Technology
KAIST breaks new grounds in positioning technology with an AI-integrated GPS board that works both indoors and out
KAIST (President Kwang Hyung Lee) announced on the 8th that Professor Dong-Soo Han's research team (Intelligent Service Integration Lab) from the School of Computing has developed a GPS system that works both indoors and outdoors with quality precision regardless of the environment.
This Indoor/Outdoor-Integrated GPS System, or IOI GPS System, for short, uses the GPS signals outdoors and estimates locations indoors using signals from multiple sources like an inertial sensor, pressure sensors, geomagnetic sensors, and light sensors. To this end, the research team developed techniques to detect environmental changes such as entering a building, and methods to detect entrances, ground floors, stairs, elevators and levels of buildings by utilizing artificial intelligence techniques. Various landmark detecting techniques were also incorporated with pedestrian dead reckoning (PDR), a navigation tool for pedestrians, to devise the so-called “Sensor-Fusion Positioning Algorithm”.
To date, it was common to estimate locations based on wireless LAN signals or base station signals in a space where the GPS signal could not reach. However, the IOI GPS enables positioning even in buildings without signals nor indoor maps.
The algorithm developed by the research team can provide accurate floor information within a building where even big tech companies like Google and Apple's positioning services do not provide. Unlike other positioning methods that rely on visual data, geomagnetic positioning techniques, or wireless LAN, this system also has the advantage of not requiring any prior preparation. In other words, the foundation to enable the usage of a universal GPS system that works both indoors and outdoors anywhere in the world is now ready.
The research team also produced a circuit board for the purpose of operating the IOI GPS System, mounted with chips to receive and process GPS, Wi-Fi, and Bluetooth signals, along with an inertial sensor, a barometer, a magnetometer, and a light sensor. The sensor-fusion positioning algorithm the lab has developed is also incorporated in the board.
When the accuracy of the IOI GPS board was tested in the N1 building of KAIST’s main campus in Daejeon, it achieved an accuracy of about 95% in floor estimation and an accuracy of about 3 to 6 meters in distance estimation. As for the indoor/outdoor transition, the navigational mode change was completed in about 0.3 seconds. When it was combined with the PDR technique, the estimation accuracy improved further down to a scope of one meter.
The research team is now working on assembling a tag with a built-in positioning board and applying it to location-based docent services for visitors at museums, science centers, and art galleries. The IOI GPS tag can be used for the purpose of tracking children and/or the elderly, and it can also be used to locate people or rescue workers lost in disaster-ridden or hazardous sites. On a different note, the sensor-fusion positioning algorithm and positioning board for vehicles are also under development for the tracking of vehicles entering indoor areas like underground parking lots.
When the IOI GPS board for vehicles is manufactured, the research team will work to collaborate with car manufacturers and car rental companies, and will also develop a sensor-fusion positioning algorithm for smartphones. Telecommunication companies seeking to diversify their programs in the field of location-based services will also be interested in the use the IOI GPS.
Professor Dong-Soo Han of the School of Computing, who leads the research team, said, “This is the first time to develop an indoor/outdoor integrated GPS system that can pinpoint locations in a building where there is no wireless signal or an indoor map, and there are an infinite number of areas it can be applied to. When the integration with the Korea Augmentation Satellite System (KASS) and the Korean GPS (KPS) System that began this year, is finally completed, Korea can become the leader in the field of GPS both indoors and outdoors, and we also have plans to manufacture semi-conductor chips for the IOI GPS System to keep the tech-gap between Korea and the followers.”
He added, "The guidance services at science centers, museums, and art galleries that uses IOI GPS tags can provide a set of data that would be very helpful for analyzing the visitors’ viewing traces. It is an essential piece of information required when the time comes to decide when to organize the next exhibit. We will be working on having it applied to the National Science Museum, first.”
The projects to develop the IOI GPS system and the trace analysis system for science centers were supported through Science, Culture, Exhibits and Services Capability Enhancement Program of the Ministry of Science and ICT.
