ACM POPL 2019, one of the world's top academic societies in programming languages, was adopted in a paper written by KAIST Computer Science Master's Degree Park Kyung-hee, Bachelor's Degree Hong Jae-min and Professor Ryu Seok-young with Dr. Guy L. Steele Jr. of the Oracle Institute.
The 16th APLAS (Asian Symposium on Programming Language and Systems), which KAIST supported as a Gold Sponsor, was held in Wellington, New Zealand, December 3, 2018. Professor Sukyoung Ryu, chair of the program, invited three world-renowned lecturers: Amal Ahmed (USA), Azalea Raad (MPI-SWS, Germany), and Bernard Scholes (University of Sydney, Australia), and conducted various programs including presentations of papers and poster sessions and workshops on December 2 and December 6, 2018.
Professor Jinah Park of the School of Computing at KAIST delievered a keynote lecture on the topic “Hippocampal Morphology Study based on Progressive Template Deformable Model” at the International Conference on Medical Imaging and Case Reports 2018 held in Baltimore in the U.S. from October 26 to 28, 2018. The event involved 70 people from 48 institutions in 23 countries. The event attracted many researchers who are influential in medical images and clinical studies including Dr. Marth Shenton from Harvard Medical School, Professor Polina Golland of MIT, Michael Miller and Professor Jeffery Siewerdwen of Johns Hopkins University.
Professor Min H. Kim has chosen the best research and development of 2018 top 100 Six professors from KAIST have been selected for the "Top 100 2018 state research and development" announced by the Ministry of Science and ICT and the Korea Institute for Science and Technology Planning. The winners are Il-du Kim and Byeong-gook Park at the Department of New Material Engineering, Ho-min Kim at the Graduate School of Medicine, Jae-woo Lee at the Department of Biochemistry, Min H. Kim at the School of Computing, and Kyung-chul Choiat the Department of Electrical and Electronic Engineering. Professor Min H. Kim of the School of Computing was chosen for excellence in the field of information and electronics. It was recognized that he developed high-performance imaging technology to obtain high-performance images. Professor Il-du Kim was chosen as the best performance in the field of machinery and materials. It was recognized that he developed ultra-high sensitivity gas sensor platform material based on self-assembly organic complex catalyst coupling. Professor Byung-kook Park was also chosen for excellence in the machine and material fields. He has developed a material technology that obtains spin current from heat. Ho-min Kim , a professor at the medical school, was selected as the best performance in the life and ocean fields. It has established the 3rd structure and molecular warfare of core protein that controls the formation of synapses. Professor Jae-woo Lee has been chosen for excellence in energy and the environment. He was credited with developing high-value carbon-material synthesis technology. Kyung-chul Choi was chosen as the best performance in information and electronics. It was recognized that it developed a smooth display that was implemented on top of clothes. The performance selected for excellence will be awarded to the Minister of Science and ICT with a certificate and a signboard. The six selected professors will be nominated as candidates for the state-funded R&D achievement evaluation (medal, presidential citation, and the prime minister's citation) and will receive preferential treatment in the selection of new R&D projects.
Intelligent Service Integration (ISI) Laboratory of KAIST School of Computing(Prof. Han Dongsoo) has decided to carry out the international academic project for the development of Global Indoor Positioning System with Global H Company. Global H will support KAIST ＄ 400,000 for the project, which will be accompanied by technology transfer. The ISI Lab, which developed the KAIST Indoor Positioning System (KAILOS) in 2014 and released to the public, has recently developed a crowd sourcing AI technique that automatically labels the location of wireless signals acquired from unspecified number of smartphone users. In this joint international project, KAIST will upgrade location labeling AI technique using crowdsourcing to commercialization level. If the project is successfully performed, H Company is expected to install the system developed by KAIST its products and commercialize it. Professor Han Dongsoo, who will lead the international industry project with H company to be conducted over the next year, said, "It is a pity that the technology developed by KAIST will be commercialized through overseas companies before the domestic companies. The result is that domestic regulations on location services are too strict. " Professor Han Dongsoo said, "It is significant that a global company recognized the technology developed by KAIST and commissioned an industrial project for commercialization. Technology continues to decline and disappear if not developed. We will continue to expand international industry-academia cooperation in the field of indoor location recognition in the future. "
Kim Kwang, professor of KAIST (President: Sang Chul Shin) Graduate School of Computing and Information Security Graduate School, along with Muhamad Erza Aminanto and Dr. Harry Chandra Tanuwidjaja, Ph.D. students from Indonesia, wrote an English book called “Network Intrusion Detection using Deep Learning : A Feature Learning Approach” (in the aspected of network intrusion detection using features of deep learning) which supported by IITP’s project on “Communication Technology Research using Bio-inspired Algorithm” from April 2018 to February 2018. He has published this in one of the cyber security systems and networking series at Springer, a prominent publisher in Germany. This book introduces various methods of intrusion detection system using deep learning, which is artificial intelligence technique and widely used in computer vision, natural language processing, image processing, etc., and described an intrusion detection technique which extracts and learns the features of intrusion traffic with very high scan rate (99.918％) and low false positives (0.012％) compared to existing skills. Annexes include technical trends on artificial intelligence techniques for detecting malicious codes. This book will serve as a good guide for undergraduate and graduate students, R & D personnel in providing practical knowledge of establishing cyber security systems regarding graft artificial intelligence onto cyber security. 참조: https://www.springer.com/gp/book/9789811314438
Professor Moonzoo Kim delievered a keynote speech at the 15th International Conference on Formal Aspects of Component Software (FACS) which was held from October 10 to 12, 2018 with Professor Edward Lee of UC Berkeley and Professor Gigore Rosu of UIUC. His talk was titled “Lessons Learned from Automated Analysis of Industrial SW for 15 Years”.
Professor Choi Key-Sun, head of bidding committee for International Conference on Computational Linguistics(COLING), participated in the presentation of the ICCL Steering Committee held in Santa Fe, New Mexico from 20th to 26th August, and confirmed the 29th COLING in Gyeongju, Korea in 2022. Computational linguistics is a core area of the Fourth Industrial Revolution that completes artificial intelligence as an integrated field of computer science and linguistics that allows machines to understand and respond to human speech and writing. COLING is a global conference on computerized languages with over 1200 participants from 50 countries every two years. It has been held tying the authoritative ACL (The Association for Computational Linguistics) and the International Conference on Language Resources and Evaluation (LREC) in the field of computational linguistics. The Main Conference has about 1,000 papers submitted, about 300 of which are presented. The main conference includes demo sessions, tutorials, and more than 10 workshops. COLING 2022 is expected to be held for about one week starting from Hangul Day on Oct. 9, 2022. It is expected to contribute greatly to the development of computer language related industries and human resources development. It will be able to show the status and leadership of computer linguistics in Korea.
