Assoc.-Prof. Dr. Antorweep Chakravorty | November 25, 2019 | 16:00 | S.2.42

Abstract:

Blockchain is an innovation for creating distributed trust between users facilitating the exchange of value over a network. It can be seen as a decentralized read-only database operated collectively by participants in the network. Participants in the network can be different organizations that provide computing infrastructure to maintain a single version of a decentralized ledger. Each participant locally maintain the same version of this ledger in their own environment and agree upon any updates or changes to its state by employing some consensus algorithms. This enables the trust to be distributed throughout the network, without the need for a central intermediary. The decentralization of trust allows the blockchain technology to be transparent, secure, auditable, redundant and immutable. Since each participant maintains the same version of the truth, it removes the potential of conflict. Additionally, it also enhances the trust of end-users using applications provided by organizations driven by blockchains as they are able to get confirmation about operations on their data from multiple distinct entities rather than a single centralized party. These features of the blockchain has lead to its adoption not only in financial sectors but also in health, energy, IoT, supply chain and smart cities.

CV:

Dr. Antorweep Chakravorty is an Associate Professor at the University of Stavanger. His current research and development work is in the field of applied Blockchains, Big Data, Large Scale Machine Learning and Data Privacy. He has an interest in real-world problems, especially development of privacy enabled data-driven services in smart energy, healthcare and smart city domains. Antorweep completed his PhD. in 2015 with a thesis on Privacy Preserving Big Data Analytics at the University of Stavanger, Norway. Along with having a background in applied research in data-driven solutions, he is also involved in mentoring, teaching and supervision. He spent 6 months on a research exchange program at IBM Thomas J. Watson Research Center, New York, USA.

Prof. Dr. Thomas Eiter | October 25, 2019 | 14:00 | S.2.69

Abstract:

The Contextualized Knowledge Repository (CKR) framework was conceived as a logic-based approach for representing context dependent knowledge, which is a well-known area of study in AI, based on description logics. The framework has a two-layer structure with a global context that contains context-independent knowledge and meta-information about the contexts, and a set of local contexts with specific knowledge bases.  In many practical cases, it is desirable that inherited global knowledge can be „overridden“ at the local level. In order to address this need, an extension of CKR with global defeasible axioms was developed: these axioms locally apply to individuals unless an exception for overriding exists; such an exception, however, requires a justification that is provable from the knowledge base.

The formalization of this intuition has some desirable semantic properties, and furthermore allows for a translation of reasoning tasks on extended CKRs to datalog programs under the answer set (i.e., stable) semantics. This work complements other work on nonmonotonic extensions of description logics with an expressive formalism for exception handling by overriding, and adds to the body of results on using deductive database technology in these areas.

This is joint work with Loris Bozzato and Luciano Serafini (Fondazione Bruno Kessler, Trento).

CV:

Thomas Eiter is a full professor in the Faculty of Informatics at Vienna University of Technology (TU Wien), Austria, and Head of the Institute of Information Systems, where he also leads the Knowledge Based Systems Group. From 1996-1998, he was an associate professor of Computer Science at the University of Giessen, Germany.

Prof. Eiter’s current research interests include knowledge representation and reasoning, computational logic, foundations of information systems, and complexity in AI.  He has contributed to the DLV system and some of its extensions, e.g. the DLVHEX system. He has been involved in various national and international research and training projects, and he has been serving on a number of professional committees and boards. Prof. Eiter’s work has been honored with some best paper awards; he is a Fellow of the  European Association for Artificial Intelligence (EurAI), a Member of the Academia Europea, and a Corresponding Member of the Austrian Academy of Sciences.

Prof. Milan Stehlík | October 18, 2019 | 15:00 | V.1.27

Abstract:

Extracting chaotical and stochastic parts of information from time series needs very specific techniques. Motivated by two applications, image processing for cancer discrimination and methane emissions modelling we will explain the necessary techniques for statistical learning on chaotical and stochastic parts from data. In particular, Tsallis Entropy will be introduced and its role in information theory for dynamical system explained. Iterated function systems will be used as an example for chaos re-simulation. Construction of stochastic fractals will be discussed. We will show the importance of decomposition of data to stochastic, deterministic and chaotic part.

CV:

Professor Milan Stehlík  obtained his PhD in 2003 at Comenius University, Bratislava,  Slovakia,  and he habilitated in Statistics in 2011 at Johannes Kepler University in Linz, Austria. During 1.3.2014-1.10.2015 he was Associate Professor at Universidad Técnica Federico Santa María, Chile. In 2015 he received Full Professorship at University of Valparaiso, Valparaiso, Chile.