Profile: Dong-Soo Han, Ph.D.Professorddsshhan@kaist.ac.krhttp://isilab.kaist.ac.kr
Intelligent Service Integration Lab.School of Computing
http://kaist.ac.kr/en/
Korea Advanced Institute of Science and Technology (KAIST)Daejeon, Republic of Korea
2022.07.13 View 9176 -
PICASSO Technique Drives Biological Molecules into Technicolor
The new imaging approach brings current imaging colors from four to more than 15 for mapping overlapping proteins
Pablo Picasso’s surreal cubist artistic style shifted common features into unrecognizable scenes, but a new imaging approach bearing his namesake may elucidate the most complicated subject: the brain. Employing artificial intelligence to clarify spectral color blending of tiny molecules used to stain specific proteins and other items of research interest, the PICASSO technique, allows researchers to use more than 15 colors to image and parse our overlapping proteins.
The PICASSO developers, based in Korea, published their approach on May 5 in Nature Communications.
Fluorophores — the staining molecules — emit specific colors when excited by a light, but if more than four fluorophores are used, their emitted colors overlap and blend. Researchers previously developed techniques to correct this spectral overlap by precisely defining the matrix of mixed and unmixed images. This measurement depends on reference spectra, found by identifying clear images of only one fluorophore-stained specimen or of multiple, identically prepared specimens that only contain a single fluorophore each.
“Such reference spectra measurement could be complicated to perform in highly heterogeneous specimens, such as the brain, due to the highly varied emission spectra of fluorophores depending on the subregions from which the spectra were measured,” said co-corresponding author Young-Gyu Yoon, professor in the School of Electrical Engineering at KAIST. He explained that the subregions would each need their own spectra reference measurements, making for an inefficient, time-consuming process. “To address this problem, we developed an approach that does not require reference spectra measurements.”
The approach is the “Process of ultra-multiplexed Imaging of biomolecules viA the unmixing of the Signals of Spectrally Overlapping fluorophores,” also known as PICASSO. Ultra-multiplexed imaging refers to visualizing the numerous individual components of a unit. Like a cinema multiplex in which each theater plays a different movie, each protein in a cell has a different role. By staining with fluorophores, researchers can begin to understand those roles.
“We devised a strategy based on information theory; unmixing is performed by iteratively minimizing the mutual information between mixed images,” said co-corresponding author Jae-Byum Chang, professor in the Department of Materials Science and Engineering, KAIST. “This allows us to get away with the assumption that the spatial distribution of different proteins is mutually exclusive and enables accurate information unmixing.”
To demonstrate PICASSO’s capabilities, the researchers applied the technique to imaging a mouse brain. With a single round of staining, they performed 15-color multiplexed imaging of a mouse brain. Although small, mouse brains are still complex, multifaceted organs that can take significant resources to map. According to the researchers, PICASSO can improve the capabilities of other imaging techniques and allow for the use of even more fluorophore colors.
Using one such imaging technique in combination with PICASSO, the team achieved 45-color multiplexed imaging of the mouse brain in only three staining and imaging cycles, according to Yoon.
“PICASSO is a versatile tool for the multiplexed biomolecule imaging of cultured cells, tissue slices and clinical specimens,” Chang said. “We anticipate that PICASSO will be useful for a broad range of applications for which biomolecules’ spatial information is important. One such application the tool would be useful for is revealing the cellular heterogeneities of tumor microenvironments, especially the heterogeneous populations of immune cells, which are closely related to cancer prognoses and the efficacy of cancer therapies.”
The Samsung Research Funding & Incubation Center for Future Technology supported this work. Spectral imaging was performed at the Korea Basic Science Institute Western Seoul Center.