Professor Min H. Kim selected as 6 core patent technologies of KAIST "Ultra Spectroscopic Imaging Technology" of Professor Min H. Kim of School of Computing has been selected as the six key patent technologies of KAIST and announced at the COEX Seminar on September 10, 2018 in Samseong-dong. This event is a six-key patent technology including biotechnology, artificial intelligence, nanotechnology, and semiconductor fields such as immuno-activated chemotherapy and AI-based super high-resolution image conversion technology. 2018 KAIST Core Tech Transfer Day website: http://tech4.kaist.ac.kr/ [Related article : ETNews ] http://www.etnews.com/20180920000185 2018 KAIST Core Tech Transfer Day Introduction KAIST (President, Shin, Sung-cheol) introduces six key patent technologies, including the 'Immune Activation Cancer Therapeutics' to activate the immune response of the patient to induce the body's innate immune system to kill cancer cells and 'ultra-high-resolution image conversion hardware technology' which instantly convert low-resolution images to high-resolution images (4K UHD) using real-time AI (Deep Learning) technology , which will be commercialized immediately. KAIST announced on October 3 that '2018 KAIST key patent technology transfer briefing seminar' will be held at COEX, Seoul, from 1 pm on October 10 under the supervision of the Industry-academia cooperation team (chief, Choi Kyung-chul). This seminar was designed to create an industry-university cooperation model that not only creates jobs but also enhances corporate competitiveness by transferring the superior technologies possessed by researchers of KAIST to companies. Officials from industry-academia cooperation team said that "We prepared this briefing as part of the innovation plan for technology commercialization, one of the five innovation areas of KAIST Vision 2031, which announced in March that KAIST will become the world's leading university by 2031." and announced that they will hold a briefing every year to select patent technology and transfer it to companies. KAIST plans to provide business finance support services through cooperation with the Technology Guarantee Fund to companies that transfer selected technologies. These companies will also receive various services from KAIST, such as business model development, patent-R & D linkage strategy analysis, domestic and foreign marketing priority promotion. The technology that KAIST introduced this year is the core patent technology of bio, nano, artificial intelligence, and semiconductor which is the center of the 4th industrial revolution. ① New nano patterning platform technology (Prof. Jung Hee Tae, Department of Chemical and Biological Engineering) ② Obtain candidate substances for immuno-activated chemotherapy (Prof. Byung-Seok Choi, Department of Chemistry) ③ Technology capable of mass production of biofuels using microorganisms (Professor Lee Sang-yeol, Department of Biochemical Engineering). ④ Compact single-shot ultra-spectral camera technology (Prof. Min H. Kim, School of Computing) ⑤ High-speed, high-resolution up-scaling technology based on AI (Deep Learning) (Prof. Moon-Chul Kim, Department of Electrical and Electronics Engineering) ⑥ Radiation-resistant MOSPET device (Prof. Hee-cheol Lee, Department of Electrical and Electronics Engineering) are included in six core patent technologies. In particular, Prof. Kim Mun-cheol and Prof. Min H. Kim's patent technology was introduced and exhibited at the International Household Appliance Expo (IFA 2018) held in Berlin, Germany from August 31 to September 5, attracting much attention from participants. The six core technologies selected by KAIST are highly influential in the industry and have been chosen considering the applicability to various fields in the future, market size, and technological innovation. To this end, KAIST has been conducting public consultations on excellent technologies in the campus, where professors directly researched and developed the patent, consulted and evaluated them with a panel of about 15 judges, including patent attorneys, venture investors, and commercialization experts. About 200 people, including business stakeholders and investors, will be invited to discuss the mutual cooperation plan including technology development and technology transfer. Professor Lee Sang-yeop, a researcher, and 6 professors will attend the meeting, present 15 minutes for each patented technology and consult about technology transfer at the site. In addition to this, President Shin Sung-chul, acting president of Korea Technology Guarantee Fund Kang Nak-kyu, CEO of Korea Softbank Lee Joon-pyo, and the president of KAIST's alumni association Cha Gi-cheol will participate in the 4th Industrial Revolution era and emphasize the significance of technology commercialization related to advanced technology held by the university. Professor Kyung-chul Choi, head of the KAIST's Industrial and Academic Cooperation Group, said, "With this tech transfer briefing, we will introduce the core patent technologies of KAIST to companies and develop them into global growth." "We will continue to discover core patent technologies and ideas for various projects that have not yet been discovered, thus activating the technology business using core technologies and actively pursuing industrial cooperation projects." said Choi.
The 7th Open Knowledge Base and Question Answering (OKBQA-7), where Professor Choi Ki-Sun of KAIST School of Computing is the General Chair, was held at the E3-1 Building of KAIST School of Computing from Aug. 7th to 10th, 2018. OKBQA-7 Hackathon, which is a place where experts, researchers and students gather in various fields with a total of 5 themes from August 7th to 8th. Topics like OKBQA Platform, Dialog Corpus, Multi -Modal Character Identification, Knowledge Base Population, and Free topics for joint research was actively discussed and brainstormed. On August 9th of this event, we conducted the OKBQA-7 tutorial program DeepLearningQA 2018 Tutorial. Yuta Nakashima, Andre Freitas, and Mikhail Burtsev, the top experts in each field, gave a lecture on topics such as Video Summarization, Open Information Extraction, and Deep Pavlov. On August 10, the last day of the event, OKBQA-7 Hackathon's achievements were summarized, and the OKBQA-7 Workshop program, a forum for future developments, new research topics, and free discussions on various consortia, was conducted. About 30 experts, researchers and students participated in the event. About 70 experts, researchers and students participated in the tutorial program.
Book of Professor Kang Sung Won of the School of Computing, "Development of a Systematic Software Product Line" (published by Hongneung Science Publishing Co., June, 2017, p. 475) was selected as the best academic book of the Korean Academy of Science in 2018. The Ministry of Education and the Republic of Korea Academy constituted an examination committee composed of 106 academic members and scholarship experts, conducted a multi-stage examination over a period of two months and selected a total of 285 books including humanities, social sciences, Korean studies, natural sciences. Selected books are distributed to university libraries nationwide in order to share excellent research results in the field of basic science. "Systematic Software Product Line Development" is the first Korean academic research work in the field of software product line. It sets out the fundamental principles of software product line development in a coherent and comprehensive way that goes beyond existing international literature and shows the working of these principles through case studies.
Establishment of smart science museum exhibition research group to improve exhibitions of the 4th industrial revolution era (Development of exhibition service technology that combines indoor location recognition technology with AR / VR, IoT, AI technology) The exhibition guidance for the science museum is expected to be renewed. KAIST (President, Shin Sung-chul) and the National Science Museum (President, Bae Tae-min) will showcase the smart science museum exhibition group that develops a system that guides the exhibition hall of science museum by linking indoor technology and key technologies of the fourth industrial revolution such as AR / VR and IoT Was launched. The research institute has nine universities including KAIST(School of Computing : Han Dong-su, Park Jin-a, Department of Industrial Design : Lee Ki-hyuk), Yonsei University, HanYang University and six research institutes including Electronic Component Research Institute and National Center for Science and Technology., A total of 15 tasks will be undertaken. From the second half of 2018 to 2022, about 13 billion won of government budget will be spent for four years. There have been many difficulties due to the lack of qualified and professional exhibition guides. The efficiency of exhibition guidance using smart phones was also slow. When the indoor location-based exhibition guidance system that the research team is aiming at is launched, visitors can receive exhibition information service through various methods including AR / VR technique depending on the location. Specifically, a service similar to the explanation of the exhibition guide will be provided through a smart phone. They will also apply living-wrapping techniques, which will be used to improve the exhibition, by conveying various feedbacks from spectators to the science museum immediately. The indoor location will utilize the KAIST Indoor Locating System (KAILOS), an indoor location recognition system developed by KAIST for a long time. Bae Jeong-Hoe of the National Science Museum said "Every year hundreds of thousands of young people visit the science museum. We should show them various examples of science contributing to the development of our society through exhibitions and instill dreams and inspiration through science. That is reason why the exhibition of science museum should be changed and developed in accordance with the 4th industrial revolution era. The exhibition should be changed in conjunction with the core technology of the 4th industrial revolution and the exhibition guidance should be made using the latest IT technology.”. Professor Han Dongsoo, the chair of the research group, said, "We will systematically organize the science museum display technology and exhibition contents into a smart science museum display platform, which will make the exhibition information system more flexible and easier to expand. AR/VR technology and indoor location recognition technology will be used in the exhibition guide.” The exhibition guidance system developed by the research team will be applied first to the National Science Museum and gradually expanded to 167 science museums across the country. It will be applied to museums and art museums in each district that show exhibits like a science museum. [그림] 주요 서비스
ONR (Office of Naval Research, Department of Defense, USA) decided to support Prof. Byunghoon Kang's project "Towards Dialects Computing in Network and System Protocols". The research team consists of Prof. Byunghoon Kang, postdoctoral researchers Dr. JinSoo Jang and Dr. Hojoon Lee, and 10 Ph.D./Master candidates. They will conduct a study on blocking various attacks exploiting a formal protocol by polymorphizing existing network and system protocols. The research period will be three years (September 2018 - August 2021), and a total of 1.5 billion won (＄ 1,366,665) will be granted. Cases where the US Department of Defense directly supports overseas universities are unusual, suggesting recognition of the excellence of the team’s information protection research capacity.
