Estimating Space-Time Covariance from Finite Sample Sets

Dr. Stephan Alexander Weiss | May 22, 2019 | 11:00 | B02.1.59

Abstract:

Covariance matrices are central to many adaptive filtering and optimisation problems. In practice, they have to be estimated from a finite number of samples; on this, I will review some known results from spectrum estimation and multiple-input multiple-output communications systems, and how properties that are assumed to be inherent in covariance and power spectral densities can easily be lost in the estimation process. I will discuss new results on space-time covariance estimation, and how the estimation from finite sample sets will impact on factorisations such as the eigenvalue decomposition, which is often key to solving the introductory optimisation problems. The purpose of the presentation is to give you some insight into estimating statistics as well as to provide a glimpse on classical signal processing challenges such as the separation of sources from a mixture of signals.

Stephan Weiss. I am a Professor at the University of Strathclyde and head its Centre for Signal & Image Processing. My particular interests are adaptive filtering and array signal processing.

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Why AI is shaping our games

Dr. Johanna Pirker | May 16, 2019 | 10:00 | B01.0.203

Abstract:

AI is used to create parts of our games. It provides intelligent enemy behavior, techniques such as pathfinding or can be used to generate in-game content procedurally. AI can also play our games. The idea to train computers to beat humans in game-like environments such as Jeopardy!, Chess, or soccer is not a new one. But can AI also design our games? The role of Artificial Intelligence in the game development process is constantly expanding. In this talk, Dr. Pirker will talk about the importance of AI in the past, the present, and especially the future of game development.

Bio:

Dr. Johanna Pirker is researcher at the Institute of Interactive Systems and Data Science at Graz University of Technology (TUG). She finished her Master’s Thesis during a research visit at Massachusetts Institute of Technology (MIT) working on collaborative virtual world environments. In 2017, she finished her doctoral dissertation in computer science on motivational environments under the supervision of Christian Gütl (TUG) and John Belcher (MIT). She specialized in games and environments that engage users to learn, train, and work together through motivating tasks. She has long-lasting experience in game design and development, as well as virtual world development and has worked in the video game industry at Electronic Arts. Her research interests include AI, data analysis, immersive environments (VR), games research, gamification strategies, HCI, e-learning, CSE, and IR. She has authored and presented numerous publications in her field and lectured at universities such as Harvard, Berlin Humboldt Universität, or the University of Göttingen. Johanna was listed on the Forbes 30 Under 30 list of science professionals.

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Use, Misuse, and Reuse of Continuous Integration Features

Prof. Shane McIntosh | May 2, 2019 | 14:00 | N.1.42

Abstract:

Continuous Integration (CI) is a popular practice where software systems are automatically compiled and tested as changes appear in the version control system of a project. Like other software artifacts, CI specifications, which describe the CI process, require maintenance effort. In this talk, I will describe the results of an empirical analysis of patterns of feature use and misuse in the Travis CI specifications of 9,312 open source systems. To help developers to detect and remove patterns of misuse, we propose Hansel and Gretel, anti-pattern detection and removal tools for Travis CI specifications. To help developers to rapidly develop and reuse common CI logic, we propose an extension to the TouchCORE modelling tool that allows users to select high-level features from CI feature models and generate an appropriate CI specification. To support this envisioned tool, we perform an initial analysis of common CI features using association rule mining, which yielded underwhelming results.

Bio:

Shane McIntosh is an assistant professor in the Department of Electrical and Computer Engineering at McGill University, where he leads the Software Repository Excavation and Build Engineering Labs (Software REBELs). He received his PhD in Computer Science from Queen’s University, for which he was awarded the Governor General of Canada’s Academic Gold Medal. In his research, Shane uses empirical software engineering techniques to study software build systems, release engineering, and software quality. More about his work is available online at http://rebels.ece.mcgill.ca/.

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A Survey of Evaluation Techniques and Systems for Answer Set Programming

Prof. Francesco Ricca | May 3, 2019 | 11:00 | S.1.42

Abstract:

Answer set programming (ASP) is a prominent knowledge representation and reasoning paradigm that found both industrial and scientific applications. The success of ASP is due to the combination of two factors: a rich modeling language and the availability of efficient ASP implementations. In this talk we trace the history of ASP systems, describing the key evaluation techniques and their implementation in actual tools.

