Friday, June 16, 2023 | 12:30 pm (CET) | Room: S.2.69 | Alpen-Adria Universität Klagenfurt

Univ.-Prof.in Dr.in Martina Seidl | Institute for Symbolic Artificial Intelligence | JKU Linz

Abstract: As the prototypical NP-complete problem SAT, the decision problem of propositional logic, is considered to be hard. Despite this hardness, SAT is very successfully applied in many practical domains, because very powerful reasoning techniques are available. There are, however, problems that cannot be efficiently encoded in SAT. For such problems, formalisms with decision problems beyond NP are necessary. One of such formalisms are quantified Boolean formulas (QBFs), the extension of propositional logic with existential and universal quantifiers over the Boolean variables. The QBF decision problem is PSPACE-complete, making QBF well suitable for encoding and solving many problems from formal verification, synthesis, and artificial intelligence. In this talk, we give a short tour through recent developments in QBF solving.

Bio: Martina Seidl is a full professor of artificial intelligence at the Johannes Kepler University (JKU) in Linz. She obtained her PhD from TU Wien where she worked several years in the Business Informatics Group. In 2010,  she became assistant professor and in 2016 associate professor at the Institute for Formal Models and Verification of the JKU.  Since 2020 she is head of the Institute for Symbolic Artificial Intelligence. In her research, she develops symbolic reasoning techniques based on computational logic. She especially focuses on the theory and practice of quantified Boolean formulas (QBFs) and their applications in the context of formal verification and artificial intelligence.

October 25, 2022 | 09:00 – 11:00 am (CET) | HS 11 | Patrick Rodler | Alpen-Adria-Universität Klagenfurt

Abstract: In the modern world, we are permanently using, leveraging, interacting with, and relying upon systems of ever higher sophistication, ranging from our cars, recommender systems in eCommerce, and networks when we go online, to integrated circuits when using our PCs and smartphones, security-critical software when accessing our bank accounts, and spreadsheets for financial planning and decision making. The complexity of these systems coupled with our high dependency on them implies both a non-negligible likelihood of system failures, and a high potential that such failures have significant negative effects on our everyday life. For that reason, it is a vital requirement to keep the harm of emerging failures to a minimum, which means minimizing the system downtime as well as the cost of system repair. This is where model-based diagnosis comes into play.

Model-based diagnosis is a principled, domain-independent approach that can be generally applied to troubleshoot systems of a wide variety of types, including all the ones mentioned above. It exploits and orchestrates techniques for knowledge representation, automated reasoning, heuristic problem solving, intelligent search, learning, stochastics, statistics, decision making under uncertainty, as well as combinatorics and set theory to detect, localize, and fix faults in abnormally behaving systems.   

In this talk, we will give an introduction to the topic of model-based diagnosis, point out the major challenges in the field, and discuss a selection of approaches from our research addressing these challenges. For instance, we will present methods for the optimization of the time and memory performance of diagnosis systems, show efficient techniques for a semi-automatic debugging by interacting with a user or expert, and demonstrate how our algorithms can be effectively leveraged in important application domains such as scheduling or the Semantic Web.

Bio: Patrick Rodler is a postdoctoral researcher at the Department of Artificial Intelligence and Cybersecurity (AICS), University of Klagenfurt. He holds MSc degrees in Technical Mathematics and Computer Science, and received his PhD degree in Computer Science in 2015 from the University of Klagenfurt. As a researcher, he co-authored more than 50 papers, published in prestigious journals such as Web Semantics, Knowledge-Based Systems, Artificial Intelligence, or Information Sciences, and gave 30 talks at renowned venues such as the AAAI Conference on Artificial Intelligence (AAAI), the European Conference on Artificial Intelligence (ECAI), or the Int’l Conference on Knowledge Representation and Reasoning (KR). As a teacher, he was responsible for 26 university courses and lectures, and in 2018 he was awarded a university-wide prize for excellent teaching by the University of Klagenfurt. His research interests include artificial intelligence in general, and model-based diagnosis, intelligent search, heuristic problem solving, as well as knowledge representation and reasoning in particular.

Slides are animated. Please view in Powerpoint presentation mode.