The Korean Ministry of Science and ICT and IITP selected Prof. Jong Cheol Park's laboratory as a SW Star Lab of intelligent software on April 20, 2018. The selected "SW Star Lab" is among a total of five laboratories in four universities: Seoul National University, POSTECH, Chung Ang University, and KAIST. There are two laboratories in the field of intelligent SW, and one for each area of distributed computing, algorithms, and UI/UX. The selected lab will receive project funding of up to 300 million won per year for up to eight years and is encouraged to develop a world-class research agenda through open software. Prof. Jong Cheol Park's lab will work on a research program on the development of software for automatically predicting the reliability distribution of given documents/dialogues, consisting of five modules: data collection, automatic collection of evidence, document/conversation reliability enhancement, document/conversation reliability distribution prediction, and linguistic analysis.
Prof. Sukyoung Ryu delivered a keynote speech on “Static Analysis of Android Applications for Finding Bugs and Security Vulnerabilities” at <Programming> 2018. <Programming> 2018 is the International Conference on the Art, Science, and Engineering of Programming, where attendees discuss various theoretical, experimental, and engineering research results on programming. <Programming> 2018 was held in Nice, France from April 9 to 12, 2018.
Profs. Sukyoung Ryu, Sung-Ju Lee, Junehwa Song, and Min H. Kim’s research projects were selected to be presented in KAIST Breakthroughs, a biannual newsletter published by the College of Engieering at KAIST. Prof. Sukyoung Ryu: HybriDroid: Static analysis framework for android hybrid applications http://breakthroughs.kaist.ac.kr/?post_no=1027 Prof. Sung-Ju Lee & Junehwa Song: Zaturi: Create an audiobook for your baby using time that slips by http://breakthroughs.kaist.ac.kr/?post_no=1029 Prof. Min H. Kim: Compact hyperspectral imaging at low cost http://breakthroughs.kaist.ac.kr/?post_no=1026
KAIST team has newly suggested the unit testing of C programs that can find errors automatically while minimizing false alarms. Prof. Moonzoo Kim and Dr. Yoon Ho Kim wrote a paper "Precise Concolic Unit Testing of C Programs with Alarm Filtering Using Symbolic Calling Contexts" in collaboration with Prof. Yoon Ja Choi at Kyung-Buk University. Their paper has been accepted to ACM/IEEE ICSE (Intl. Conf. on Software Engineering) which is one of the most prestigious conferences in the Software Engineering field. Congratulations！
Two papers from the KAIST School of Computing got accepted for ACM POPL 2018, a top international conference on programming languages. The first paper is “On Automatically Proving the Correctness of math.h Implementations“ authored by Mr Wonyeol Lee in the school and his colleagues in Microsoft and Stanford (Sharma and Aiken). The second paper is “Denotational Validation of Higher-Order Bayesian Inference“ written by Prof Hongseok Yang in the school and his colleagues in Oxford, Cambridge, Tubingen and Edinburgh (Scibior, Kammar, Vakar, Staton, Cai, Ostermann, Moss, Heunen, Ghahramani).
Prof. Sung-Ju Lee's SCAN and Prof. Alice Oh's Eliph system were selected to be presented in KAIST Breakthroughs. Prof. Sung-Ju Lee's SCAN system (http://breakthroughs.kaist.ac.kr/?post_no=913) Prof. Alice Oh's Eliph system (http://breakthroughs.kaist.ac.kr/?post_no=908) Congratulations on both teams！
KAIST SoC Prof. Hongseok Yang presented a keynote at QONFEST’17 as a joint invited speaker for CONCUR, QUEST, and FORMATS. Prof. Hongseok Yang at the KAIST School of Computing presented a keynote talk on probabilistic programming at QONFEST’17, as a joint invited speaker for CONCUR, QUEST, and FORMATS. QONFEST’17 is the umbrella event of the four major international conferences CONCUR, QEST, FORMATS, and EPEW, whose topics jointly cover theory, formal modeling, verification, performance evaluation and engineering of concurrent, timed and other systems. QONFEST '17 was held in Berlin, Germany from September 4, 2017, until September 9, 2017.
IEEE/ACM ASE 2017 (Automated Software Engineering), a top international conference on software engineering, accepted a paper from School of Computing’s Graduate School of Information Security. Professor Sang Kil Cha, alongside Soomin Kim and KAIST Cyber Security Research Center, worked on the paper, “Testing Intermediate Representations for Binary Analysis”. The research was a part of Prof. Cha’s project with the Ministry of Science and ICT, a R&D project carried out since 2016 in cooperation with KAIST Cyber Security Research Center. The project is on comparing the expressiveness of existing intermediate representations used for binary analysis. The paper will be presented at IEEE/ACM ASE 2017 conference, held Oct. 30 to Nov. 3 at Illinois, US. Reference: http://ase2017.org
ㅁ KAIST Professors Dongman Lee, Wonjae Lee, Juyong Park, Meeyoung Cha, and their respective research teams unveiled their “Placeness Data Mining and Inference”, a part of their research on the development of core technologies for placeness based data mining for use in real time intelligent information suggestion services in the context of smart spaces. ㅇ The API is available at placeness.kaist.ac.kr:8080/, with the wiki on relevant information available at placeness.kaist.ac.kr/wiki ㅇ The development of core technologies for placeness based data mining for use in real time intelligent information suggestion services in the context of smart space was a government funded R&D effort, running from 2015 July to 2017 Aug, supported by the Ministry of Science and ICT (former Ministry of Science, ICT, and Future Planning). ㅇ This research analyzes the vast amounts of geotagged multimedia and text data generated by online social networking services to garner the purpose and social context of specific commercial locations’ visitors, and through this data infer the social actions, emotion, and the relationship the user has with the location. ㅇ The recently unveiled API relies on data collected and analyzed from the current major R&D objective locations (e.g. COEX, IPark Mall) and their constituent locations. Social multimedia data collected from the locations are analyzed to provide locational context from various perspectives (passers-by, visitor, time, emotion, etc). A REST API allows access via HTTP requests for the general public, providing the placeness information of the major spaces. ㅁ The above API provides 4 different inferences arising from the process of placeness inference: 1) placeness of the location of which this place is a constituent of, 2) placeness of the location within the context of the aforementioned parent location, 3) emotion based inference on the location and its parent location’s ambience, and 4) the user-location relationship. ㅇ The 4 inferences include the following information: - Fundamental technology for real time placeness matching via the analysis of users’ social context within the locality - Fundamental technology for the inference of granular placeness inference via the application of standardized data structures - Fundamental technology for the inference of placeness for reflecting the user’s diachronic / immediate context, thereby presenting a multidimensional relationship connectivity graph between localities and users - Fundamental technology for emotion inference for real time location suggestion and user specific locality emotion score output based on the inference ㅇ The information provided enables developers to improve the accuracy and satisfaction of location suggestion services, as well as mine social data for social contexts and the resultant public visitation patterns and changes in preferences, with which specific locations can be suggested, and advertising and coupons created for the purpose of promoting the consumption of specific contents within the locality. ㅁ Prof. Dongman Lee (Project Lead) claims the API developed during the research effort improves the quality of existing geography based location search and suggestion services, automatically providing changing location suggestions based on urban visitors’ changing location visit trends. The research is expected to form the core of technologies to overcome the limitations in the previous non-standardized text data analysis, harnessing both image and text simultaneously to infer the social information of the location, leading to a leap in existing location based suggestion services and AI based personal assistant services. ㅁ Placeness data mining and inference technology is applicable in various location based information search and suggestion service providers and location based social commerce services, allowing information search companies and mobile coupon providers to offer intelligent information suggestion functionalities and their improvement.