-PublicationJunyoung Seo, Yeonbo Sim, Jeewon Kim, Hyunwoo Kim, In Cho, Hoyeon Nam, Yong-Gyu Yoon, Jae-Byum Chang, “PICASSO allows ultra-multiplexed fluorescence imaging of spatiallyoverlapping proteins without reference spectra measurements,” May 5, Nature Communications (doi.org/10.1038/s41467-022-30168-z)
-ProfileProfessor Jae-Byum ChangDepartment of Materials Science and EngineeringCollege of EngineeringKAIST
Professor Young-Gyu YoonSchool of Electrical EngineeringCollege of EngineeringKAIST
2022.06.22 View 8251 -
Neuromorphic Memory Device Simulates Neurons and Synapses
Simultaneous emulation of neuronal and synaptic properties promotes the development of brain-like artificial intelligence
Researchers have reported a nano-sized neuromorphic memory device that emulates neurons and synapses simultaneously in a unit cell, another step toward completing the goal of neuromorphic computing designed to rigorously mimic the human brain with semiconductor devices.
Neuromorphic computing aims to realize artificial intelligence (AI) by mimicking the mechanisms of neurons and synapses that make up the human brain. Inspired by the cognitive functions of the human brain that current computers cannot provide, neuromorphic devices have been widely investigated. However, current Complementary Metal-Oxide Semiconductor (CMOS)-based neuromorphic circuits simply connect artificial neurons and synapses without synergistic interactions, and the concomitant implementation of neurons and synapses still remains a challenge. To address these issues, a research team led by Professor Keon Jae Lee from the Department of Materials Science and Engineering implemented the biological working mechanisms of humans by introducing the neuron-synapse interactions in a single memory cell, rather than the conventional approach of electrically connecting artificial neuronal and synaptic devices.
Similar to commercial graphics cards, the artificial synaptic devices previously studied often used to accelerate parallel computations, which shows clear differences from the operational mechanisms of the human brain. The research team implemented the synergistic interactions between neurons and synapses in the neuromorphic memory device, emulating the mechanisms of the biological neural network. In addition, the developed neuromorphic device can replace complex CMOS neuron circuits with a single device, providing high scalability and cost efficiency.
The human brain consists of a complex network of 100 billion neurons and 100 trillion synapses. The functions and structures of neurons and synapses can flexibly change according to the external stimuli, adapting to the surrounding environment. The research team developed a neuromorphic device in which short-term and long-term memories coexist using volatile and non-volatile memory devices that mimic the characteristics of neurons and synapses, respectively. A threshold switch device is used as volatile memory and phase-change memory is used as a non-volatile device. Two thin-film devices are integrated without intermediate electrodes, implementing the functional adaptability of neurons and synapses in the neuromorphic memory.
Professor Keon Jae Lee explained, "Neurons and synapses interact with each other to establish cognitive functions such as memory and learning, so simulating both is an essential element for brain-inspired artificial intelligence. The developed neuromorphic memory device also mimics the retraining effect that allows quick learning of the forgotten information by implementing a positive feedback effect between neurons and synapses.”
This result entitled “Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse” was published in the May 19, 2022 issue of Nature Communications.
-Publication:Sang Hyun Sung, Tae Jin Kim, Hyera Shin, Tae Hong Im, and Keon Jae Lee (2022) “Simultaneous emulation of synaptic and intrinsic plasticity using a memristive synapse,” Nature Communications May 19, 2022 (DOI: 10.1038/s41467-022-30432-2)
-Profile:Professor Keon Jae Leehttp://fand.kaist.ac.kr
Department of Materials Science and EngineeringKAIST
2022.05.20 View 11184 -
Energy-Efficient AI Hardware Technology Via a Brain-Inspired Stashing System
Researchers demonstrate neuromodulation-inspired stashing system for the energy-efficient learning of a spiking neural network using a self-rectifying memristor array
Researchers have proposed a novel system inspired by the neuromodulation of the brain, referred to as a ‘stashing system,’ that requires less energy consumption. The research group led by Professor Kyung Min Kim from the Department of Materials Science and Engineering has developed a technology that can efficiently handle mathematical operations for artificial intelligence by imitating the continuous changes in the topology of the neural network according to the situation. The human brain changes its neural topology in real time, learning to store or recall memories as needed. The research group presented a new artificial intelligence learning method that directly implements these neural coordination circuit configurations.
