Nanotechnology Centre for Research and Education
Division of Biomaterials and Microbiological Technologies
West Pomeranian University of Technology, Al. Piastów 45, 71-311 Szczecin, Poland
Nanotechnology is rapidly developing field with numerous potential applications in health care. Recent developments in carbon-nanomaterials — graphene in particular — offer a great deal of promise in achieving fast and affordable platform for biosensing. Among dirrefent nanomaterials, graphene has received worldwide attention due to high surface area, excellent electrical conductivity, strong mechanical strength, good thermal conductivity, high charge carrier mobility, good optical transparency and ease of biological as well as chemical functionalization. Such exceptional properties can be used in design of fast, affordable, and simple devices for bioanalysis since appropriate biosensors are required for early stage diagnosis of the disease as well as disease progression monitoring. Depending from the working principle, graphene-based biosensors can utilize their electrical or electrochemical properties to selectively detect proteins, DNA, glucose or cholesterol. Nanomaterial in such biosensor is used to construct a receptor capable to interact with a target analyte. Next, the biological sensing element (bacteria, DNA) connects to a transducer, which does the conversion from biological data to electrical data. The transducer in turn connects to a measuring device translating the electrical signal to a measurable quantity. To fabricate suitable receptor, different printing technologies are utilized, where graphene or graphene-polymer nanocomposites are used as conducting inks. An example of a graphene/polymer ink, that can be printed via ultrasonic, non-contact printing for biological sensing will be presented.
Miroslawa El Fray is the Head of the Division of Biomaterials and Microbiological Technologies and director of the Nanotechnology Centre for Education and Research, and director of Polymer Institute. She graduated from Szczecin University of Technology, where she also received her PhD in 1996. She was a post-doc at the Technical University Hamburg-Harburg, and scientific researcher at the University Bayreuth, Germany (2000-2003). She received her habilitation (DSc) at the Warsaw University of Technology in 2004. She received the Royal Society fellowship in 2005 at the Imperial College London, UK. She is an author and co-author of over 250 scientific papers and several patents (including US patents). Her scientific background is on the polymer synthesis and characterization, biodegradation and modification towards specific biomedical applications (including polymers for artificial heart, heart patches, elastomeric and photocurable networks, and biosensors). Currently, she is employed as full professor at the West Pomeranian University of Technology, Szczecin, contributing to research and education in the filed of polymer chemistry, materials engineering and nanotechnology.
Leiden Institute of Advanced Computer Science / Leiden Centre of Data Science
Leiden University, The Netherlands
In the World, we see that now and then well-known companies are in trouble since they do not innovate in time. They keep their well-established way of operating and adhere to their old fashioned business models. As a keynote speaker, I would like to advice the scientific community to pay more attention in their research to the possibilities of Big Data in relation to innovation.
This relation is rather delicate as can be seen from the following examples.
The prevailing question is: What does Big Data add to this Development?
In the lecture we will emphasize the seven phases of data development, viz. Collecting Data, Cleaning Data, Interpreting Data, Analysing Data, Visualising Data, Narrative Science, Emergence of new Paradigms.
Moreover, emphasis will be placed on Obstacles: Public safety, Narrative Science, Commercial competition, and Privacy and ethics.
Finally, attention will be pointed to Sensitive data such as Racial or Ethnic Origin.
The general rule for companies is that the processing of sensitive data is prohibited without explicit consent (Directive 95/46/EC, article 8).
Jaap van den Herik (1947) studied mathematics at the Vrije Universiteit Amsterdam (with honours), received his Ph.D. degree at Delft University of Technology in 1983 and was appointed as full Professor of Computer Science at Maastricht University in 1987. In 1988 he was appointed as part-time Professor of Law and Computer Science at the Leiden University. In 2008, he moved as Professor of Computer Science to the Tilburg University (2008- 2016). He is the Founding Director of IKAT (Institute of Knowledge and Agent Technology) and TiCC (Tilburg center for Cognition and Communication). In the Netherlands he initiated the research area e-Humanities. Moreover, he was supervisor of 71 Ph.D. researchers. He was active in many organisations, such as JURIX (Honorary Chair), the BNVKI (Honorary Member), the CSVN (Honorary Member), the ICGA, NWO-NCF, ToKeN, CATCH, and the consortium BIGGRID. Van den Herik is ECCAI fellow since 2003, member of the TWINS (the research council for sciences of the KNAW) and a member of the Royal Holland Society of Sciences and Humanities (KHMW). In 2012 he was co-recipient of an ERC Advanced Research Grant (together with Jos Vermaseren (PI, Nikhef) and Aske Plaat). On January 1, 2014 the appointment at the Faculty of Law was broadened to the Faculty of Science. Together with Joost Kok and Jacqueline Meulman he launched Leiden Centre of Data Science (LCDS) and is Chair of the Board of LCDS.
Tokyo Metropolitan University, Japan
Usability has been important factor on the design for the interface of product and system. The current evaluation methods used to assess the usability factors are interview and questionnaires. These are based on the subjective approach, therefore certain limitations are encountered. It is difficult to get the data on usability for a long duration, the quality of evaluation depends on the skill of the evaluator and these evaluation approaches are costly and time-consuming. Then, our research team has been studying the objective usability evaluation methods using biological data, some of which are eye movement and fingertip movement during the operations of the target interface. Based on the analysis of the captured data, the interface design can be sufficiently improved. In the keynote, basic idea and specific experiment of the proposed method will be presented.
Nobuyuki Nishiuchi received his Ph.D. degree in engineering from Yokohama National University, Japan, in 2004. He is currently a Full Professor at Faculty of System Design, Tokyo Metropolitan University. His main research fields are human interface, usability engineering, image processing, ergonomics and biometrics. He served as a member of the International Program Committee for international conferences such as ICBAKE, CISIM and MIT for several times. He is also an Associate Editor of the International Journal of Biometrics. He has published many papers in various national and international journals and conference proceedings.
