SOFSEM 2018 := Invited Speakers
SOFSEM 2018 has the following invited plenary speakers:
Main Keynote
Georg Gottlob: Swift Logics for Big Data
Abstract
Abstract: Reasoning with and about big data, in particular, massive web data is a great challenge. On one hand, we aim for powerful inference mechanisms that add value by creating knowledge from the data. Such mechanisms seem to require sophisticated logics with a high expressive power. On the other hand, we need swift inference algorithms with an acceptable computational complexity. In this talk, reasoning formalisms that achieve both are presented: We introduce and describe specific KRR formalisms for big data that belong to the Datalog+/- family of languages. These logical languages extend the well-known Datalog language by additional features (the "+") to gain expressive power, but simultaneously make syntactic restrictions (the “-“) so as to achieve tractability and scalability. After discussing the theoretical foundations of Datalog+/-, some applications to ontological reasoning, web data extraction, data wrangling, and general reasoning about data will be illustrated, among which are some recent commercial applications.
About Georg Gottlob
Georg Gottlob is a Professor of Informatics at Oxford University and at TU Wien. His interests include KR, theory of data and knowledge bases, logic and complexity, problem decompositions, and, on the more applied side, web data extraction, and database query processing. Gottlob has received the Wittgenstein Award from the Austrian National Science Fund, is an ACM Fellow, an ECCAI Fellow, a Fellow of the Royal Society, and a member of the Austrian Academy of Sciences, the German National Academy of Sciences, and the Academia Europaea. He chaired the Program Committees of IJCAI 2003 and ACM PODS 2000. He was the main founder of Lixto, a company that provides tools and services for semi-automatic web data extraction which was acquired by McKinsey & Company in 2013. Gottlob was awarded an ERC Advanced Investigator's Grant for the project "DIADEM: Domain-centric Intelligent Automated Data Extraction Methodology". Based on results of this project, he co-founded Wrapidity Ltd, a company that specializes in fully automated web data extraction that was recently acquired by Meltwater, an international media intelligence firm.
Foundations of Computer Science
Manfred Broy: On the logic of architecture
Abstract
Object-oriented programming is currently the perhaps most successful programming style used in software development. It combines a number of useful concepts in programming in a way that, in particular, the development of large software systems is supported by it. Nevertheless, object-oriented programming shows a number of deficiencies when dealing with cyber-physical systems. First of all, in classical object-oriented programming the execution model is inherently sequential. All attempts to extend or generalize it to parallel execution models without significant changes in the underlying execution model make the understanding of object-oriented programs utterly complicated.
Secondly, the composition of object-oriented programs has some weaknesses and open issues. This is related to the recognized lack of parallel composition and the lack of a parallel execution model as needed usually for the development of cyber-physical systems as we see them nearly everywhere nowadays. A further issue is time and probability which are first class citizens in cyber-physical applications. For cyber-physical systems we need a design concept which supports composition, parallelism, and concurrency and finally real time but keeps all of the advantages of object-oriented programming. In the following we describe an approach to specify and implement systems along the lines of some of the established concepts of object-orientation – such as inheritance and class instantiation – an approach that nevertheless provides an execution model which is parallel and concurrent in nature and supports real time and composition and therefore lays the foundation of a systems engineering style where classical object-orientation can be extended to cyber physical systems in straightforward way.
About Manfred Broy
Manfred Broy’s (Bavarian Center for Digitization and Fakultät für Informatik of Technische Universität München) research is in software and systems engineering both in theoretical and practical aspects. This includes system models, specification and refinement of system com¬ponents, specification techniques, development methods and verification. He is leading a research group working in a number of industrial projects that apply mathematically based techniques and to combine practical approaches to software engineering with mathematical rigor. There the main topics are requirements engineering, ad hoc networks, software architectures, componentware, software development processes, software evolution, and software quality. In his group the CASE tool AutoFocus was developed.
One of the main themes of Manfred Broy is the role of software in a networked world. As a member of acatech under his leadership the study Agenda Cyber-Physical Systems was created for the Federal Ministry of Research to comprehensively investigate the next stage of global networking through the combination of cyberspace and embedded systems in all their implications and potential.
Since January 2016 Professor Broy is founding president of the Bavarian Center for Digitization.
Monika Henzinger: The state of the art in dynamic graph algorithms
Abstract
A dynamic graph algorithm is a data structure that maintains a property of the graph such as its minimum spanning tree as the graph is modified through a sequence of edge insertions and deletions. Designing efficient dynamic graph algorithms has been an active research area since the 80s, with a sequence of breakthrough upper and lower bounds in recent years.
We give a survey of these results.
About Monika Henzinger
Monika Henzinger is Professor at the University of Vienna, heading the research group of Theory and Applications of Algorithms. She received her PhD in 1993 from Princeton University and was an assistant professor at Cornell University, a research at Digital Equipment Corporation, the research director at Google, and a full professor at EPFL. She was awarded an honorary PhD degree from the Technical University of Dortmund, and she received an ERC Advanced Grant, an European Young Investigator Award, and an NSF CAREER Award.
Software Engineering: Advanced Methods, Applications, and Tools
Michel Chaudron: The Quest for Effective Modeling of Software Design
Abstract
Modeling is a common part of modern-day software engineering practice. Little evidence exists about how models are used and how they help in producing better software. In this talk, I will present highlights from my last decade of research in the area of software modeling using UML.