Research on artificial intelligence is becoming very active, and the development of artificial intelligence-based electronic devices and product releases are accelerating, especially in the Fourth Industrial Revolution age. To implement artificial intelligence in electronic devices, customized hardware development should also be supported. However most electronic devices for artificial intelligence require high power consumption and highly integrated memory arrays for large-scale tasks. It has been challenging to solve these power consumption and integration limitations, and efforts have been made to find out how the human brain solves problems.
To prove the efficiency of the developed technology, the research group created artificial neural network hardware equipped with a self-rectifying synaptic array and algorithm called a ‘stashing system’ that was developed to conduct artificial intelligence learning. As a result, it was able to reduce energy by 37% within the stashing system without any accuracy degradation. This result proves that emulating the neuromodulation in humans is possible.
Professor Kim said, "In this study, we implemented the learning method of the human brain with only a simple circuit composition and through this we were able to reduce the energy needed by nearly 40 percent.”
This neuromodulation-inspired stashing system that mimics the brain’s neural activity is compatible with existing electronic devices and commercialized semiconductor hardware. It is expected to be used in the design of next-generation semiconductor chips for artificial intelligence.
This study was published in Advanced Functional Materials in March 2022 and supported by KAIST, the National Research Foundation of Korea, the National NanoFab Center, and SK Hynix.
-Publication:
Woon Hyung Cheong, Jae Bum Jeon†, Jae Hyun In, Geunyoung Kim, Hanchan Song, Janho An, Juseong Park, Young Seok Kim, Cheol Seong Hwang, and Kyung Min Kim (2022)
“Demonstration of Neuromodulation-inspired Stashing System for Energy-efficient Learning of Spiking Neural Network using a Self-Rectifying Memristor Array,” Advanced FunctionalMaterials March 31, 2022 (DOI: 10.1002/adfm.202200337)
-Profile:
Professor Kyung Min Kimhttp://semi.kaist.ac.kr https://scholar.google.com/citations?user=BGw8yDYAAAAJ&hl=ko
Department of Materials Science and EngineeringKAIST
2022.05.18 View 9427 -
Machine Learning-Based Algorithm to Speed up DNA Sequencing
The algorithm presents the first full-fledged, short-read alignment software that leverages learned indices for solving the exact match search problem for efficient seeding
The human genome consists of a complete set of DNA, which is about 6.4 billion letters long. Because of its size, reading the whole genome sequence at once is challenging. So scientists use DNA sequencers to produce hundreds of millions of DNA sequence fragments, or short reads, up to 300 letters long. Then the DNA sequencer assembles all the short reads like a giant jigsaw puzzle to reconstruct the entire genome sequence. Even with very fast computers, this job can take hours to complete.
A research team at KAIST has achieved up to 3.45x faster speeds by developing the first short-read alignment software that uses a recent advance in machine-learning called a learned index.
The research team reported their findings on March 7, 2022 in the journal Bioinformatics. The software has been released as open source and can be found on github (https://github.com/kaist-ina/BWA-MEME).
Next-generation sequencing (NGS) is a state-of-the-art DNA sequencing method. Projects are underway with the goal of producing genome sequencing at population scale. Modern NGS hardware is capable of generating billions of short reads in a single run. Then the short reads have to be aligned with the reference DNA sequence. With large-scale DNA sequencing operations running hundreds of next-generation sequences, the need for an efficient short read alignment tool has become even more critical. Accelerating the DNA sequence alignment would be a step toward achieving the goal of population-scale sequencing. However, existing algorithms are limited in their performance because of their frequent memory accesses.
BWA-MEM2 is a popular short-read alignment software package currently used to sequence the DNA. However, it has its limitations. The state-of-the-art alignment has two phases – seeding and extending. During the seeding phase, searches find exact matches of short reads in the reference DNA sequence. During the extending phase, the short reads from the seeding phase are extended. In the current process, bottlenecks occur in the seeding phase. Finding the exact matches slows the process.
