Prof. Dr. Takayuki ITO
Head, Department of Techno-Business Administration, Department of Computer Science and Engineering, Graduate School of Engineering, Nagoya Institute of Technology, Japanhttp://www.itolab.nitech.ac.jp/~ito/
Dr. Takayuki ITO is Professor of Nagoya Institute of Technology. He received the B.E., M.E, and Doctor of Engineering from the Nagoya Institute of Technology in 1995, 1997, and 2000, respectively. From 1999 to 2001, he was a research fellow of the Japan Society for the Promotion of Science (JSPS). From 2000 to 2001, he was a visiting researcher at USC/ISI (University of Southern California/Information Sciences Institute). From April 2001 to March 2003, he was an associate professor of Japan Advanced Institute of Science and Technology (JAIST). From 2005 to 2006, he is a visiting researcher at Division of Engineering and Applied Science, Harvard University and a visiting researcher at the Center for Coordination Science, MIT Sloan School of Management. From 2008 to 2010, he was a visiting researcher at the Center for Collective Intelligence, MIT Sloan School of Management. He is a board member of IFAAMAS, Executive Committee Member of IEEE Computer Society Technical Committee on Intelligent Informatics, the PC-chair of AAMAS2013, PRIMA2009, General-Chair of PRIMA2014, and was a SPC/PC member in many top-level conferences (IJCAI, AAMAS, ECAI, AAAI, etc). He received the JSPS Prize, 2014, the Prize for Science and Technology (Research Category), The Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science, and Technology, 2013, the Young Scientists' Prize, The Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science, and Technology, 2007, the Nagao Special Research Award of the Information Processing Society of Japan, 2007, the Best Paper Award of AAMAS2006, the 2005 Best Paper Award from Japan Society for Software Science and Technology, the Best Paper Award in the 66th annual conference of 66th Information Processing Society of Japan, and the Super Creator Award of 2004 IPA Exploratory Software Creation Projects. He is Principle Investigator of the Japan Cabinet Funding Program for Next Generation World-Leading Researchers (NEXT Program). Further, he has several companies, which are handling web-based systems and enterprise distributed systems. His main research interests include multi-agent systems, intelligent agents, group decision support systems, agent-mediated electronic commerce, and software engineering on offshoring.
Harnessing Online Large-scale Discussion based on Facilitation and Incentive Mechanisms
Much attention has been focused on the collective intelligence of people worldwide. Interest continues to increase in online democratic discussions, which might become one of the next generation methods for open and public forums. To harness collective intelligence, incentives for participants are one critical factor. If we can incentivize participants to engage in stimulating and active discussions, the entire discussion will head in fruitful ways and avoid negative behaviors that encourage "flaming." "Flaming" means a hostile and insulting interaction by Wikipedia. In our work, we developed an open web-based forum system called COLLAGREE that has facilitator support functions and deployed it for an internet-based town meeting in Nagoya as a city project for an actual town meeting of the Nagoya Next Generation Total City Planning for 2014-2018. Our experiment ran on the COLLAGREE system during a two-week period with nine expert facilitators from the Facilitators Association of Japan. The participants discussed four categories about their views of an ideal city. COLLAGREE registered 266 participants from whom it gathered 1,151 opinions, 3,072 visits, and 18,466 views. The total of 1,151 opinions greatly exceeded the 463 opinions obtained by previous real-world town meetings. We clarified the importance of a COLLAGREE-type internet based town meeting and a facilitator role, which is one mechanism that can manage inflammatory language and encourage positive discussions. While facilitators, who are one element of a hierarchical management, can be seen as a top-down approach to produce collective discussions, incentive can be seen as a bottom-up approach. In this talk, we also focus on incentives for participants and employ both incentives and facilitators to harness collective intelligence. I propose an incentive mechanism for large-scale collective discussions, where the discussion activities of each participant are rewarded based on their effectiveness. With these incentives, we encourage both the active and passive actions of participants. In this talk, I will present preliminary results with a large scale experiment with the Aichi-Prefecture local government in Japan.
Prof. Dr. Rudolf Marcel Fuechslin
School of Engineering ZHAW - Zurich University of Applied Sciences Technikumstrasse, Germanyhttp://www.zhaw.ch/fileadmin/php_includes/popup/person-detail.php?kurzz=furu
Ruedi F?chslin studied theoretical physics at ETH in Zurich, where he graduated with a thesis on incompressible quantum systems at the chair of Prof. J?rg Fr?hlich.
He then went to the University of Zurich, where he wrote his PhD thesis in the newly established group for computer assisted physics of Prof.