From July 24 to 28, KAIST’s School of Computing organized and hosted the 14th International Conference on Computability and Complexity in Analysis (CCA2017) and Workshop on Real Verification: http://complexity.kaist.edu/CCA2017 48 leading senior experts, rising young scientists, and eager students have attended and contributed to this unique event. They came from all over the world: Amsterdam, Birmingham, Brussels, Buenos Aires, Bulgaria, Cambridge, Connecticut, Cornell, Darmstadt, Hagen, Kyoto, Maastricht, Munich, Nagoya, Okinawa, Pohang, Pretoria, Saarbrücken, Seoul, Singapore, Tokyo, Trier, and Versailles. Over the course of five days we had 33 presentations of recent research, discussions of current challenges, and explorations of future developments in the Algorithmic Foundations of Numerics. The organizers gratefully acknowledge generous financial support from KAIST's School of Computing, from the International Relations Team (IRT), and from the National Research Foundation of Korea (NRF). Co-located with CCA 2017, a Workshop on Real Verification was organized by Prof. Gyesik Lee (Hankyong National University) and Prof. Martin Ziegler (KAIST) with invited speakers from Yonsei University, INRIA, Aston University, Trier University, KAIST, SNU, and AdaCore. For many participants this was the first time to visit Korea: They have particularly enjoyed the impressive experience of this technologically advanced country as well as of its warm hospitality, culinary richness, and cultural heritage. In fact, as part of a joint NRF/EU H2020 project, five conference participants continue staying at KAIST throughout August for further collaborative research
KAIST School of Computing Associate Professor Jinah Park presented the keynote at the 21st Medical Image Understanding and Analysis Conference (MIUA 2017) last July 11 through 13, held at John McIntyre Centre, Pollock Halls, Edinburgh, UK. The presentation was on “model-based approach to 3D shape recovery and analysis.” MIUA 2017 is a medical image analysis forum for experts in the field held every year in the UK, boasting attendees from various European countries as well as the US, Australia, and Asia. This year, of the 150 organizations attending the conference, 46 were not from the UK, and out of the 105 papers and 22 clinical abstracts submitted, 82 were from overseas. KAIST SoC Prof. Jinah Park was invited as a keynote presenter alongside Prof. Ingela Nyström (Uppsala University) and Prof. Daniel Rueckert (Imperial College London). The conference also invited Sir Michael Brady, a Professor at the University of Oxford, as the Honorary Guest Speaker. Prof. Jinah Park’s lecture was on her 3 dimensional modeling technique for extracting clinical understanding from clinical imaging data, a subject she has worked on for two decades.
KAIST became the first Korean university to have one of the world’s top 20 Computer Graphics research institutes, based on the number of papers published in the last 2 years in the top 3 CG conferences. KAIST School of Computing undergraduate CG lecture professors (CS380, by professors Min H. Kim, Jinah Park, and Sungeui Yoon) participated in a survey to mark this occasion. The survey was presented at Eurographics 2017, one of the top 3 graphics conferences alongside ACM SIGGRAPH and SIGGRAPH Asia. The presentation contained content from Prof. Kim’s undergraduate level lecture, which can be found at http://vclab.kaist.ac.kr/cs380/. We extend our most sincere congratulations. [Reference] [Reference] “What we are teaching in Introduction to Computer Graphics”, Balreira, Dennis G.; Walter, Marcelo; Fellner, Dieter W., Proc. Eurographics 2017, The Eurographics Association, http://diglib.eg.org/handle/10.2312/eged20171019 [Eurographics Presentation] http://wiki.inf.ufrgs.br/What_we_are_Teaching_in_Introduction_to_Computer_Graphics
Three papers by KAIST SoC students Jung Guk Park (Doctorate, advisor: Prof. Alice Oh), Chunjong Park (M.S., advisor: Prof. Sung-Ju Lee), and Bumsoo Kang (Doctorate, advisor: Prof. Junehwa Song) were presented at CSCW 2017. The 20th ACM Conference on Computer-Supported Cooperative Work and Social Computing, held from last Feb. 25th to Mar. 1st, is one of the best conferences in HCI (Human Computer Interaction) and Social Computing. CSCW focuses on research on designing and utilizing technologies for groups and communities, and has a long history of being considered one of the best conferences for HCI and Social Computing. KAIST School of Computing led global research efforts in said fields, presenting three papers this year. The paper from Prof. Alice Oh’s lab was by Jung Guk Park, presenting a system that shows how a piece of code was written, letter by letter, for students that have problems understanding others’ code during SoC class peer assessments. The paper received an Honorable Mention Award. Alumnus Chunjong Park presented a technology to detect breaks between social activities via various smartphone sensors, and notify the user of such events. This was in an effort to prevent smartphones from becoming inconveniences hampering social interaction. The paper was a collaboration between the labs of Professors Sung-Ju Lee, Dongman Lee, and Juho Kim. Bumsoo Kang presented a mobile app that reads books to babies in their parent’s voice, using the small bits of unused time during a working day. This paper was a collaboration between the labs of Professors Junehwa Song, Sung-Ju Lee, and an IBM lab in the US. Eliph: Effective Visualization of Code History for Peer Assessment in Programming Education Jungkook Park, Yeong Hoon Park, Suin Kim, and Alice Oh “Don’t Bother Me. I’m Socializing！”: A Breakpoint-Based Smartphone Notification System Chunjong Park, Junsung Lim, Juho Kim, Sung-Ju Lee, and Dongman Lee Zaturi: We Put Together the 25th Hour for You. Create a Book for Your Baby Bumsoo Kang, Chulhong Min, Wonjung Kim, Inseok Hwang, Chunjong Park, Seungchul Lee, Sung Ju Lee, and Junehwa Song
School of Computing Intelligent Service Lab (Prof. Dong-Soo Han) announced that they have developed a system for providing global indoor localization using Wi-Fi signals. The technology uses numerous smartphones to collect fingerprints of location data and label them automatically, greatly reducing the cost of constructing an indoor localization system while maintaining high accuracy. The method can be used in any building in the world, provided the floor plan is available, and there are Wi-Fi fingerprints to collect. To accurately collect and label the location information of collected fingerprints, the research team analyzed indoor space utilization. This led to a technology that classified indoor space in to places used for stationary tasks (resting spaces), and spaces used to reach said places (transient spaces), and separate algorithms to optimally and automatically collect location labelling data. A few years ago, the team has also implemented a means of automatically labelling resting space locations from collected signals in various contexts such as homes, shops, and offices via the users’ address information. The latest one allows for the automatic labelling of transient spaces’ locations such as hallways, lobbies, and stairs using unsupervised learning, also without any additional location information. Testing in KAIST’s N5 building and the 7th floor of N1 building proved the technology is capable of 3 to 4 meter accuracy given enough training data. The accuracy is comparable to technology using manually labeled location information. Google, MS, and other multinational corporations collected tens of thousands of floor plans for their indoor localization projects. Indoor signal map collection was also attempted but proved more difficult. As a result, existing indoor localization services were often plagued by inaccuracies. In Korea, COEX, Lotte World Tower, and other landmarks provide comparatively accurate indoor localization, but most buildings suffer from the lack of signal maps, preventing indoor localization services. Professor Dong-Soo Han claims that “This technology allows easy deployment of highly accurate indoor localization system in any building in the world. In the near future, most indoor spaces will provide localization services, just like outdoor spaces.” He further added that although smartphone collected fingerprints were left unutilized and discarded