The researchers set out to solve the problem of accelerating the DNA sequence alignment. To speed the process, they applied machine learning techniques to create an algorithmic improvement. Their algorithm, BWA-MEME (BWA-MEM emulated) leverages learned indices to solve the exact match search problem. The original software compared one character at a time for an exact match search. The team’s new algorithm achieves up to 3.45x faster speeds in seeding throughput over BWA-MEM2 by reducing the number of instructions by 4.60x and memory accesses by 8.77x. “Through this study, it has been shown that full genome big data analysis can be performed faster and less costly than conventional methods by applying machine learning technology,” said Professor Dongsu Han from the School of Electrical Engineering at KAIST.
The researchers’ ultimate goal was to develop efficient software that scientists from academia and industry could use on a daily basis for analyzing big data in genomics. “With the recent advances in artificial intelligence and machine learning, we see so many opportunities for designing better software for genomic data analysis. The potential is there for accelerating existing analysis as well as enabling new types of analysis, and our goal is to develop such software,” added Han.
Whole genome sequencing has traditionally been used for discovering genomic mutations and identifying the root causes of diseases, which leads to the discovery and development of new drugs and cures. There could be many potential applications. Whole genome sequencing is used not only for research, but also for clinical purposes. “The science and technology for analyzing genomic data is making rapid progress to make it more accessible for scientists and patients. This will enhance our understanding about diseases and develop a better cure for patients of various diseases.”
The research was funded by the National Research Foundation of the Korean government’s Ministry of Science and ICT.
-PublicationYoungmok Jung, Dongsu Han, “BWA-MEME:BWA-MEM emulated with a machine learning approach,” Bioinformatics, Volume 38, Issue 9, May 2022
(https://doi.org/10.1093/bioinformatics/btac137)
-ProfileProfessor Dongsu HanSchool of Electrical EngineeringKAIST
2022.05.10 View 7800 -
Professor Lik-Hang Lee Offers Metaverse Course for Hong Kong Productivity Council
Professor Lik-Hang Lee from the Department of Industrial System Engineering will offer a metaverse course in partnership with the Hong Kong Productivity Council (HKPC) from the Spring 2022 semester to Hong Kong-based professionals.
“The Metaverse Course for Professionals” aims to nurture world-class talents of the metaverse in response to surging demand for virtual worlds and virtual-physical blended environments. The HKPC’s R&D scientists, consultants, software engineers, and related professionals will attend the course. They will receive a professional certificate on managing and developing metaverse skills upon the completion of this intensive course.
The course will provide essential skills and knowledge about the parallel virtual universe and how to leverage digitalization and industrialization in the metaverse era. The course includes comprehensive modules, such as designing and implementing virtual-physical blended environments, metaverse technology and ecosystems, immersive smart cities, token economies, and intelligent industrialization in the metaverse era.
Professor Lee believes in the decades to come that we will see rising numbers of virtual worlds in cyberspace known as the ‘Immersive Internet’ that will be characterized by high levels of immersiveness, user interactivity, and user-machine collaborations.
“Consumers in virtual worlds will create novel content as well as personalized products and services, becoming as catalyst for ‘hyperpersonalization’ in the next industrial revolution,” he said.
Professor Lee said he will continue offering world-class education related to the metaverse to students in KAIST and professionals from various industrial sectors, as his Augmented Reality and Media Lab will focus on a variety of metaverse topics such as metaverse campuses and industrial metaverses.
The HKPC has worked to address innovative solutions for Hong Kong industries and enterprises since 1967, helping them achieve optimized resource utilization, effectiveness, and cost reduction as well as enhanced productivity and competitiveness in both local and international markets. The HKPC has advocated for facilitating Hong Kong’s reindustrialization powered by Industry 4.0 and e-commerce 4.0 with a strong emphasis on R&D, IoT, AI, digital manufacturing.
The Augmented Reality and Media Lab led by Professor Lee will continue its close partnerships with HKPC and its other partners to help build the epicentre of the metaverse in the region. Furthermore, the lab will fully leverage its well-established research niches in user-centric, virtual-physical cyberspace (https://www.lhlee.com/projects-8 ) to serve upcoming projects related to industrial metaverses, which aligns with the departmental focus on smart factories and artificial intelligence.
2022.04.06 View 7091