Stiftinga Vestlandsforsking (Western Norway Research Institute) is a non-profit research and development institute devoted to serve the needs of businesses, industry and public bodies. The institute plays a key role in bringing research and the private and public sectors together as a community builder.
Institute’s Big Data research group specializes in the utilising of big data and semantic science for data integration, analysis and process management. One of our research objectives is to identify value that big data can provide from the discovery of strategic information up to its analysis and exploitation. Our principal research areas are applications of semantic technologies, knowledge discovery in big data, with application to, among others, emergency management, tourism, healthcare, and mobility. Our group has also extensive experience in requirements elicitation, specification, analysis and management; design and execution of empirical studies (case studies, action research); validation of innovative solutions through large scale demonstrations, pilots or testing of use cases in a real setting. We offer cross-industry expertise, technological and socio-economic insight, and commitment to sustainable solutions.
Rajendra Akerkar is a professor of Information Technology at Vestlansforsking, Norway. He leads big data research at the institute. He has 28 years of experience in knowledge representation and reasoning, data science, intelligent systems and requirement engineering. His current research focuses on application of big data methods to real-world challenges (in disaster management, mobility, transport and energy utilities), and social media analysis in a wide set of semantic dimensions. He is currently coordinating two international projects on Big Data in transport and Big Data in emergency management funded by the European Commission (H2020) and the Research Council of Norway respectively. He also participated in the European Union’s 7th Framework Programme funded projects. Rajendra has extensive experience in managing research and innovation projects funded by both industry and funding agencies, including the EU Framework Programs and the Research Council of Norway. He is actively involved in several international ICT initiatives for more than 20 years.
The University of Bergen (UiB) is an internationally recognised research university. Academic diversity and high quality are fundamental for us. UiB is the most cited university in Norway. UiB has six faculties and a total of 14,800 students. Around 1,550 of these are international students. We employ 3,600 staff. PhD candidates are paid employees of staff, making the doctoral degree at UiB particularly attractive for rising talent. About one in three graduating doctors are from outside Norway.
The Department of Information Science and Media Studies is the result of a merger between the two former entities – The Department of Information Science and The Department of Media Studies. The two disciplines joined forces in 2004 against a technological backdrop where convergence within various media and communication forms called for increasingly interdisciplinary research. Core research efforts at the Department includes the study of information and communication technologies, their social and historical developments, their institutional contexts, their contents and their use(r)s.
Semantic and Social Information Systems (SSIS) is one of the research groups in our department. It counts 6 staff members and a larger number of graduate students. The group studies the intersection of two major ongoing developments in the ICT world: semantic technologies and social media. Semantic information systems enable intelligent consumption of data by machines by exposing meaning in data using technologies such as OWL, RDF, and SPARQL, while social information systems such as Facebook, YouTube and Wikipedia are characterised by user-generated content intended for human consumption.
While semantic and social information systems may appear unrelated at first, we believe that they are in fact complementary. Social media tends to produce large collections of user-generated content that can potentially be leveraged by semantic technologies if they can be enriched (or “lifted”) semantically. For example, social technologies can be used to add dynamic, contextual semantics to Information Systems, whereas semantic technologies can be used to make the contents of social information systems more findable and better organised. The intersection of the two fields involve managing and interoperating big data sources that are potentially highly beneficial for managing emergency situations
Andreas Lothe Opdahl is a professor of Semantic and Social Information Systems at the University of Bergen. His general research interest is modelling and analysis of information systems (IS) in an enterprise context. He studies how models can be used to facilitate broad involvement in IS development and enterprise change projects, by including other stakeholder groups in addition to ICT experts and managers. He is particularly interested in how models can be used for identifying and analysing safety and security threats as part of requirements work. He has also investigated how organisations actually use IS models in practice. A related research interest is the semantics of IS and enterprise modelling notations. He is investigating how clearer definitions of notation semantics can contribute to making better models and to facilitate consistency checking and perhaps even automatic translation across different notations. His work on a Unified Enterprise Modelling Ontology (UEMO) is part of this project activity.
Intelligent Perception and Urban Computing Group (IPUC) is a research group directed by Prof. Xuan Song, which is affiliated with Center for Spatial Information Science, The University of Tokyo.
IPUC aims to develop novel algorithms, cutting-edge technologies, and applicable systems to sense human dynamics and mobility, so as to understand human activity and behavior, and to make cities more desirable, livable, sustainable and green. Our goal is to improve lifestyle safety, convenience and intelligence, for individuals and the community. We concentrate on several research themes, such as Urban Computing, Intelligent Perception, Big Data Analytics, Disaster Informatics, and Emergency Management and Response.
