Skip to content

Keynote Speakers

1. Professor Shin'ichi Satoh (National Institute of  Informatics (NII), Tokyo, Japan)

Shin'ichi Satoh is a professor at National Institute of Informatics (NII), Tokyo.  He received PhD degree in 1992 at the University of Tokyo.  His research interests include image processing, video content analysis and multimedia database.  Currently he is leading the video processing project at NII, addressing video analysis, indexing,retrieval, and mining for broadcasted video archives.


Talk: Observing Society via Television--- Challenges towards Social Analysis by Using Large-Scale Broadcast Video Archive

We can obtain many interesting aspects only by watching television, e.g., what's going on in Japan and the world, what is the current trends, how is economic activities, and so on.  This talk will introduce couple of trials to automatically analyze such information by computers.  Especially, with NII TV-RECS video archive containing 300,000 hours of broadcast videos, we developed and deployed couple of key technologies including face detection and matching, fast commercial film mining, and visual object retrieval towards social analysis tools.


2. Professor. Dr. Gerhard Rigoll  (Institute for Human-Machine Communication TU München (TUM), Germany)

Gerhard Rigoll obtained the Dipl.-Ing degree from Stuttgart University/ Germany, in 1982. He joined Fraunhofer-Institute (IAO) in Stuttgart and received the Dr.-Ing. degree in 1986 in the area of automatic speech recognition. From 1986 to 1988 he worked as postdoctoral fellow at IBM T.J. Watson Research Centre in Yorktown Heights/USA for the IBM Tangora speech recognition project. He received the Dr.-Ing. habil. degree in 1991 from Stuttgart University with a thesis on speech synthesis. From 1991 to 1993 he worked as a guest researcher in the framework of the EC Scientific Training Programme in Japan for the NTT Human Interface Laboratories in Tokyo/Japan. In 1993 he was appointed full professor of computer science at Gerhard-Mercator-University in Duisburg, Germany. In 2002, he joined Technische Universität München (TUM), where he is now heading the institute for Human-Machine Communication. He has been a visiting professor at Nara Institute of Science and Technology (NAIST) in spring 2005 and is regularly lecturing at Singapore Institute of Technology (SIT) since 2011.

His research interests are in the field of human-machine communication and multimedia information processing, covering areas such as speech and handwriting recognition, gesture recognition, face detection & identification, emotion recognition, person tracking, and interactive computer graphics. Dr. Rigoll is a Senior Member of the IEEE and is the author and co-author of more than 500 papers in the field of pattern recognition, covering the above mentioned application areas. He has supervised more than 40 PhD dissertations during the last two decades. He was Associate Editor of the IEEE Transactions on Audio, Speech and Language Processing and other international journals, has served as session chairman, organizer and member of the program committee for numerous international conferences, and has been the general chairman of the Annual DAGM-Symposium on Pattern Recognition in 2008

Talk: Recent Developments in Multimodal Human-Machine and Human-to-Human Communication

Today, almost everybody can get an impression of the progress in the area of human-machine communication, because one can experience this technology on a daily basis. The best example for this is the development of smartphones, where e.g. Personal Digital Assistants such as Siri from Apple or Cortana from Microsoft have significantly improved the usage of automatic speech recognition. Additionally, other modalities, such as e.g. face detection, emotions or gaze-interaction became more and more involved, so that nowadays multimodal interaction is already reality on advanced smartphones.

This talk will highlight some of these developments by explaining some of the underpinning methods for multimodal HCI, such as statistical pattern recognition and machine intelligence techniques, including deep learning methods. The talk will conclude with the presentation of two relatively new emerging application areas involving a high degree of multimodality: The first one is the area of human-robot interaction (HRI), which became popular due to the transition of robots from autonomously acting machines in factories to interactive assistants for cooperation with humans. The other is in the emerging area of human-to-human communication. Here we present a novel system for videoconferencing, where Augmented Reality (AR) methods are employed in order to project a user interactively into the environment of the other conference participant.


3. Professor Limsoon Wong (National University of Singapore)

Limsoon Wong is a professor of computer science at the National University of Singapore. He currently works mostly on knowledge discovery technologies and their application to biomedicine. He is a Fellow of the ACM, named for his contributions to database theory and computational biology. He was a co-recipient of the ICDT 2014 Test of Time Award for his work on naturally embedded query languages. Limsoon serves on the editorial boards of Information Systems, IEEE Transactions on Big Data, Biology Direct, Drug Discovery Today, etc. He co-founded Molecular Connections, an information extraction and curation services company in India, and oversaw its steady growth over the past decade to some 1000 research engineers, scientists, and curators.

Talk: Some issues that are often overlooked in big data analytics

The arrival of the “big data” era is opening up new avenues in business, healthcare, etc. Much attention has been paid to scaling challenges arising from the huge increase in volume, velocity, and variety. Not as much attention has been paid to non-scaling-related issues that affect a number of fundamental assumptions in current statistical analysis approaches.  Having more data is tremendously helpful in some analysis procedures. At the same time, having more data can also make the same analysis procedures fail in fundamental ways. We discuss some examples of these issues and how they might be fixed.



4. Dr. Koji Zettsu (National Institute of Information and Communications Technology - NICT)

Dr. Koji Zettsu: received Ph.D in Informatics from Kyoto University in 2005. He is a Director of Information Services Platform Laboratory at Universal Communication Research Institute of National Institute of Information and Communications Technology (NICT), Japan.  He was a visiting associate professor of Kyoto University, Osaka University from 2008 to 2012. He was a visiting researcher of Christian-Albrechts-University Kiel, Germany in 2009. He was the technical editor of Value-creating Network sub-working group of New Generation Network Forum, Japan from 2009 to 2010. His research interests are information retrieval, databases and software engineering. He is a member of IPSJ, IEICE, DBSJ and ACM.