Currently he is Visiting professor at the Department of Statistics & Actuarial Science, The University of Iowa. In 2018 he was visiting Full Professor at School of Mathematics & Statistical Sciences Arizona State University, AZ, USA. He was involved in several international projects and collaborations in Austria, Spain, Russia, Canada, Germany, USA among others.

He does research in Extremes, Optimal design of experiments, Statistical Modelling, Neural Computing, Cancer discrimination. He servers as Associate Editor for Europe of Neural Computing and Applications, Associate Editor of Journal of Applied Statistics and Revstat.  He has been Principal Investigator of Innovative project LIT-2016-1-SEE-023 Title: Modeling complex dependencies: how to make strategic multicriterial decisions?  at Linz Institute of Technology, Austria and Chilean FONDECYT Regular. He published more than 180 papers and gave more than 190 talks.

Dario Bauso | Friday 6 September | 11:00am | Lakeside Labs B04b B4 1.114

Abstract: The massive penetration of smart technology has changed energy systems and many other engineering applications such as transportation, logistics, and security. In all these contexts, one often observes a large number of machines and humans interacting with each other. Thus there is a need to redefine the boundaries of some engineering disciplines to accommodate both physical and socio-economic components. Control Engineering, the discipline which studies the ways in which one can control the evolution of a system is no exception. A core concept in control is ‘feedback’ whereby a machine (the controller) gets measurements from sensors about the state of the system one wishes to control and sets the inputs to the system. In the presence of numerous machines and humans, one observes the humans turning into strategic players who learn the environment and make decisions knowing that the environment (which is constituted by the other players) is at the same time learning about them and will react accordingly. This takes the concept of feedback to the next level and opens the floor to a number of game theoretic aspects (learning, incentives, pricing).

In this tutorial I will present new perspectives and challenges arising when dealing with co-existing physical and socio-economic components. I will introduce dynamic games with a large number of players, (also known as mean-field games) and discuss recent trends. I will also discuss the role of strategic thinking and learning in competitive scenarios. The tutorial will conclude with a look at bio-inspired collective decision making problems and related evolutionary game models.

Bio: I received the Laurea degree in Aeronautical Engineering in 2000 and the Ph.D. degree in Automatic Control and System Theory in 2004 from the University of Palermo, Italy. Since 2018 I have been with the Jan C. Willems Center for Systems and Control, ENTEG, Faculty of Science and Engineering, University of Groningen (The Netherlands), where I am currently Full Professor and Chair of Operations Research for Engineering Systems. Since 2005 I have also been with the Dipartimento di Ingegneria, University of Palermo (Italy). From 2015 to 2018 I was with the Department of Automatic Control and Systems Engineering, The University of Sheffield (UK), where I was Reader in Control and Systems Engineering. From 2012 to 2014 I was also Research Fellow at the Department of Mathematics, University of Trento (Italy).

I have been academic visitor in several universities. From October 2001 to June 2002, I was a Visiting Scholar at the Mechanical and Aerospace Engineering Department, University of California, Los Angeles (USA). In 2010 I was short-term visiting scholar at the Department of Automatic Control of Lund University (Sweden) and at the Laboratory of Information and Decision Systems of the Massachusetts Institute of Technology (USA). In 2013 I was visiting lecturer at the Department of Engineering Science, University of Oxford (UK) and at the Department of Electrical and Electronic Engineering of Imperial College London (UK). In 2018-2019 I have been guest professor at Keio University, Japan.

My research interests are in the field of Optimization, Optimal and Distributed Control, and Game Theory. Since 2010 I am member of the Conference Editorial Board of the IEEE Control Systems Society. I was Associate Editor of IEEE Transactions on Automatic Control from 2011 to 2016. I am Associate Editor of IFAC Automatica, IEEE Control Systems Letters and Dynamic Games and Applications. I have also been general chair of the 6th Spain, Italy, and Netherlands Meeting on Game Theory (SING 6).

Prof. Dr. Johannes Huber | 5. September 2019 | 16:00 Uhr | B04.1.06

Zum 250. Geburtstag von Joseph Fourier

Kurzfassung:

Der französische Mathematiker und Physiker Joseph Fourier (1768 – 1830) erkannte, dass jede mathematische Funktion in einem begrenzten Definitionsbereich durch eine Summe von sinus-Schwingungen approximierbar ist, was nicht zuletzt für die Ingenieurwissenschaften von eminenter Bedeutung ist. Im Vortrag wird zunächst versucht, die Grundaussagen der Theorie allgemeinverständlich zu veranschaulichen. Anmerkungen zum Empfinden von Wohlklang und Dissonanz in der Musik anhand der Fourier-Reihenentwicklung von Schallwellen sowie hochaktuelle Erkenntnisse von Fourier zum Treibhauseffekt der Erdatmosphäre aus dem Jahr 1827 ergänzen den Vortrag.