Peter Fritz Meier in the field of superconductivity. During this time, he had the opportunity to act together with Meier as a consultant for the Institute
for Forensic Medicine. This experience fostered his interest in biological and medical problems. He had the luck to become a post doc in Prof. John McCaskill's group
for Biomolecular Information Processing where he investigated molecular ecologies, evolutionary processes and dynamical processes in cells. In 2007,
he got the opportunity to spend half a year at the ECLT, where he studied the scaling behavior of dissipative particle dynamics. He then returned
to the University of Zurich, where he got a position in Prof. Rolf Pfeifer's Artificial Intelligence Lab. Presently, he holds a position as professor of applied
complex systems science and is heading the group for Applied Complex System Science at the Institute for Applied Mathematics and Physics at the School of
Engineering at the Zurich University of Applied Sciences. In addition, he is co - director of the European Centre for Living Technology in Venice,
Italy. Besides research, he has interested in questions relating to the interplay between natural sciences and the humanities.
His research interest are:
- Modeling of complex systems
- Mathematical engineering
- Evolutionary methods
- Biomimetic systems
- Modeling of socio - technical systems
- Applied statistical physics
- Applied Morphological Computing (prosthetics, living technology, systems medicine)
- Topics at the interface between physics, biology, sociology and computer science
Morphological Control - Applied Embodied Intelligence in Mechanical and Biological Systems
Present computer science distinguishes sharply between hard- and software. Stripping off all physics from the abstract concept of computation yields such wonderful results as higher - level languages, abstraction and portability. However, there is a price to pay: Controlling physical processes, e.g. a robot, requires bringing back physics via a lot of coding. Additionally, distinguishing hard- and software may facilitate the work of human engineers and programmers but seems to be less relevant in control systems resulting from an evolutionary process. This talk presents the concept of morphological control. The physical dynamics of a computing system are not anymore regarded as something that, in the best case, doesn't disturb a computation but is an essential part of it. In short, morphological control exploits physical dynamics for control purposes. This approach requires a close collaboration between experts from computer science, dynamical systems theory, control theory and machine learning. Morphological control offers new perspectives to Creativity Support Systems by presenting a control paradigm that is intended to be closer to biological systems. Biomimetic technology aims at exploiting the ways and means of nature for the purpose of optimizing engineered systems. Whereas most bionics focusses on the means (materials), the focus in morphological control is put on the ways (organizational principles) and to learn how nature's evolved process management can be used in rationally planned engineering. Most often, morphological control is illustrated by and used for applications in robotics. Our interpretation broadens the concept and includes also systems that are governed statistical mechanics. This means that also cellular dynamics can be understood from the perspective of morphological control. With respect to applications, this talk also includes instances of morphological control in biology and medicine and analyses them from a practical as well as theoretical perspective.
Prof. Dr. Takeshi Tokuyama
Graduate School of Information Sciences(GSIS), Tohoku University, Sendai, Japan.http://www.dais.is.tohoku.ac.jp/~tokuyama/profile_e.htm
Prof. Dr. Takeshi Tokuyama received Ph. D. in mathematics from U. Tokyo in 1985, and worked as a research staff member of IBM Tokyo Research Laboratory from 1986 to 1999. From 1999, he has been a professor in Graduate School of Information Sciences (GSIS) of Tohoku University, and he is currently the dean of GSIS from 2014. His interest includes Theoretical Computer Science and Discrete Mathematics, Computational Geometry and related combinatorics. He received several awards including IPSJ Research Award 1992, ISAAC Best Paper Award 1997, IBM Japan Science Award in 2002, and Funai Information Science Promotion Contribution Award in 2008. He is a fellow in Information Processing Society of Japan and The Institute of Electronics, Information and Communication Engineers.
Theoretical Computer Science for Big Data Analysis: Recent Activities in Japan.
Theoretical Computer Science (TCS) is the most fundamental research area in computer science, and it historically has given foundations of IT design. In this talk, I would like to explain the contribution of TCS to big data analysis, and introduce research activities of collaborative projects of TCS and Big Data Analysis in Japan.
Prof. Dr. Ryosuke Shibasaki
Center for Spatial Information Science and Division of Environmental Studies Department of Socio-Cultural and Socio-Physical Environmental Studies, The University of Tokyo, Kashiwa Campushttp://shiba.iis.u-tokyo.ac.jp/index-e.html
Ryosuke Shibasaki is a professor at the Center for Spatial Information Science, University of Tokyo. His research interests cover geospatial data acquisition, data assimilation for moving objects like people and vehicles, geo-intelligence, and context-aware services based on personal behavior model. He obtained a Ph.D. in remote sensing/GIS from the University of Tokyo in 1986. His past work experience includes associate professor at the Department of Civil Engineering (1988-1991) and at the Institute of Industrial Science, the University of Tokyo (1991-98), professor at the Center for Spatial Information Science (1998-present), and director of the University of Tokyo (2005-2010). He was a former president of the Asian GIS Association and former president of the GIS Association of Japan. He served as board member of the Japanese Society of Photogrammetry and Remote Sensing, the Infrastructure Implementation Board (IIB) and Group of Earth Observations (GEO), and as member of Scientific Committee of WDS (World Data System) and ICSU (International Council of Scientific Union).