Topics that will be addressed:
- What is the state of UML modeling in practice and in open source projects?
- How can we assess the quality of UML models? Do UML models actually help in creating better software?
In addition, I will overview some of the ongoing projects that aim to enhance the effectiveness of modeling.
About Michel Chaudron
Michel Chaudron is Full Professor at the Software Engineering division, which is part of the joint Department of Computer Science of Chalmers and Gothenburg University in Sweden. Prior to this, he worked at Universities in Leiden and Eindhoven in the Netherlands. He obtained his Ph.D. in the area of formal methods and programming calculi for parallel computing. His research interests are in software architecture, software design, software modeling with a special focus on UML, and software composition. He has an interest in empirical studies in software engineering esp in the aforementioned areas and preferably industrial context. He supports several conferences and journals including (Conf:) MODELS and Euromicro SEAA and (Jnl:) SoSyM and Empirical Studies in Software Engineering (EMSE).
Danny Weyns: Self-Managing Internet of Things
Abstract
Internet of Things (IoT) consists of tiny, networked computers that are used for monitoring and control applications. Critical goals in IoT are energy efficiency and high packet delivery, regardless of changes in traffic load and interference. Dealing with these changes manually results in continuous maintenance. In this talk, I will introduce the basic principles of self-adaptation and show how the approach enables IoT applications to manage themselves, reducing the burden on system operators.
About Danny Weyns
Danny Weyns is professor at the Katholieke Universiteit Leuven. His main research interests are in software engineering of self-adaptive systems. Self-adaptation endows a system with the capability to adapt itself to deal with uncertain operating conditions. His research focuses on formalisms and design models to realize and assure self-adaptation for different quality goals, applying both architecture-based and control-based approaches. Dr. Weyns is also affiliated with Linnaeus University.
Data, Information and Knowledge Engineering
Yannis Manolopoulos: Network Analysis on the Science of Science
Abstract
In today’s vigorous research world with the extensive recording of scientific efforts in online databases and the rising interest to provide data intelligence from the produced data regarding the scientific community, the “science of science” has emerged as a fast growing interdisciplinary field. From this wide coverage of research activity, real world dense and complex networks are formulated to describe the dynamics of science. Bibliographic data have grown in complexity and size exceeding human understanding and the need for automated decision support is evident across scientific stakeholders from funding agencies to hiring committees, from individual scientists to publishing venues. The provocative questions rise: how does scientific collaboration and networking affect research impact, what constitutes a truly influential individual in science and what meaningful interpretable patterns arise in the evolution of science? By leveraging the various networks (collaboration, citation, co-citation, etc.) related to the recording of science, we explore the factors affecting the generation of research and identify mechanisms of effective research collaboration and production. We investigate the interconnectivity and the positioning of scientific entities in their academic cohorts in an attempt to distinguish the truly influential ones and the attributes related to their status. With a case study regarding bibliometric data of the SOFSEM conference, the social, geographical, historical and institutional influences on scientific output are visualized through the decomposition of scientific networks and actionable information is extracted about the social process that leads to scientific impact over time.
About Yannis Manolopoulos
Yannis Manolopoulos is Professor with the Department of Informatics of the Aristotle University of Thessaloniki. He has been with the University of Toronto, the University of Maryland at College Park and the University of Cyprus. He has also served as Rector of the University of Western Macedonia in Greece, Head of his own department, and Vice-Chair of the Greek Computer Society. His research interest focuses in Data Management. He has co-authored 5 monographs published by Springer, textbooks in Greek, as well as >330 journal and conference papers. He has received >11.000 citations from >1700 distinct academic institutions (h-index=51). He has also received 4 best paper awards from SIGMOD, ECML/PKDD, MEDES and ISSPIT conferences and has been invited as keynote speaker in 13 international events. He has served as main co-organizer of several major conferences (among others): ADBIS 2002, SSTD 2003, SSDBM 2004, ICEIS 2006, EANN 2007, ICANN 2010, AIAI 2012, WISE 2013, CAISE 2014, MEDI 2015, ICCCI 2016, DAMDID 2016, CBI 2017, TPDL 2017, DASFAA 2018. He has also acted as evaluator for funding agencies in Austria, Canada, Cyprus, Czech Republic, Estonia, EU, Hong-Kong, Georgia, Greece, Israel, Italy, Poland and Russia. Currently, he serves in the Editorial Boards of (among others) The VLDB Journal, The World Wide Web Journal, The Computer Journal.
Thomas Eiter: LARS - A Framework for Analytic Reasoning over Streams
Abstract
Stream reasoning continuously derives conclusions on streaming data, aiming at high expressiveness under declarative semantics. For this, LARS (a Logic-based Framework for Analytic Reasoning over Streams) has generic window operators to form data snapshots and modalities to access temporal information, and a rule-based language that extends Answer Set Programming to streams. We discuss LARS and its relation to other formalisms, and touch implementation and applications (in part ongoing work).
About Thomas Eiter
Thomas Eiter is Professor of Knowledge-Based Systems in the Faculty of Informatics at TU Wien, Austria. He worked in various fields of Computer Science and Artificial Intelligence, with Knowledge Representation and Reasoning as main area. He served on many editorial boards, steering bodies, and program committees (e.g. chairing KR 2014 and IJCAI 2019); he is a EurAI (formerly ECCAI) Fellow, Corresponding Member of the Austrian Academy of Sciences, and Member of the European Academy of Sciences.