to date, the development of an application for the data will create a new field of wireless LAN big data fingerprinting. This new indoor navigation technology is likely to be valuable to Google, Apple, or other global firms providing indoor localization information for the whole world. Nonetheless the technology will also be valuable for Korean localization service firms for domestic localization services. Prof. Han added that “the new global indoor localization system deployment technology will be added to KAILOS, KAIST’s indoor localization system.” KAILOS was released in 2014 as KAIST’s open platform for indoor localization service, allowing anyone in the world to add floor plans to KAILOS, and add the building’s signal fingerprint data to help create a universal indoor localization service. As localization accuracy improves in indoor environs, despite the absence of GPS signals, applications such as location based SNS, location based IoT, and location based O2O are expected to take off, leading to various improvements in convenience and safety. Integrated indoor-outdoor navigation service is also visible on the horizon, fusing vehicular navigation technology with indoor navigation. [그림] 무선랜 핑거프린트 기반 스마트폰 실내 위치인식 [그림] 불특정 다수의 스마트폰을 통해서 수집된 핑거프린트의 수집 위치를 자동으로 라벨링하는 자율학습 기법 [그림] KAIST Indoor Locating System (KAILOS) 응용 서비스 및 관련 기술
The first seminar by HCI＠KAIST Research Society was held last Thursday (October 13th). HCI＠KAIST Research Society was organized by the School of Computing Future Planning Committee with the goal of providing a platform for cooperation between HCI labs in KAIST, and facilitate HCI education and research. Currently, 11 labs in KAIST are participating in the program. The society will be holding biweekly seminars, open workshops, and open house, and is operated with the help of Golfzon and the School of Computing. The first seminar started off with previews of two papers to be published in the UIST 2016 conference, and the second seminar is to be presented by guest speaker Professor Krzysztof Gajos from Harvard University.
Professor Dong Soo Han’s laboratory in KAIST School of Computing developed an on-campus indoor/outdoor navigation system called, ‘Campus Atlas’. The system provides a direction to the destination by simply getting a visitor’s name or the room number of the building. For more information, please refer to the news article in Korean: http://www.dt.co.kr/contents.html?article_no=2015090302109976731002
A paper published from Software Testing and Verification Group (SWTV; Professor Moonzoo Kim’s Laboratory) has been accepted to IEEE/ACM International Conference on Automated Software Engineering (ASE), one of the best conferences in computer science. Congratulations for the approval！ S. Hong, B. Lee, T. Kwak, Y. Jeon, B. Ko, Y. Kim, and M. Kim, Mutation-based Fault Localization for Real-world Multilingual Programs, IEEE/ACM International Conference on Automated Software Engineering (ASE), Nov 9-13, 2015 (acceptance rate: 21％)
Sung-Ju Lee, the professor of KAIST School of Computing, has been appointed as a Technical Program Chair of the IEEE International Conference on Computer Communications (IEEE INFOCOM 2016). Started in 1992, INFOCOM is a prestigious international conference that covers various networking topics such as the Internet, wireless networking, mobility, datacenters, and others. Professor Lee is appointed as a TPC chair of INFOCOM for his contribution to the networking communications research; he is the first Korean to chair the TPC of the conference. He will select 650 technical program committee members who will review more than 1,600 paper submissions. Professor Lee is a leading researcher in wireless mobile networking systems. He is a Fellow of IEEE, and was the General Chair of ACM MobiCom 2014 (International Conference on Mobile Computing and Networking). He also serves on the editorial board of IEEE TMC (Transactions on Mobile Computing) and IEEE Internet of Things Journal. The 34th IEEE International Conference on Computer Communications will be held in April 2016 in San Francisco, California, USA.
The following news reports are about the national first image forensic tool developed in Professor Heung-Kyu Lee’s Laboratory, which is on a web service for testing at 'http://forensic.kaist.ac.kr'. Don’t Even Think About Faking a Picture with Photoshop！ – Donga Science 2015-06-12 The Research Team of Professor Heung-Kyu Lee in KAIST Developed ‘Digital Image Forgery Identification Technology’ In 2008, Iran announced that they launched ‘Shahab-3,’ a medium-range ballistic missile, and gave away the picture of launching four missiles for the proof. However, after revealing the picture, there was a rumor that the picture is a fake. Iran government made no comment about the rumor. Recently, a national research team developed an image forgery detector and verified the image. As a result, the detector found out three suspicious areas on the image, including smoke trails from three missiles. The research team of the professor Heung-Kyu Lee in KAIST developed an image forgery detection tool and created a webpage (forensic.kaist.ac.kr) for testing the tool. For example, if a picture of banana has modified by coloring light green on the top of the banana to make it fresh, the tool notifies the user by highlighting the modified area. Another example is that rafting people on a river; the tool even finds out that the picture is fake, a combined picture of a river and a rafting people. Professor Lee’s Team observed the statistical changes on the picture’s small dots (pixels) when modifying pictures. Using those changes, they developed the technology to find out the image forgery, such as copy-and-paste or retouches. It only takes a few seconds to find out. The research team commented that it would be helpful on research ethics or medical problems by applying the technology to pictures on academic papers, or medical videos. Professor Lee said, “The research on an image forgery detection is important, but there is a lack of research on it,” and he added, “We are planning to research on verifying various images successfully from the testing period.” Daejeon = Reporter Seung Min Jeon of Donga Science, enhanced＠donga.com "Identifying a Picture from Photoshop"… On a KAIST Research Team’s Website – Chosun Ilbo 2015-06-11 By Gun Hyung Park As many people generally use digital pictures, it gets easy to modify pictures using photo editors, such as Photoshop. Modifying pictures can be critical if the picture is used for an evidence on a criminal investigation. A national research team developed an image forgery detection tool and opened to the public. Heung-Kyu Lee, a professor of KAIST School of Computing, said, “We opened a web service detects an image forgery from a digital picture, which is not noticeable to the human eye.” Lee said, “An image forgery technology has been on a research worldwide for more than ten years, but there was an issue on accuracy,” and said, “This technology can identify the forgery with a success rate of 90~95％.” The service is available on the website (forensic.kaist.ac.kr) for anyone, for free. The research team of Professor Lee developed a software application by using three image analyzing techniques introduced in the world. The basic technology is ‘Digital Multimedia Pixel Analysis’ technique. When modifying a picture, the digital image’s small dots (pixel; a smallest element in an image) rapidly cut off or smash. If there is such area, then the image is a fake. The tool also uses the technique detects a pattern generated by Photoshop by analyzing ‘compression’ and ‘restore,’ called, ‘format-based detection’ technique, and a unique pattern generated from each camera, called, a ‘camera-based detection.’ Using this tool, the research team demonstrated the picture of launching ‘Shahab-3’, a medium-range ballistic missile announced by Iran government, is a forgery. At that time, Iran government modified a different picture and announced it to hide the failure to launch the missile. However, the tool detects the alteration successfully. Professor Lee said, “When a user uploads a picture, the tool analyzes and highlights the suspicious area of the image with three analysis techniques in about a minute,” and said, “We believe that we can increase the accuracy by opening this technique to the public.”