CV:

Francesco Ricca (www.mat.unical.it/ricca) is currently an Associate Professor at the Department of Mathematics and Computer Science of the University of Calabria, Italy. In the same Department he is Coordinator of the Computer Science Courses Council.
He received his Laurea Degree in Computer Science Engineering (2002) and a PhD in Computer Science and Mathematics (2006) from the University of Calabria, Italy, and received the Habilitation for Full Professor in Computer Science (INF/01) in 2017.
He is interested in declarative logic-based languages, consistent query answering, and rule-based reasoning on ontologies and in particular on the issues concerning their practical applications: system design and implementation, and development tools.
He is co-author of more than 100 (peer-reviewed) publications including international research journals (30+), encyclopedia chapters, conference proceedings, and workshops of national and international importance. He has served in program committees of international conference and workshop, such as IJCAI, AAAI, KR, ICLP, LPNMR and JELIA, and has been reviewer for AIJ, JAIR, TPLP, JLC, etc. He is Area Editor of Association for Logic Programming newsletters, and member of the Executive Board of the Italian Association for Artificial Intelligence.

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Forgetful, shortsighted demons in wireless communications (in Kooperation mit der Lakeside Labs GmbH)

Harun Siljak, PhD | February 26, 2019 | 15:30 | B04.1.114 (Lakeside B04, Eingang b, 1. Stock)

Abstract:

The common theme of results presented in this talk is control of complex systems in wireless communications subject to information loss, either because of noise/equipment limitations or because of the controller’s inability to wait long enough or see far enough. Can we reconstruct the past and/or predict the future based on imperfect information and why would we want to do it in the first place?

Bio:

Harun Siljak obtained his BoE and MoE degrees in control engineering from University of Sarajevo in 2010 and 2012, respectively, and his PhD in electrical engineering from International Burch University Sarajevo in 2015. After working at International Burch University and Bell Labs Ireland, he joined Trinity College Dublin as an EDGE Marie Curie Fellow in 2017 to work on his project on complexity and control in distributed massive MIMO. His research interests include physics of computation, reversibility, wave propagation and nonlinear dynamics. His other interests include popular science and science fiction writing, as well as collaborations with artists and writers.

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Random Matrix Theory in Array Signal Processing: Application Examples

Prof. Xavier Mestre | February 25, 2019 | 11:00 | S.1.42

Abstract:

Conventional tools in array signal processing have traditionally relied on the availability of a large number of samples acquired at each sensor or array element (antenna, hydrophone, microphone, etc.). Large sample size assumptions typically guarantee the consistency of estimators, detectors, classifiers and multiple other widely used signal processing procedures. However, practical scenario and array mobility conditions, together with the need for low latency and reduced scanning times, impose strong limits on the total number of observations that can be effectively processed. When the number of collected samples per sensor is small, conventional large sample asymptotic approaches are not relevant anymore. Recently, large random matrix theory tools have been proposed in order to address the small sample support problem in array signal processing. In fact, it has been shown that the most important and longstanding problems in this field can be reformulated and studied according to this asymptotic paradigm. By exploiting the latest advances in large random matrix theory and high dimensional statistics, a novel and unconventional methodology can be established, which provides an unprecedented treatment of the finite sample-per-sensor regime. In this talk, we will see that random matrix theory establishes a unifying framework for the study of array signal processing techniques under the constraint of a small number of observations per sensor, which has radically changed the way in which array processing methodologies have been traditionally established. We will show how this unconventional way of revisiting classical array processing has lead to major advances in the design and analysis of signal processing techniques for multidimensional observations.

Bio:

Xavier Mestre received the MS and PhD in Electrical Engineering from the Technical University of Catalonia (UPC) in 1997 and 2002 respectively and the Licenciate Degree in Mathematics in 2011. During the pursuit of his PhD, he was recipient of a 1998-2001 PhD scholarship (granted by the Catalan Government) and was awarded the 2002 Rosina Ribalta second prize for the best doctoral thesis project within areas of Information Technologies and Communications by the Epson Iberica foundation. From January 1998 to December 2002, he was with UPC’s Communications Signal Processing Group, where he worked as a Research Assistant and participated actively in several European-funded projects. In January 2003 he joined the Telecommunications Technological Center of Catalonia (CTTC), where he currently holds a position as a Senior Research Associate and head of the Advanced Signal and Information Processing Department. During this time, he has actively participated in 8 European projects and two ESA contracts. He has been coordinator of the European ICT project EMPhAtiC (2012-15) and has participated in 6 industrial contracts, some of which have lead to commercialized products. He is author of three granted patents, 9 book chapters, 41 international journal papers and more than 90 articles in international conferences. He has been associate editor of the IEEE Transactions on Signal Processing (2008-11, 2015-present) and associate co-editor of the special issue on Cooperative Communications in Wireless Networks at the EURASIP Journal on Wireless Communications and Networking. He is IEEE Senior member and elected member of the IEEE Sensor Array and Multi-channel Signal Processing technical committee (2013-2018) and the EURASIP Special Area Teams on “Theoretical and  Methodological Trends in Signal Processing” (2015-present) and “Signal Processing in Communications” (2018-present). He has participated in the organization of multiple conferences and scientific events, such as the “IEEE Wireless Communications and Networking Conference 2018″ (general vice-chair), the “IEEE International Symposium on Power Line Communications” (technical chair), the “European Wireless 2014″ (general co-chair), the “European Signal Processing Conference 2011″ (general technical chair), the “IEEE Winter School on Information Theory” 2011 (general co-chair), the “Summer School on Random Matrix Theory for Wireless Communications” 2006 (general chair). He is general chair of the IEEE International Conference on Acoustics, Speech and Signal Processing 2020.