Dragi Kimovski | Alpen-Adria-Universität Klagenfurt | Friday, December 18, 2020 | 11:00 (CET, 10:00 UTC) | online

Abstract: The computing continuum extends the high-performance cloud data centers with energy-efficient and low-latency devices close to the data sources located at the edge of the network. However, the heterogeneity of the computing continuum raises multiple challenges related to application and data management. These include (i) how to efficiently provision compute and storage resources across multiple control domains across the computing continuum, (ii) how to decompose and schedule an application, and (iii) where to store an application source and the related data. To support these decisions, we explore in this thesis, novel approaches for (i) resource characterization and provisioning with detailed performance, mobility, and carbon footprint analysis, (ii) application and data decomposition with increased reliability, and (iii) optimization of application storage repositories. We validate our approaches based on a selection of use case applications with complementary resource requirements across the computing continuum over a real-life evaluation testbed.

Bio: Dragi Kimovski is a postdoctoral researcher with “Zielvereinbarung” at the Institute of Information Technology (ITEC), University of Klagenfurt. He earned his doctoral degree in 2013 from the Technical University of Sofia. He was an assistant professor at the University for Information Science and Technology in Ohrid, and a senior researcher and lecturer at the University of Innsbruck. During his career, he conducted multiple research stays at the University of Michigan, University of Bologna, and University of Granada. He was a work package leader and scientific coordinator in two Horizon 2020 projects (ENTICE and ASPIDE), and coordinated the OeAD AtomicFog project. He co-authored more than 40 articles in international conferences and journals. His research interests include parallel and distributed computing, fog and edge computing, multi-objective optimization, and distributed processing for bioengineering applications.

Angeliki Katsenou | University of Bristol | September 29, 2020 | 10:00 (CET, 08:00 UTC)

Abstract: Cisco reported in the past reports that the video data share was expected to reach 80% by the year 2023. However, due to the pandemic and recently imposed a remote work lifestyle, this figure is expected to increase even more. Except for the on-demand and conferencing services, the number of users that are generating, storing, and sharing their content usually through either social media platforms or video-sharing platforms is increasing. Meanwhile from the video coding perspective, as video technologies evolve towards improved compression performance, their complexity inversely increases.

A challenge that many video service providers face is the heterogeneity of networks and display devices for streaming, as well as dealing with a wide variety of content with different encoding performance. In the past, a fixed bit rate ladder solution based on a „fitting all“ approach has been employed. However, such a content-tailored solution is highly demanding; the computational and financial cost of constructing the convex hull per video by encoding at all resolutions and quantization levels is huge. In this talk, we present a content-agnostic approach that exploits machine learning to predict the bit rate ladder with only a small number of encodes required.

Bio: Angeliki Katsenou is a Leverhulme Early Career Fellow and is with the Visual Information Lab at the University of Bristol since 2015. She obtained her Ph.D. degree from the Department of Computer Science and Engineering, University of Ioannina, Greece (2014). She received her Diploma in Electrical and Computer Engineering and an M.Sc. degree in Signal and Image Processing from the University of Patras, Greece. She has experience in several FP7 EC-funded and EPSRC projects, such as MSCA-ITN PROVISION and EPSRC Platform Grant EP/M000885/1. Her research interests include perceptual video analysis, video compression, image/video quality, and resource allocation for video communication systems. She has also been involved with conference organization activities and is currently one of the Technical Program Co-Chairs for Picture Coding Symposium (PCS) 2021, Bristol, UK.

The review of the TEWI colloquium of Laura Toni from June 26, 2020 comprises the video and slides (below):

Abstract: A major challenge for the next decade is to design virtual and augmented reality systems (VR at large) for real-world use cases such as healthcare, entertainment, e-education, and high-risk missions. This requires VR systems to operate at scale, in a personalized manner, remaining bandwidth-tolerant whilst meeting quality and latency criteria. One key challenge to reach this goal is to fully understand and anticipate user behaviours in these mixed reality settings.

This can be accomplished only by a fundamental revolution of the network and VR systems that have to put the interactive user at the heart of the system rather than at the end of the chain. With this goal in mind, in this talk, we describe our current researches on user-centric systems. First, we describe our view-port based streaming strategies for 360-degree video. Then, we present more in details our research on of users‘ behaviour analysis, when users interact with the 360-degree content. Specifically, we describe a set of metrics that allows us to identify key behaviours among users and quantify the level of similarity of these behaviours. Specifically, we present our clique-based clustering methodology, information theory and trajectory base in-depth analysis. Finally, we conclude with an overview of the extension of this work to navigation within volumetric video sequences.