The proposal from Scalable Graphics/Geometric Algorithm Lab. (Professor Sungeui Yoon), with the name of, “(SW Star Lab) Nearest Query Software Development for Mass Image Search and Prototype Rendering,” has successfully accepted. The proposal is about developing and extending “Proximity Computing” technology into various practical fields and opening the related software applications into public. The project will be supported up to 8 years with a fund of 0.3 billion KRW (＄0.27 million USD) per year. Also, they will cooperate with Professor Otfried Cheong’s team to develop a strong technology on theory. Please refer to the attached document for more information about SW Star Lab. Government Plans to Raise National SW Technology up to 80％ of the United States 2015.04.12 / PM 02:13 To make a competitive global software company, government enhanced supporting research and development (R&D); government made an objective to improve the software technology of Korea from 73％ up to 80％ of the United States. In addition, government plans to increase the number of global open-source software applications from 2 to 5, and global professional software companies from 20 to 50. On May 12th, MSIP (the Ministry of Science, ICT and Future Planning) prepared for ‘K-ICT SW Global Leadership Strategy’ to create software-driven society and made sure to support for creating a global software company. The strategy is one of the ‘three-year plan on economy,’ to transform the SW R&D project into focusing on raising national software industry to lead the international software markets. ▲ MSIP’s K-ICT SW global leadership strategy K-ICT SW Global Leadership Strategy is classified into three areas: ▲ the main source area ▲ application development area ▲ SW R&D creation of outcome. In the main source area, they select eight main-source areas on software technology, and nominate some graduate school laboratories into ‘SW StarLab’ and support up to 8 years. The eight main-source areas are operating systems, machine learning, intelligent software, database management systems, and others. They designated 10 Star Labs in this year and planning to increase the number up to 25. In an application development area, they support SW R&D project through stages by changing the project into a free competition under the policy that the proposer and performer must be the same. SW R&D project has simplified the applying procedures to help creative and challengeable startups, who have won from contest or the creative economy town, to commercialize and launch new products quickly. They plan to shorten the processing period from 4.5 months ∼ a year to 2.5 months. For developing companies, government is planning to introduce the MOS (Market Oriented SW) project in this year, using the market-selecting and incubating capability of investment companies, including global venture capitals. The GCS (Global Creative SW) project, which is for globalizing companies, will change the process to support R&D and overseas expansions within one-stop. They will announce in April after changing the system from government-leading project to a free competition. To accelerate taking the outcome of the SW R&D project, they reorganize the overall system of the project, such as tasks, evaluations, and maintenance (including quality assurance). They also plan to avoid external performance indicators such as the number of patents and support qualitative indicators, such as the capability of software quality management, the practical use open source software. Also, they apply the open-evaluation to professionalize the evaluation and plan to support improving the capability of software quality management. Yanghee Choi, the Minister of Science, ICT and Future Planning said, “This strategy is for the globalization of the national software industries by transforming the SW R&D project from deployment-oriented project into the achievement-oriented project. Translated the news report from: ZDNet Korea
Interactions, a bi-monthly magazine published by the Association for Computing Machinery (ACM), the largest educational and scientific computing society in the world, features an article that introduces the Human-Computer Interaction (HCI) Lab at KAIST in its latest issue of March and April 2015 (http://interactions.acm.org/archive/view/march-april-2015/human-computer-interaction-lab-kaist). The HCI Lab (http://hcil.kaist.ac.kr/) is run by Professor Geehyuk Lee of the Computer Science Department at KAIST. Started in 2002, the lab conducts various research projects to improve the design and operation of physical user interfaces and develop new interaction techniques for new types of computers. For the article, please go to the link below: ACM Interactions, March and April 2015 Day in the Lab: Human-Computer Interaction Lab ＠ KAIST http://interactions.acm.org/archive/view/march-april-2015/human-computer-interaction-lab-kaist
[Prof. U Kang] The triangle enumeration problem is regarded as one of the fundamental graph mining problems. Its various applications include measuring content quality in social networks and finding spam pages on the Web. With massive input graphs, issues related to the performance of the network and to system failure may arise. To address the issues, this paper describes a new multi-round MapReduce randomized algorithm for enumerating all triangles. The experimental evaluation shows the scalability of the proposed approach – that it can significantly increase the size of data sets that can be processed. [Acknowledgement] · This work was supported by the IT R&D program of MSIP/IITP. [10044970, Development of Core Technology for Human-like Self-taught Learning based on Symbolic Approach]. [Publication] · This was presented at ACM International Conference on Information Knowledge Management (CIKM 2014), which is the most prestigious conference in the field of data mining. [Reference] · Ha-Myung Park, Francesco Silvestri, U Kang, Rasmus Pagh (2014), "MapReduce Triangle Enumeration With Guarentees," ACM International Conference on Information and Knowledge Management (CIKM), 2014
[Prof. Kee-Eung Kim] The ultimate goal of artificial intelligence (AI), which is in essence building intelligent systems, requires computational and mathematical frameworks for intelligent behaviors. At the core of these frameworks lies the principle of rationality, and the decision theory provides a classical but effective tool for building intelligent systems as well as understanding the behavior of humans and animals. My research group at KAIST has been devoted to designing and developing decision-theoretic representations and algorithms for AI. Research Results My research group is working on representations and algorithms for decision theoretic planning problems, including large scale Markov decision processes (MDPs) and partially observable MDPs (POMDPs). Decision theory is one of the most important approaches to understanding and implementing the rational and intelligent behavior. 1. MDPs and POMDPs The classical MDP/POMDP representation has been a useful tool for modeling intelligent behaviors for decades. However, we often encounter the need to extend the standard representation to effectively capture real-world problems. For example, how can we naturally specify the constraints on the properties of desired solutions, or handle the uncertainty in the parameters of the model? As we extend the standard model, how can we address the computational challenges in designing efficient algorithms? We have addressed some of these theoretical issues and presented at top-tier AI conferences. 2. Machine learning of behavioral data The standard way of machine learning for the intelligent behavior is the reinforcement learning (RL). However, the standard setting in RL algorithms assumes prescribed reward functions, which is not an easy task to specify them in practice. Inferring the reward function from the behavior data is referred to as the inverse reinforcement learning (IRL), and its significance has emerged from the connection among RL and other disciplines such as neurophysiology, behavioral neuroscience, and economics. IRL is an important problem for understanding human and animal behaviors, and we have presented our algorithms at a top-tier machine learning conference and journal. 3. Applications Besides theoretical research on representations and algorithms, our group also worked on applications to demonstrate the usefulness of the decision-theoretic AI approach. Our work on applications include spoken dialogue systems and brain-computer interface systems. Awards 1. 