 

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Developing and Evolving a DSL-Based Approach for Runtime Monitoring of Systems of Systems

Priv.-Doz. Dr. Rick Rabiser | February 7, 2019 | 10:00 | S.2.42

Abstract

Complex software-intensive systems are often described as systems of systems (SoS) due to their heterogeneous architectural elements. As SoS behavior is often only understandable during operation, runtime monitoring is needed to detect deviations from requirements. Today, while diverse monitoring approaches exist, most do not provide what is needed to monitor SoS, e.g., support for dynamically defining and deploying diverse checks across multiple systems. In this talk, I will describe our experiences of developing, applying, and evolving an approach for monitoring an SoS in the domain of industrial automation software, that is based on a domain-specific language (DSL). I will first describe our initial approach to dynamically define and check constraints in SoS at runtime, including a demo of our monitoring tool REMINDS, and then motivate and describe its evolution based on requirements elicited in an industry collaboration project. I will furthermore describe solutions we have developed to support the evolution of our approach, i.e., a code generation approach and a framework to automate testing the DSL after changes. We evaluated the expressiveness and scalability of our new DSL-based approach using an industrial SoS. At the end of the talk, I will also present general lessons we learned and give an overview of other projects in the area of software monitoring as well as other areas such as software product lines, that I am currently involved in.

Bio

Rick Rabiser (http://mevss.jku.at/rabiser) is currently a senior researcher at the Christian Doppler Laboratory for Monitoring and Evolution of Very-Large-Scale Software Systems (VLSS) at Johannes Kepler University Linz, Austria. In this lab, he heads the research module on requirements-based monitoring and diagnosis in VLSS evolution, with Primetals Technologies Austria as industry partner. He holds a Master’s and a Ph.D. degree in Business Informatics as well as the venia docendi (Habilitation) in Practical Computer Science from Johannes Kepler University Linz. His research interests include but are not limited to variability management, software maintenance and evolution, systems and software product lines, automated software engineering, requirements engineering, requirements monitoring, and usability and user interface design. Dr. Rabiser co-authored over 120 (peer-reviewed) publications; served in 80+ program committees and 25+ conference and workshop organization committees; and frequently reviews articles for several international journals like IEEE TSE, IEEE TSC, ACM CSUR, EMSE, JSS, and IST. He is also a member of the steering committee of the Euromicro SEAA conference series and a member of the Euromicro Board of Directors (Director for Austria) and the Euromicro Executive Office (Publicity Secretary). He is also an elected member of the steering committee of the International Systems and Software Product Line Conference (SPLC). He currently is the speaker of computer scientists at JKU Linz, who are not full professors (Fachbereichssprecher Mittelbau Informatik).

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Effective model-based approaches for automated software testing

Prof. Giorgio Brajnik | January 23, 2019 | 11:00 | N.1.42 (Germanistik)

Abstract

Testing lies at the heart of software development. Tightly woven with requirements engineering, the testing process influences how software is developed and its quality.  With adoption of agile and devops approaches, the continuous testing process has to rely on a testing strategy that is multi-level and has to balance test automation and exploratory testing.  Because so many things need to be tested, and because the system under test changes very often and rapidly, effectiveness and sustainability of the testing process is a must.

I will present an approach for automating end-to-end testing that is based on UML specifications of the behavior of the system and a toolkit that automatically generates source code supporting definition of high level test cases and related artifacts. In this way, a software development team can avoid dealing with low level details and focus instead on what needs to be tested, what test conditions need to be covered, how test results affect requirements coverage. This kind of information constitutes then a living documentatio of the system specification which can be used to guide exploratory testing. Such an approach is currently being used in mobile apps (in the area of workforce management) and web apps (in the financial domain).

Bio

Giorgio Brajnik is associate professor at the Computer Science Department of the University of Udine, Italy. He holds a degree in Computer Science (from the University of Udine) and a PhD in Computer Science (from the University of Manchester). After working on information search systems, since 1999 his focus is on methods for effective assessment of accessibility and quality of websites and web applications and more recently on model-based techniques for analysis of user interfaces.