Bio:

Johannes Huber studierte Elektrotechnik an der Technischen Universität München und erwarb 1977 das Diplom. Er wurde 1982 zur Dr.-Ing. promoviert und erhielt 1991 den Titel Dr.-Ing. habil. mit einer Monographie zur Trelliscodierung. Von 1991 bis März 2017 war er Inhaber des Lehrstuhls für Informationsübertragung an der Friedrich-Alexander-Universität Erlangen-Nürnberg. Seit April 2017 ist er Prof. em. am Institute for Digital Communications (IDC) dieser Universität. Von 2007 bis 2009 war er Dekan der Technischen Fakultät.

In der Forschung ist Johannes Huber auf den Gebieten digitale Übertragung, Informations- und Codierungstheorie, codierte Modulation, Entzerrungs- und Detektionsverfahren, MIMO-Übertragungsverfahren, DSL etc. aktiv. Er hat zwei Monographien verfasst und ist Autor und Co-Autor von ca. 340 wissenschaftlichen Veröffentlichungen. In den Jahren 1988, 2000 und 2006 wurden Publikationen, die er verfasst bzw. mit verfasst hat, mit dem Preis der deutschen informationstechnischen Gesellschaft ausgezeichnet. 2004 erhielt er den Innovationspreis der Vodafone-Stiftung für Mobilfunk und in den Jahren 2003 und 2010 wurde ihm der EEEfCOM Innovationspreis verliehen.

Prof. Huber ist Fellow of the IEEE, Corresponding Fellow of the Royal Society of Edinburgh und ordentliches Mitglied der Bayerischen Akademie der Wissenschaften (BAdW). An der BAdW leitet er die Kommission „Forum Technologie“ und ist stellvertretender Sprecher der Sektion III: Naturwissenschaften, Mathematik, Technikwissenschaften

Inzwischen sind 11 seiner ehemaligen Doktoranden selbst Professoren an namhaften Universitäten und Hochschulen.

Der Rückblick zum TEWI-Kolloquium von Prof. Dr. Benjamin Rott am 8. November 2018 beinhaltet das Video und Vortragsfolien (siehe unten):

Kurzfassung:
In der Mathematikdidaktik wird das Problemlösen seit Pólyas „Schule des Denkens“ – mal mehr und mal weniger intensiv – thematisiert. Im Vortrag werden wichtige Ergebnisse entsprechender Forschung resümiert und es werden an konkreten Beispielen aktuelle Forschungsprojekte aus Deutschland erläutert, in denen es u. a. um Heurismen, ihre Wirksamkeit und Lehrbarkeit sowie um Problemlösen im Mathematikunterricht und in der Lehrerbildung geht.

Abschließend wird aus Sicht des Vortragenden beschrieben, wie nächste Schritte auf dem Gebiet der Problemlöseforschung aussehen könnten und sollten.

CV:
Benjamin Rott hat von 2001 bis 2006 Mathematik und Physik für das gymnasiale Lehramt in Oldenburg studiert und anschließend in Salzgitter das Referendariat absolviert. Von 2008 bis 2012 hat er an der Universität Hannover in Mathematikdidaktik promoviert und anschließend eine Postdoc-Stelle an der PH Freiburg angenommen. Von 2014 bis 2017 war Benjamin Rott Juniorprofessor an der Universität Duisburg-Essen und seit 2017 ist er Universitätsprofessor an der Universität zu Köln.
Die Forschungsschwerpunkte von Benjamin Rott sind das mathematische Problemlösen, Überzeugungen und Beliefs zur Mathematik sowie mathematische Begabung.

The review of the TEWI colloquium of Prof. Liang ZHANG (Leon) Ph.D from July 5, 2019 comprises the slides (below):

Abstract:

Dynamic, distributed and open business forces enterprises to support various critical requirements, such as, timely reacting to changes, properly reusing business assets and smoothly collaborating with external partners. Existing approaches focus on mechanisms dealing with heterogeneity, but there is a lack of frameworks enabling legacy business processes performing collaboration in an open service environment. This paper proposes the L2L service framework featuring reactive IoT event messaging and coordinator-based collaborating between autonomous enterprises. Along with the emerging of coordinators, L2L empowers on-the-fly business process collaboration with dynamic changes. We present our experiments with a real-world scenario from the shipping industry of China.