2nd place in the POMDP track of the International Probabilistic Planning Competition (IPPC), 2011 2. Best poster award at the Pacific-Rim Conference on Artificial Intelligence (PRICAI), 2010 References Published papers 1. Jaedeug Choi and Kee-Eung Kim,“MAP Inference for Bayesian Inverse Reinforcement Learning”In: Proceedings of Neural Information Processing Systems (NIPS 2011). [Accepted] 2. Jaeyoung Park, Kee-Eung Kim, and Yoon-Kyu Song,“A POMDP-based Optimal Control of P300-based Brain-Computer Interfaces”In: Proceedings of the AAAI Conference on Artificial Intelligence (AAAI) NECTAR Track. 2011. [8th Korean AAAI paper] 3. Dongho Kim, Jaesong Lee, Kee-Eung Kim, and Pascal Poupart,“Point-Based Value Iteration for Constrained POMDPs”In: Proceedings of the International Joint Conference on Artificial Intelligence (IJCAI). 2011. [5th Korean IJCAI paper] 4. Eunsoo Oh and Kee-Eung Kim,“A Geometric Traversal Algorithm for Reward-Uncertain MDPs”In: Proceedings of the Conference on Uncertainty in Artificial Intelligence (UAI). 2011. [1st Korean UAI paper] 5. Pascal Poupart, Kee-Eung Kim, and Dongho Kim,“Closing the Gap: Towards Provably Optimal POMDP Solutions”In: Proceedings of the International Conference on Automated Planning and Scheduling (ICAPS). 2011. [1st Korean ICAPS paper] 6. Jaedeug Choi and Kee-Eung Kim,“Inverse Reinforcement Learning in Partially Observable Environments”Journal of Machine Learning Research (JMLR), 12. 2011. [2nd Korean JMLR paper] 7. Dongho Kim, Jin Hyung Kim, and Kee-Eung Kim,“Robust Performance Evaluation of POMDP-Based Dialogue Systems”IEEE Transactions on Audio, Speech, and Language Processing (TASLP), 19(4). 2011. 8. Youngwook Kim and Kee-Eung Kim,“Point-Based Bounded Policy Iteration for Decentralized POMDPs”In: Proceedings of Pacific-Rim Conference on Artificial Intelligence (PRICAI) / Lecture Notes in Computer Science (LNCS) 6230. 2010. [Best poster award] 9. Jaeyoung Park, Kee-Eung Kim, and Sungho Jo,“A POMDP Approach to P300-Based Brain-Computer Interfaces”In: Proceedings of the ACM International Conference on Intelligent User Interfaces (IUI). 2010. 10. U.S. Patent Application 20110152710,“Adaptive Brain-Computer Interface Device”
[Prof. Min H. Kim] 3D imaging techniques have been broadly used in manufacturing, entertainment and military industries. However, current 3D imaging systems have been limited to capturing and representing only trichromatic 3D objects. This research project extends the spectral dimension of 3D imaging techniques beyond the trichromatic spectrum. It is the first approach to build a complete 3D scanning system that measures the hyperspectral reflectance of solid objects. This research project includes the design and building of a 3D imaging system, the development of 3D imaging algorithms, and several 3D software applications to visualize such hyperspectral 3D image data. The research outcome of this project could be broadly adapted to physically meaningful measurements of hyperspectral material appearance of 3D solid objects in natural science and bio-medical engineering. Schematic overview of the 3D imaging spectroscopy system (ACM Trans. on Graphics, 31(4), 38:1-11, SIGGRAPH 2012) Research Funding ㆍ This work was supported by the National Research Foundation (NRF) of Korea, Samsung Electronics and Microsoft Research Asia additionally. Research Results ㆍ This imaging system was introduced for the first time in ACM Transactions on Graphics, 2012, the top journal in computer graphics. The associated visualization software application was published in ACM Journal on Computing and Cultural Heritage, 2014 such that this work was received a best paper award in 2012 at the International Symposium on Virtual Reality, Archaeology and Cultural Heritage (VAST 2012). References ㆍ M. H. Kim, T. A. Harvey ,D. S. Kittle, H. Rushmeier, J. Dorsey, R. O. Prum, D. J. Brady (2012), "3D Imaging Spectroscopy for Measuring Hyperspectral Patterns on Solid Objects," ACM Transactions on Graphics (Proc. SIGGRAPH 2012), 31(4), July 2012, pp. 38:1-11 (IF=3.361) ㆍ M. H. Kim, H. Rushmeier, J. ffrench, I. Passeri, D. Tidmarsh (2014), "Hyper3D: 3D Graphics Software for Examining Cultural Artifacts," ACM Journal on Computing and Cultural Heritage, 7(3), February, pp. 1:1-19
[Prof. Sue Bok Moon] Via quantitative analysis with the not-sampled, but complete data, we show media-like characteristics of Twitter. Online communication has emerged as a new form of media, and our work is one of the first to demonstrate a quantitative approach for new media research. Research Results Online Social Network (OSN) services are creating a sea of new products and services based on the social networks. OSN services, such as Facebook and Twitter, threaten the established ones, such as Microsoft, Google and Apple. Twitter, a microblogging service, stands out from other OSN services in that its relations are directional and most user profiles and tweets are public. For three months from June 2009, we collected profiles of all Twitter users. Our analysis shows that Twitter has characteristics of not only a social network but also of media. The reciprocity typically over 80％ in social networks is low (less than 50％). Most tweets are of news nature. Retweets expand readership by 100 or more easily. ※Excellency and Expected effects No further explanation is necessary for the influential power of Twitter, as demonstrated in the recent Seoul mayor election. However, in 2009 when we started our research on Twitter, domestic awareness was low and nobody could have imagined the explosive power in the MENA (Middle East North Africa) situations this spring. Our paper, “What is Twitter, a Social Network or a News Media?” published in the World-Wide Web (WWW) conference on April 2010, investigates social phenomena via Twitter and provides statistical approaches on the complete data of Twitter. Our data crawling and analysis methodologies have become a de-facto standard in follow-up research. The Library of Congress in US has decided to archive the entire Twitter data, thus acknowledging the historic significance of massive-scale communication records among hundreds of million users for the first time in human history. Twitter provides an epoch-making data that allows people to collect information and observe its diffusion in an unprecedentedly massive scale and is changing the face of research methodologies in computer science, sociology, politics, business administration, cognitive science and more. Our paper, published in the WWW conference in 2010, is cited more than 2000 times (via Google Scholar) as of July 2014 and we expect the number to increase even more in the coming years. This work has been covered by domestic and foreign press such as ChosunIlbo, HankookIlbo, MIT Technology Review Blog, ReadWriteWeb, the Observer, PC World, Mashable Op-Ed. Computer science graduate courses at Georgia Institute of Technology, UC Santa Barbara and Cornell have included our paper in their lecture material. Non-computer science departments, such as MIT Business School, Bowdoin College sociology department, and the University of California at San Diego Visual Arts Department have also included our work. From 2009 I have given more than 10 invited talks on this paper, including Boston Univ., Northwestern Univ., UC Santa Barbara, Microsoft Research Bangalore, Microsoft Research Redmond, Duke Univ., North Carolina State Univ. This work provides data collection and analysis methodologies for new media studies and falls to the category of fundamental science. It is hard to file for a patent or apply immediate productization from this work but this work reveals basic characteristics of new media, of which knowledge is imperative to designing derivative products or services. Our investigation of human society via online service provides a new direction for interdisciplinary research between computer science, humanities, and social sciences. KAIST established the Web Science and Technology division under the World-Class University program sponsored by the Ministry of Education, Science and Technology, for this kind of interdisciplinary research. In Korea with its world-best high-speed Internet infrastructure and less-than-1％ illiteracy and highly educated work-force, interdisciplinary research could be the guiding light to take our IT industry to the next level. We hope our social network of interdisciplinary collaborators initiated by this Twitter research continues to expand and become a catalyst for explosive growth in our academic excellence. Reference Published papers 1. Haewoon Kwak, Changhyun Lee, Hyunwoo Chun, Sue Moon,“What is Twitter, a Social Network or a News Media?” Proceedings of the World-Wide Web, April 2010, Raleigh, North Carolina.(Acceptance rate: 14％ , Citation: 313) Funding Sources 1. Collect, Analyze and Share for Future Internet : High-Precision Measurement and Analysis Research, 2008.3.1.∼2013.2.28., MKE