At the university he teaches courses on object oriented programming and accessibility and user centered web development.  In ’92 and ’95-’96 he was visiting scholar at the University of Texas at Austin. He has been invited lecturer, panelist and visiting professor in Europe, the U.S. and New Zealand. He participated to several of the W3C working groups dealing with accessibility. He also supervised the development of accessibility testing tools when he was working with a company he cofounded, Usablenet Inc.  Currently he is scientific advisor for Interaction Design Solutions, a startup company he co-founded that is specialized on model-driven techniques for software system testing.

He is program committee member of several conferences, including the International Cross-Disciplinary Conference on Web Accessibility and ACM Assets, for which he was co-chair of the Doctoral Consortium  and also General Chair; he is regular reviewer for several journals. Additional details are available at www.dimi.uniud.it/giorgio/vitae.html.

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Interactive Objects for Graph Algorithmic Thinking

Andrea Bonani | December 10, 2018 | 11:00 | B01.0.14

Abstract:
In parallel with the rapid growth of digital technology and its pervasiveness in everyday life, it emerged the need to introduce knowledge of computer science at school, from the early years of the scholastic curriculum. This is not intended to promote programming careers among students, nor because they shall work in areas related to Information Technology, but because already in the present times, and more in the future, aware citizens must have digital skills and competences in order to be fully integrated into our society.
In the last decade Computational Thinking has gained attention as a way for schools to develop those skills required by the current digital age. Algorithmic thinking is at the core of Computational Thinking and tangible interactive solutions can help children develop algorithmic thinking skills.
This talk focusses on exploratory research concerning tangibles for graphs and graph algorithmic thinking (GAT) for learners aged from 9 to 15 years. The purpose of this research is to promote Algorithmic Thinking at school, by means of multi-sensory physical activities and learning-by-doing. Specifically, the research uses inter-connected interactive tangible objects. Manipulating tangibles fosters interplay between abstraction and concreteness, so as to enable learners to learn through visual and tactile experiences.
By following an action research process, interactive objects for GAT evolved through prototyping and actions-studies. The talk overviews their evolution and delves into its most recent action: an ecological study with learners using tangibles for GAT. It ends by reflecting on results and future work.

CV:
Andrea Bonani is a PhD student at the Faculty of Computer Science, Free University of Bozen-Bolzano. After his graduation from the University of Padua, Italy, he worked as a teacher of Mathematics at the first level of secondary school. Later, he worked for 10 years in the Education Department of the Province of Bozen-Bolzano (Dipartimento Istruzione e Formazione Italiana) as the coordinator of the FUSS project. The FUSS project installed GNU/Linux in all Italian speaking schools of South Tyrol and promoted the use of new technologies among teachers. The focus of his PhD research fits between computer science education and interaction design. In particular, his PhD research is concerned with the design and development of interactive objects for the scaffolding of graphs and graph algorithmic thinking.

 

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The demystification of the robot: Why we need informed people and explainable machines (in Kooperation mit der JOANNEUM RESEARCH Forschungsgesellschaft mbH ROBOTICS, Klagenfurt)

Univ.-Prof.in Dr.in Martina Mara | November 20, 2018 | 13:00 | HS 2

Abstract:
Robotics and Artificial Intelligence entail many opportunities for humanity: From improving medical diagnoses to enabling greater autonomy for the elderly, from cleaning the house to optimizing energy efficiency. In the public discourse, however, smart technologies are customarily represented by the stereotypical image of the android, the artificial replication of the human being. Based on psychological findings, Mara argues that a human-centered approach towards technological development must foster new visions of complementary human-machine relationships instead of fueling fears of substitution. Furthermore, as many outside the expert circles still lack information about technical functions and feel uncomfortable with technology they don’t understand, there is a need for user empowerment: By explaining basic technological concepts to the public and by designing machines that are explainable themselves.

CV:
Prof. Martina Mara is a leading expert on human-robot relationships and head of the Robopsychology Lab at the Johannes Kepler University Linz. Her team explores how autonomous machines should look like, behave, and communicate in order to establish comfortable interaction experiences for varying target groups. She earned her doctorate at the University of Koblenz-Landau’s Institute for Communication Psychology and Media Education with a dissertation on anthropomorphic machines. She regularly speaks at international conferences and she writes about social impacts of emerging technologies in her weekly tech column „Schöne neue Welt“ („Brave new world“). As a member of the Austrian Council for Robotics, she advices the Austrian government in establishing a strategy for the application of robotics and artificial intelligence.

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