Over the past four years, the PIUC has been working in collaboration with Japan government and industry partners (e.g., Microsoft, Hitachi, ZDC Company, JR Company) to construct several intelligent systems or models for disaster reasoning, emergency management, and location/mobility data mining. The research can be summarized as follows: (1) By mining the “Big GPS records” of 1.6 million users in one year, an intelligent system (DBAPRS) was developed to automatically discover, analyze, and simulate population evacuations during the Great East Japan Earthquake and the Fukushima Daiichi nuclear accident. (2) A novel approach to mine and model large amounts of human emergency mobility information following disasters in a city was proposed. (3) An intelligent system for urban emergency management during large-scale disasters was developed that automatically learns a probabilistic model to better understand and simulate human mobility during emergency situations. Based on the learned model, population mobility in various urban areas impacted by the earthquake throughout Japan can be automatically simulated or predicted. (4) An HMM-based human behavior model and urban mobility model was developed to accurately predict human behavior and mobility following large scale disasters. (5) A spectrum based approach was developed to effectively understand human disaster activities in a city. These research results were published in the eminent publications for computer science including ACM TOIS, ACM TIST, KDD 2013 and 2014, IJCAI 2016, UbiComp 2014-2016, AAAI 2014-2016, and IEEE Intelligent Systems. In particular, the research results of the PI on predicting human behavior and mobility following large-scale disasters was highlighted and reported by United Nations Global Pulse, the Discovery Channel and Fast Company Magazine.
Xuan Song received the Ph.D. degree in signal and information processing from Peking University, China, in 2010. From 2010 to 2012, he worked in Center for Spatial Information Science, The University of Tokyo as a post-doctoral researcher. From 2012 to 2015, he worked in Center for Spatial Information Science, The University of Tokyo as a Project Assistant Professor. In 2015, he was promoted to Project Associate Professor with the Center for Spatial Information Science, The University of Tokyo. In the past five years, he led and participated in some important projects as principal investigator or primary actor in Japan, such as DIAS/GRENE Grant of MEXT, Japan; Japan/US Big Data and Disaster Project of JST, Japan; Young Scientists Grant of MEXT, Japan; Research Grant of MLIT, Japan; CORE Project of Microsoft; Grant of JR EAST Company and Hitachi Company, Japan. His main research interest are AI and its related research areas, such as data mining, intelligent system, computer vision, and robotics, especially on intelligent surveillance/reasoning system design, mobility and spatio-temporal data mining, and disaster informatics. By now, he has published more than 40 technical publications in journals, book chapter, and international conference proceedings, including more than 30 high-impact papers in top-tier publications for computer science and robotics, such as ACM TOIS, ACM TIST, IEEE TPAMI, IEEE Intelligent System, KDD, UbiComp, IJCAI, AAAI, ICCV, CVPR, ECCV, ICRA and etc. His research was featured in many Japanese and international media, including United Nations, the Discovery Channel, and Fast Company Magazine. He received Honorable Mention Award in UbiComp 2015.
The Hong Kong Polytechnic University (PolyU) offers 220 postgraduate, undergraduate and sub-degree programmes for more than 32,000 students every year. The Department of Computing of PolyU has secured top positions in various world rankings, for example, 31st in Computer Science in the “Best Global Universities Rankings” released by the U.S. News and World Report in 2017. The Department of Computing (COMP) is devoted to constructing a nurturing environment and creating excellent learning experiences for students, inspiring them to unleash their potentials into becoming future’s innovators. It delivers high quality research postgraduate programmes, taught master programmes and undergraduate programmes in computer science and multi-disciplinary areas of IT and enterprise computing. Its programmes integrate theories, systems and applications, meeting the needs of students who wish to pursue their career in computing related technology. COMP has made significant contributions to research that makes impact, keeping up with the knowledge advancement and global development in computing and information technology and facilitates technology transfer. It engages in a full and extensive spectrum of research areas, with a strategic focus in human-centered computing and big data analytics. It demonstrates its research capabilities through impressive records of winning competitive research grants, high quality publications in prestigious journals and conferences, and strong industrial collaborations.
Prof. Song Guo is a Full Professor and head of Big Data Analytics and Cloud Computing Group at Department of Computing. His research interests are mainly in the areas of cloud and green computing, big data, wireless networks, and cyber-physical systems, especially their applications for disaster management. He has published over 300 conference and journal papers in these areas. His research has been sponsored by JSPS, JST, MIC, NSF, NSFC, and industrial companies, including JST-NSF Big Data for Disaster Management, “BDD: Dynamic Evolution of Smart-Phone Based Emergency Communications Network” and JSPS “A WiFi-based Survivor Tracking and Searching System for Disaster Environment”. He is a senior member of IEEE, a senior member of ACM, and an IEEE Communications Society Distinguished Lecturer.