[Prof. U Kang] Scalable big graph mining using distributed systems opens new opportunities for the discovery of interesting patterns and anomalies on very large graphs which could not be analyzed before. Article: Graphs are ubiquitous: computer networks, social networks, mobile call networks, biological networks, citation networks, protein regulation networks, and the World Wide Web, to name a few. Spurred by the lower cost of disk storage, the success of social networking sites (e.g. Facebook, Twitter, and Google＋) and Web 2.0 applications, and the high availability of data sources, graph data are being generated at an unparalleled rate. They are now measured in terabytes and heading toward petabytes, with more than billions of nodes and edges. Mining such big graphs helps us find patterns and anomalies which lead to many interesting applications including fraud detection, cyber security, social network analysis, etc. The research team at Prof. U Kang in Department of Computer Science is working on scalable big graph mining which includes two components: scalable algorithms and discoveries on real world graphs. Scalable Algorithms. Traditional graph algorithms assume the input graph fits in the memory or disks of a single machine. However, the recent growth of the sizes in graphs violates this assumption. Since single machine algorithms are not tractable for handling big graphs, the research team at Prof. U Kang is working on designing and developing scalable algorithms and distributed platforms for mining and managing big graphs. Prof. U Kang is the main author of the award-winning Pegasus graph mining software which includes various large scale graph mining algorithms including PageRank, Random Walk with Restart (RWR), diameter estimation, connected components, eigensolver, and tensor analysis. Discoveries on Real World Graphs. The developed scalable algorithms lead to the analysis of large real world graphs, and interesting discoveries of patterns and anomalies which could not be found before. One of the most interesting discoveries is the seven-degrees of separation in one of the largest publicly available Web graphs with ∼7 billion edges. The discovery suggests that the so-called ＇small world' phenomenon exists in the Web, and the distance between any two Web pages is much smaller than people's expectations. Another interesting discovery is the existence of suspicious adult advertisers in the Twitter who-follows-whom social network at 2009 with 3 billion edges. In the scatter plot of degree vs. triangles of Twitter accounts, some famous U.S. politicians have mildly connected followers, while adult advertisers have tightly connected followers, creating many triangles. The reason is that adult accounts are often from the same provider, and the accounts follow each other to boost their rankings, thereby creating many cliques containing triangles. Image caption: Anomaly detection in graph: the degree vs. triangles in the Twitter who-follows-whom social network at 2009. Some famous U.S. politicians have mildly connected followers, while adult advertisers have tightly connected followers, creating many triangles. The reason is that adult accounts are often from the same provider, and the accounts follow each other to boost their rankings, thereby creating many cliques containing triangles. [U KANG AND CHRISTOS FALOUTSOS, BIG GRAPH MINING: ALGORITHMS AND DISCOVERIES, SIGKDD EXPLORATION VOLUME 14 ISSUE 2, DECEMBER 2012.
[Prof. Junehwa Song] Advancing our smartphones as conversational interaction sensing platforms to promote social health in everyday life Article: A team of researchers in Dept. of Computer Science, KAIST are leading new mobile initiatives to build social context platforms and create life-immersive social services. The key inspiration is to advance our commodity mobile devices such as smartphones towards a face-to-face social gateway – to acquire the real-time social contexts and create proactive services naturally overlaid on our everyday face-to-face social lives. Why social? Because it is an integral basis which constitutes many of our daily activities, such as family life, team-oriented works, hanging out with friends, and so on. They believe that stretching out for diverse social contexts around the user will realize the foundation of future mobile systems which achieve holistic understanding on the user’s need and useful life-immersive services. The quest begins with a question, “What would be the primitive context in our face-to-face social interaction?” As the initial and natural step, the research team focused on conversation, which would be the most prevalent tool to communicate with people just in front of us. A number of new technical challenges arises to recognize delicate conversational contexts with commodity mobile devices. In 2013, they reached the first milestone, SocioPhone, a mobile face-to-face interaction platform with highlights meta-linguistic contexts in conversations. SocioPhone is described in a paper published in ACM MobiSys 20131 (International Conference on Mobile Systems, Applications, and Services) by a team of a KAIST graduate Youngki Lee, who is now an assistant professor of Information Systems, Singapore Management University (SMU), and 8 others. SocioPhone abstracts on-going conversations as a sequence of turns and pauses. SocioPhone provides applications with a set of intuitive APIs to monitor rich meta-linguistic context on the fly, without requiring computation-intensive semantic inference on conversation contents. At its core, the SocioPhone runtime monitors conversational turn-centric contexts in a highly-efficient and precise manner based on a new socially-leveraged collaborative sensing scheme. In addition to the paper publication, a live demonstration of SocioPhone won the Best Demonstration Award in ACM HotMobile 20132 (International Workshop on Mobile Computing Systems and Applications), which was conducted by a KAIST graduate student Chulhong Min and 14 others. Continuing the efforts, the research team is now creating compelling applications which are indispensable for a new platform to find its unique values. Notably, they proposed TalkBetter, a prominent initiative for everyday clinical care applications. The paper describing TalkBetter has won the Best Paper Award in ACM CSCW 20143 (International Conference on Computer Supported Cooperative Work and Social Computing), which was authored by an interdisciplinary team of a KAIST graduate Inseok Hwang who is now a research assistant professor of Center for Mobile SW Platform in KAIST, Prof. Dongsun Yim in Dept. of Communication Disorders, Ewha Womans University, and 5 others. They introduced a mobile in-situ intervention service to expedite everyday family-driven care for children with speech impediments. With close collaboration with the speech-language pathologists and the patients regularly taking speech-language care, TalkBetter has been designed and developed as an integrated therapeutic service which facilitates the parents to acquire clinically desirable conversation habits throughout natural conversations, not only depending on simple a-priori prescription as it has been done thus far. Today, many people observe growing concerns about the anti-social effects of smartphones, attempting to suppress the smartphone use in face-to-face social situations. These researches advocate an antithesis of such technophobic skepticisms. They are pursuing the pro-social potential of pervasive mobile devices around us, and realizing the first-of-its-kind mobile systems to enhance our everyday social life experience. These researches were supported by National Research Foundation funded by Ministry of Science, ICT, and Future Planning (MSIP) and IT R&D Program of MSIP/KEIT of the Korean Government. 1. Lee, Y., Min, C., Hwang, C., Lee, J., Hwang, I., Ju, Y., Yoo, C., Moon, M., Lee, U., Song, J. SocioPhone: Everyday Face-To-Face Interaction Monitoring Platform Using Multi-Phone Sensor Fusion. ACM MobiSys 2013, Taipei, Taiwan, June 2013. 2. Min, C., Hwang, I., Lee, J., Hwang, C., Yoo, C., Moon, M., Park, T., Lee, C., Lee, H., Kim, Y., Ju, Y., Lee, Y., Lee, U., Song, J. Demo: Bringing In-situ Awareness to Mobile Systems: Everyday Interaction Monitoring and Its Applications. ACM HotMobile 2013 (Demo), Jekyll Island, GA, USA, February 2013. 3. Hwang, I., Yoo, C., Hwang, C., Yim, D., Lee, Y., Min, C., Kim, J., Song, J. TalkBetter: Family-driven Mobile Intervention Care for Children with Language Delay. ACM CSCW 2014, Baltimore, MD, USA, February 2014. Image caption: Real-time meta-linguistic monitoring and feedback by the smartphone for the on-going conversation between the mother and her son. [PHOTO COURTESY OF THE RESEARCHERS] Image caption: Face-to-face conversation situations and socially-leveraged collaborative sensing scheme for conversational turn monitoring [PHOTO COURTESY OF THE RESEARCHERS]