Institute of Mathematics, University of Warsaw and
Systems Research Institute, Polish Academy of Sciences
Agent-based decision support in solving problems related to Complex Adaptive Systems (CAS) requires relevant computation models as well as methods for incorporating reasoning over computations performed by agents. To model, crucial for CAS, interactive computations performed by agents, we extend the existing Granular Computing (GrC) approach to Interactive Granular Computing (IGrC) by introducing complex granules (c-granules or granules, for short). Agents performing computations learn due to interaction with the environment how to perform actions and through interactions with the environment they discover relevant rules of behavior, not provided a priori. Many advanced CAS tasks may be classified as control tasks performed by agents aiming at achieving the high quality computational trajectories relative to the considered quality measures over the trajectories. Here, new challenges are to develop strategies to control and predict the behavior of the system. We propose to investigate these challenges using the IGrC framework. The reasoning, which aims at controlling computations, in order to achieve the required targets, is called an adaptive judgment. Adaptive judgment is more than a mixture of reasoning based on deduction, induction and abduction. IGrC is based on perception of situations in the physical world. Hence, the theory of judgment has a place not only in logic but also in psychology and phenomenology. This reasoning deals with granules and computations over them. Due to the uncertainty the agents generally cannot predict exactly the results of actions (or plans). Moreover, the approximations of the complex vague concepts, e.g., initiating actions (or plans) are drifting with time. Hence, adaptive strategies for evolving approximations of concepts are needed. In particular, the adaptive judgment is very much needed in the efficiency management of granular computations, carried out by agents, for risk assessment, risk treatment, and cost/benefit analysis. The discussed approach is developed in cooperation with many co-workers, in particular with Dr Andrzej Jankowski and is based on the work on different real-life projects.
Andrzej Skowron, ECCA and IRSS Fellow, received the Ph. D. and D. Sci. (habilitation) from the University of Warsaw in Poland. In 1991 he received the Scientific Title of Professor. He is Full Professor in the Faculty of Mathematics, Computer Science and Mechanics at the University of Warsaw and in Systems Research Institute of Polish Academy of Sciences. Andrzej Skowron is the (co)author of more than 400 scientific publications and editor of many books. His areas of expertise include reasoning with incomplete information, approximate reasoning, soft computing methods and applications, rough sets, rough mereology, granular computing, intelligent systems, knowledge discovery and data mining, decision support systems, adaptive and autonomous systems, perception based computing, and interactive computational systems. He was the supervisor of more than 20 PhD Theses. In the period 1995-2009 he was the Editor-in-Chief of Fundamenta Informaticae journal. He is on Editorial Boards of many international journals. Andrzej Skowron was the President of the International Rough Set Society from 1996 to 2000. He has delivered numerous invited talks at international conferences including a plenary talk at the 16th IFIP World Computer Congress (Beijing, 2000). He was serving as (co-)program chair, advisory board member, and PC member of more than 200 international conferences. He was involved in numerous research and commercial projects including dialog-based search engine (Nutech), fraud detection for Bank of America (Nutech), logistic project for General Motors (Nutech), algorithmic trading (Adgam), control of UAV (Linköping University), and medical decision support (Polish-American Pediatric Clinic in Cracow). Andrzej Skowron was on the ICI Thomson Reuters list of the mostly cited researchers in Computer Science (globally) in 2012
Information Systems Group
Department of Management Science and Engineering
School of Economics and Management
Tsinghua University, Beijing 100084, China
Competitive intelligence is the action of defining, gathering, analyzing, and distributing intelligence about products, customers, competitors, and any aspect of the environment needed to support executives and managers making strategic decisions for an organization. Traditionally, competitive intelligence is detected and analyzed mainly by experts/managers based on the intra-organizational data/information. However, external big data (e.g., query log, social interaction, blog/twitter, online review, helpfulness votes, open media, etc.) becomes a more and more important source for conducting online competitive intelligence analysis, e.g., dynamic competitor identification and competitiveness degrees measuring with Google search query log, customer insights detection from online reviews, incremental competitive intelligence digests extraction with Internet news. Moreover, due to the 4V characteristics of the big data source, some intelligent and automatic methods should be developed to overcome the shortcomings of traditional methods conducted by human experts. In this talk, I will briefly introduce several related novel methods.
Qiang Wei is an associate professor, Information Systems Group, School of Economics and Management, Tsinghua University. He received his PhD in management from Tsinghua University in 2003. In 2007, he worked as an international faculty fellow at Sloan School of Management, MIT, USA. His research interests include big data analytics, data mining and business intelligence, fuzzy logic, etc. He authored 60+ academic papers in acknowledged journals, e.g., INFORMS Journal of Computing, Decision Sciences, Information Sciences, Decision Support Systems, Electronic Commerce Research and Applications, and conferences, e.g., ICIS, INFORMS, IFSA, NAFIPS, IEEE-ICMB, etc. He published several textbooks in Chinese, i.e., “Business Intelligence Theory and Techniques” and “Management System Simulation”. He is serving as associate editors of several journals (e.g., Decision Support Systems, Electronic Commerce Research), a secretary-in-general of Association for Management Sciences and Engineering of China, standing council members of the Society of Fuzzy Mathematics and Fuzzy Systems of China, Association for Information Systems China Chapter, Information Economy Society of China, etc. He got several NSFC grants of China, and organized and participated as keynote/invited speaker, organizing chair, PC member in several international conferences. He has received several awards, e.g., New Century Talent Award (Ministry of Education of China), Excellent Textbook award (Ministry of Education of China), several teaching awards and best paper awards.