Bio: Laura Toni received the M.S. and Ph.D. degrees, both in electrical engineering, from the University of Bologna, Bologna, Italy, in 2005 and 2009, respectively. In 2007, she was a Visiting Scholar at the University of California at San Diego (UCSD), San Diego, CA, USA, and since 2009, she has been a frequent visitor to the UCSD, working on media coding and streaming technologies. Between 2009 and 2011, she was with the Tele-Robotics and Application Department, Italian Institute of Technology, investigating wireless sensor networks for robotics applications. In 2012, she was a Postdoctoral Fellow at UCSD, and between 2013 and 2016, she was a Postdoctoral Fellow in the Signal Processing Laboratory (LTS4) at École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland. Since July 2016, she has been a Lecturer in the Electronic and Electrical Engineering Department, University College London (UCL), U.K. Her research mainly involves interactive multimedia systems, decision-making strategies under uncertainty, large-scale signal processing, and communications. She received the UCL Future Leadership Award in 2016, the ACM Best 10% Paper Award in 2013, and the IEEE/IFIP Best Paper Award in 2012.

The review of the TEWI colloquium of Lucia D’Acunto from June 24, 2020 comprises the video and slides (below):

Abstract: In this talk, I will present the recent advancements on 5G for what concerns support for “the media vertical sector”, i.e., use cases involving the transmission of audiovisual content. I will begin by introducing the research that TNO has conducted on this topic in the past few years, starting with the H2020 TRIANGLE project, were we first adapted network orchestration to “communicate” with media orchestration components, such as a DASH Aware Network Element (DANE). Then, I will explain how we created media-specific 5G slices in the context of the H2020 5GINFIRE project, and what benefits media service providers can expect. I will further discuss about the advantages that edge computing offers to video production, based on our results from the H2020 FLAME project. Finally, I will give an overview of the standardization activities around this topic. I will conclude my talk with an outlook on future developments and offer some reflections on what researchers, telecom operators and service providers can expect.

Bio: Lucia D’Acunto received her PhD in 2012 from Delft University of Technology, the Netherlands, with a thesis on video streaming over peer-to-peer networks. She now works as a senior research scientist at TNO, focusing on video distribution and on the impact of future internet architectures (e.g. ICN, SDN and 5G) on it. She has led and is leading various European research projects on these topics, most notably the open call projects from the European Projects TRIANGLE, 5GINFIRE and FLAME. Since 2016, Lucia is an active participant and contributor to the 3GPP SA4 group, which focusses on mobile and 5G standardization for media applications. Lucia also serves in the organizing committees of several international conferences, usually in the roles of program chair or demo chair, and in the program committees. Lucia also regularly advises European operators on network and TV technologies and contributes to 5GPPP and NEM visions on the 5G Media Vertical and pilots. Lucia has published her research in several papers and journals and holds more than 15 patent applications.

Lucia D’Acunto | TNO | Wednesday, June 24, 2020 | 14:00 (CET, 12:00 UTC) | online (registration required for external attendees)

Abstract: In this talk, I will present the recent advancements on 5G for what concerns support for “the media vertical sector”, i.e., use cases involving the transmission of audiovisual content. I will begin by introducing the research that TNO has conducted on this topic in the past few years, starting with the H2020 TRIANGLE project, were we first adapted network orchestration to “communicate” with media orchestration components, such as a DASH Aware Network Element (DANE). Then, I will explain how we created media-specific 5G slices in the context of the H2020 5GINFIRE project, and what benefits media service providers can expect. I will further discuss about the advantages that edge computing offers to video production, based on our results from the H2020 FLAME project. Finally, I will give an overview of the standardization activities around this topic. I will conclude my talk with an outlook on future developments and offer some reflections on what researchers, telecom operators and service providers can expect.

Bio: Lucia D’Acunto received her PhD in 2012 from Delft University of Technology, the Netherlands, with a thesis on video streaming over peer-to-peer networks. She now works as a senior research scientist at TNO, focusing on video distribution and on the impact of future internet architectures (e.g. ICN, SDN and 5G) on it. She has led and is leading various European research projects on these topics, most notably the open call projects from the European Projects TRIANGLE, 5GINFIRE and FLAME. Since 2016, Lucia is an active participant and contributor to the 3GPP SA4 group, which focusses on mobile and 5G standardization for media applications. Lucia also serves in the organizing committees of several international conferences, usually in the roles of program chair or demo chair, and in the program committees. Lucia also regularly advises European operators on network and TV technologies and contributes to 5GPPP and NEM visions on the 5G Media Vertical and pilots. Lucia has published her research in several papers and journals and holds more than 15 patent applications.