Challenges of Mobile Big Data: Methodologies and Applications
Along with the penetration of ICT in society and the advance and spread of sensors, measurement instruments and observation equipment for gathering information in the real world, the amount of data obtained from various fields has grown exponentially and continues to become more diverse. Advanced integration and use of big data are expected to bring about science and technology innovation and the creation of intellectual value through new scientific discoveries, with development of the resulting knowledge leading to creation of social and economic value as well as improvement and optimization of services. Particularly mobile devices become normal communication tools for everyone in this modern society. This talk will provide recent advances in methodologies and applications of mobile big data for implementing a great social impact. In order to make scientific discoveries, solve challenging social and economic problems and achieve innovative value creation, large-scale and diverse relevant data which could not be accumulated by individual researchers or organizations will be mutually related and subjected to a high level of integrated analysis. Challenges in the mobile big data are listed and analyzed.
Dr. Virach Sornlertlamvanich
Sirindhorn International Institute of Technology, Thammasat Universityhttps://www.siit.tu.ac.th/professor_en.php?id=445
Dr. Virach Sornlertlamvanich received his bachelor and master degrees in Engineering from Kyoto University, and doctoral degree in Computer Science from Tokyo Institute of Technology. From 1990 to 2014, he was a principal researcher of National Electronics and Computer Technology Center (NECTEC), Thailand. Currently he is a professor at Sirindhorn International Institute of Technology, Bangkadi Campus, Thammasat University. He got ASEAN Outstanding Engineering Achievement Award 2011 from ASEAN Federation of Engineering Organisations (AFEO) in 2011, a Consolation Prize for "Software and Device for Supporting Arm, Leg Disabled and Paralysis Impaired Persons in Using Computer", awarded by The National Research Council of Thailand for Innovation in Science, Technology and Industry section in 2005, "The Most Outstanding Researcher of the Year 2003 (Information Technology and Communication)" awarded by The National Research Council of Thailand in 2003, a Consolation Prize for "Thai Text to Speech Engine", awarded by The National Research Council of Thailand for Innovation in Science, Technology and Industry section in 2002, and "The Researcher of the Year 2001" from The Nation in 2001. He is the author of more than 10 papers in a number of journals and more than 100 conference papers. His research interests include natural language processing, human language technology, information retrieval, data mining, artificial intelligence, machine learning and the related field.
Natural Language Processing and Its application to Creativity Support Systems
The talk will formalize the three fundamental problems in natural
language processing. Those are word segmentation, named entity
recognition or keyword extraction, and semantic relation
extraction. In the flood of information today, we spend most of the
time to grasp the essence of the information rather than to enjoy the
reading. Many approaches have been proposed to handle these
fundamental issues, however, there is still much room for
improvement. The introduced approach is not the best one, but it is
aimed to make the problem well recognized. Mutual information and
entropy are effective measures to uncover the possible word boundary
for the non-segmenting languages such as the Thai language. It is
remarkably to note that with the approach, the result has shown that
about 30% of the extracted words are not defined in the Thai-Thai
dictionary published by Thai Royal Institute in 1982. Keyword labeling
is also a task that we can effectively apply a machine learning
approach such as MIRA (Margin Infused Relaxed Algorithm) to capture
the word surrounding context. This can be done on the result from the
word segmentation task. Undoubtedly, the accuracy of the annotated tag
is ranked from person (PER), date (DAT), location (LOC), and
organization (ORG). This is because tag for person has the least
ambiguity. The pattern for extracting the semantic relation between
the type-annotated keywords is accordingly assigned to the word form
of the disambiguated verb phrase. The experimental result shows that
most of the distance between the keyword and the target verb phrase is
not more than one word. Therefore, we can find the target verb phrase
in the adjacent position or one word skipped position with the highest
Based on the solution for the above discussed NLP fundamental issues, many more tasks are made possible on the current viable Internet connection. The talk demonstrates the three constructive applications on the huge generated data i.e. linked data formation for knowledge map reasoning; keyword tracking on social media to understand the online social movement; and hyper local news publishing to fill in the information gap between urban and rural life. The task of natural language processing today is not just only for the language itself any more, but it can bring along the possibilities on the advance of the Internet, big data, and machine learning technique.