Talk:  Cyber-Physical-Social Data Fusion in IoT

Internet of Things (IoT) brings us to the new era of information where information can be collected and communicated among everybody and everything and anything. In this way, cyberspace, physical space and human knowledge and social activities can be synchronized to bring us an ability to monitor the real world under different facets. That will help us to discover useful knowledge from gathered information from cyber- physical-social space and turn these knowledge to wisdoms. In this talk, I am going to discuss the platform for Cyber-Physical- Social Data Fusion that can be built on top of IoT. Event Data Warehouse, being developed by NICT, provides functionality for collecting, integrating, analyzing and visualizing multi-sourced heterogeneous sensing data from cyber, physical social spaces.  The fundamental technologies and potential applications of the Event Data Warehouse are introduced as well as some recent reserch issues.



5. Associate Professor Yuichi Tanaka (Tokyo University of Agriculture and Technology)

 Yuichi Tanaka received the B.E., M.E. and Ph.D. degrees in electrical engineering from Keio University, Yokohama, Japan, in 2003, 2005 and 2007, respectively. He was a Postdoctoral Scholar at Keio University, Yokohama, Japan, from 2007 to 2008, and supported by the Japan Society for the Promotion of Science (JSPS). From 2006 to 2008, he was also a visiting scholar at the University of California, San Diego (Video Processing Group supervised by Prof. T. Q. Nguyen). From 2008 to 2012, he was an Assistant Professor in the Department of Information Science, Utsunomiya University, Tochigi, Japan. Since 2012, he has been an Associate Professor in Graduate School of BASE, Tokyo University of Agriculture and Technology, Tokyo, Japan. His current research interests are in the field of multidimensional signal processing which includes: graph signal processing, image and video processing with computer vision techniques, distributed video coding, objective quality metric, and effective spatial-frequency transform design.

Dr. Tanaka has been an Associate Editor of IEICE Trans. Fundamentals since 2013. Currently he is an elected member of the APSIPA Image, Video and Multimedia Technical Committee. He was a recipient of the Yasujiro Niwa Outstanding Paper Award in 2010, the TELECOM System Technology Award in 2011, and Ando Incentive Prize for the Study of Electronics in 2015. He also received APSIPA ASC 2014 Best Paper Award.

Talk:  Graph signal processing: Extracting information from signals on networks

Graph signal processing is an emerging field of signal processing. It aims to extract useful information from signals on complex (and possibly large-scale) networks. In graph signal processing, signals are treated as graph signals; each element is placed onto a vertex of a graph. Signal processing tasks, e.g., compression, filtering, denoising, and inpainting, will be very efficient and intuitive when we consider graph spectral domain representation of graph signals. There exists numerous applications in sensor network, social network, brain network and image processing. First, fundamentals of graph signal processing are introduced in this talk, such as graph Fourier transform, graph filtering, and downsampling. Then some recent works from my research group in graph wavelet/filter bank design and denoising of graph signals are presented.


6. Professor  Keiji Hirata (Future University Hakodate)

 Keiji Hirata received degree of Doctor of Engineering from University of Tokyo in 1987.  He joined NTT Basic Research Laboratories in 1987 (later changed to NTT Communication Science Laboratories) and Future University Hakodate as professor in 2011.  His research interest includes music informatics (computational music theory), smart city (demand-responsive transportation), ICT support for depression, and video communication system.


Talk:  Introduction to computerized music theory


In this talk, I would like to introduce you to an interdisciplinary research area of computer and music.  At a first glance, music may be considered subjective, ambiguous, and aesthetic.  In reality, however, many musicologists and musicians have been devoting much effort to developing a music theory for understanding and creating music in the systematic and analytic way.  My colleagues and I have been formalizing and computerizing such a music theory.  This talk will focus on some recent results of my work; in particular, the data representation of musical structures such as a melody and a rhythm, the distance between melodies suitable for computer calculation, and the algebraic operations for melodies.



7. Assoc. Prof. Jason J. Jung (Chung-Ang University)

 Dr. Jason J. Jung is an Associate Professor in Chung-Ang University, Korea, since September 2014. Before joining CAU, he was an Assistant Professor in Yeungnam University, Korea since 2007. Also, He was a postdoctoral researcher in INRIA Rhone-Alpes, France in 2006, and a visiting scientist in Fraunhofer Institute (FIRST) in Berlin, Germany in 2004. He received the B.Eng. in Computer Science and Mechanical Engineering from Inha University in 1999. He received M.S. and Ph.D. degrees in Computer and Information Engineering from Inha University in 2002 and 2005, respectively. Dr. Jung serves as Editorial board member of many international journals, e.g., Journal of Universal Computer Science, International Journal of Intelligent Information and Database Systems, International Journal of Social Network Mining and International Journal of Web Engineering and Technology. He has edited 10 special issues in international journals, 2 conference proceedings. He is the author of about 100 international publications. His research topics are knowledge engineering on social networks by using many types of AI methodologies, e.g., data mining, machine learning, and logical reasoning. Recently, he have been working on intelligent schemes to understand various social dynamics in large scale social media (e.g., Twitter and Flickr).


Talk:  Social Data Analytics and Knowledge Management


In this talk, we will survey the state of the art technologies on knowledge management systems (KMS) and the emerging social networking services (SNS). A lot of social activities on SNS are expected to stimulate the KMS (e.g., enriching the knowledge). Thereby, in this talk, we will discuss several issues on integrating
the meaningful features of SNS into KMS.