The Humanitarian & Social Informatics Lab at George Mason University focuses on Humanitarian Informatics as the interdisciplinary science of information systems concerned with welfare of human society, involving representation, processing and management of information and knowledge for decision support by mining large-scale heterogeneous data sources. The lab currently researches basic human behavior problems by mining and fusing online social and open Web data with offline data sources using interdisciplinary computing approaches, guided by domain semantics and socio-psychological theories. We strive to conduct foundational research that is evaluated with real-world challenges.
Hemant Purohit is an assistant professor of Information Sciences & Technology. He is also head of the Humanitarian & Social Informatics Lab at George Mason University. He studies human behavior on the web via an interdisciplinary approach of Computer and Social Sciences. He model individual and group behavior (e.g., intent, comprehension, attitude and engagement) in online communities to design cooperative information systems that mine crowd-generated and opensource data to support organizational decision making. This research is employed into a variety of humanitarian informatics problems for social good, including emergency management, gender-based violence, public health resilience, and STEM efforts assessment. His technical interests are merge top-down and bottom-up data mining approaches by employing domain semantics and guidance from offline socio-behavioral knowledge into statistical methods, and understand online individual and group behavior from unstructured, large-scale social and web data.
San Diego State University (USA)
The Center for Information Convergence and Strategy (CICS) aims to catalyze and nurture the advancement of San Diego State University as a national leader in knowledge-driven, transdisciplinary thinking and solutions. CICS is home to over thirty researchers and subject matter experts, from domains as diverse as climatology, linguistics, religious studies, public administration, international trade, criminology, disaster management, and global security. The center focuses on data acquisition and analytics, social media solutions, strategic mapping, and systems integration and development. CICS deploys computational technologies and domain expertise to evaluate current trends and develop strategies based on evolving content, from advanced visualization to predictive analytics.
André Skupin is a professor of Geography at San Diego State University. He is also the Founder & Co-Director, Center for Information Convergence and Strategy (CICS). Dr. Skupin’s core research area is the application of geographic metaphors, cartographic principles, and computational methods in the visualization of non-geographic information. His work has been strongly interdisciplinary, aimed at increased cross-fertilization between geography, information science, and computer science. These efforts have resulted in new approaches to create map-like knowledge domain visualizations on the basis of vector space models and artificial neural networks. Recent work includes novel methods for visualizing individual human movement and demographic change as trajectories in n-dimensional attribute space.
IIT College of Science offers challenging and rigorous programs in mathematics and the sciences to outstanding students with a thirst for knowledge who want to change the world. The Text Analysis in the Public Interest lab focuses on three core areas: Social Media Analysis, Information extraction and Data mining, and Machine learning. The goal of research is two-fold: (1) to leverage this unprecedented source of data to advance research in automated processing of informal human communication; and (2) to apply these techniques to analyze trends in social media and produce socially beneficial technology.
Aron Culotta is assistant professor of Computer Science within the Computer Science department at Illinois Institute of Technology. Dr. Culotta leads the Text Analysis in the Public Interest Lab, which investigates socially-beneficial applications of natural language processing, machine learning, and text mining algorithms.
The National Institute of Informatics (NII) seeks to advance integrated research and development activities in information-related fields, including networking, software, and content. These activities range from theoretical and methodological work through applications. As an inter-university research institute, NII promotes the creation of a state-of-the-art academic-information infrastructure (the Cyber Science Infrastructure, or CSI) that is essential to research and education within the broader academic community, with a focus on partnerships and other joint efforts with universities and research institutions throughout Japan, as well as industries and civilian organizations.
Yusheng Ji is a Professor at the National Institute of Informatics, Japan. Her research interests include network architecture, traffic control, and performance analysis for quality of service provisioning in wired and wireless communication networks. Dr. Ji is a member of IEICE and IPSJ. She has held various positions, such as Board member of Trustees of IEICE, Steering Committee Member of Quality Aware Internet (QAI) SIG and Internet and Operation Technologies (IOT) SIG of IPSJ, Associate Editor of IEICE Transactions, Guest Editor and Guest Associate Editor of Special Sections of IEICE Transactions, and Associate Editor of IPSJ Journal. She has also served as a TPC member of many conferences, including IEEE ICC, IEEE GLOBECOM, and PIMRC, and was the Mobile and Wireless Networking Symposium Co-Chair of IEEE GLOBECOM 2012.