CV:

Liang Zhang is a Professor of Computer Science at Fudan University, China. He received B.S. and Ph.D. degrees in computer science from Wuhan University, China. He has published over 70 journal and conference papers concerning multimedia databases, digital library, web services, and recently business process management (BPM). He is a Steering Committee Member of ICSOC, and has been the PC co-Chair of ICSOC 2013, General co-Chair of ICSOC 2012, publicity co-chair of BPM 2011, program co-chair of CBPM 2011, and NDBC 2011. His current research interests include XaaS infrastructure for CPS, and collaborative workflows for instant virtual organizations. He has been collaborating with Jianwen Su’s group at the University of California, Santa Barbara, Jian Yang’s group at Macquarie University, and Marlon Dumas at Tartu University. Recently, he collaborates with Prof. Hong-Linh Truong Aalto University, Finland, for IoT/BPM integration research. Dr. Zhang’s research has been supported by NSFC and other national agencies.

The review of the TEWI colloquium of PD Dr. Ralf Klamma from June 17, 2019 comprises the video and slides (below):

Abstract:

Augmented Reality (AR) is on the way to establishing itself in business and teaching once more. However, there is a lack of uniform guidelines or even standards both in the creation of teaching materials and in the use of AR in teaching. In addition, the industry needs enough well-trained specialists who can implement the established AR concepts, making a transfer from university to industry necessary. Therefore, in this talk we address both challenges in teaching with AR and the special needs of teaching about AR.

As teaching with AR will surely advance human performance and also brings in new perspectives with the communication, coordination and collaboration of AR in supporting human performance. As computer scientists, we have a European, interdisciplinary and application-oriented perspective, as our experience comes from several funded European projects in these areas. We also incorporate new incentives into teaching contexts in our framework, such as gamification, learning analytics and experience capturing. In addition, we refer to international standardization efforts such as IEEE ARLEM.

Teaching about AR adopts a multi-perspective view. First, there is scientific and technological basic knowledge helping to understand the underlying physical and technical principles. Second, there is engineering and design knowledge to master the creation, fabrication, and utilization of AR in many ways. Third, there is the necessary pedagogical knowledge to transform these complex settings in manageable teaching scenarios and processes, e.g. for higher education curricula.

Here, teaching AR can learn from traditions of science and engineering education as well as from more recent knowledge about computer science education. Examples from recent and on-going European projects will illustrate the argumentation.

CV:

Ralf Klamma holds diploma, doctoral and habilitation degrees in computer science from RWTH Aachen University. He leads the research group “advanced community information systems” (ACIS) at the information systems chair, RWTH Aachen University. He is known for his work in major EU projects for Technology Enhanced Learning (PROLEARN, GALA, ROLE, Learning Layers, TELMAP, Tellnet, CUELC, SAGE, BOOST, VIRTUS and WEKIT).

Ralf organized doctoral summer schools & conferences in Technology Enhanced Learning, Web Engineering and Social Network Analysis. He serves as associate editor for Social Network Analysis and Mining (SNAM), Frontiers of AI for Human Learning and Behavior Change and the International Journal on Interaction Design & Architecture(s) (IxD&A).

He was associate editor for IEEE Transactions on Learning Technologies (ToLT). His research interests are community information systems, serious games, augmented reality & wearables, web engineering, social network analysis, requirements engineering and technology enhanced learning.

Prof. Dr.-Ing. Heiko Hamann | July 8, 2019 | 15:00 | B02.2.05

Abstract:
In similar style to the book of the same title we try to understand how to design large-scale robot systems by going through several example scenarios on topics such as aggregation, task allocation, self-assembly, collective decision-making, and collective construction. We study the methodology behind building multiple, simple robots and how the complexity emerges from multiple interactions between these robots such that they are able to solve difficult tasks.

CV:
Heiko Hamann received his doctorate in engineering from the University of Karlsruhe, Germany in 2008. He did his postdoctoral training in modular robotics and evolutionary robotics at the Zoology department of the University of Graz, Austria. From 2013 to 2017 he was assistant professor of swarm robotics at the University of Paderborn, Germany. Since 2017 he is full professor for service robotics at the University of Lübeck, Germany. His main research interests are swarm robotics, evolutionary robotics, and modeling of complex systems.