Speakers for 2024
Title : Behavioral patterns discovery and analysis: issues and challenges
Prof. Daniela Grigori
Bio: Daniela Grigori is a full Professor of computer science at University Paris Dauphine-PSL since September 2011 and she has been the head of LAMSADE CNRS laboratory the last six years. Her current research interests include process management, data and process analytics, data integration and graph analytics. She has a number of papers in major international conferences and journals and has served as organizer and program committee member in many conferences. She is the co-author of a book on process analytics.
Abstract: Event logs that are recorded by information systems provide a valuable starting point for the analysis of processes in various domains, reaching from healthcare, through logistics, to e-commerce. Specifically, behavioral patterns discovered from an event log enable operational insights, even in scenarios where process execution is rather unstructured and shows a large degree of variability. While such behavioral patterns capture frequently recurring episodes of a process’ behavior, they are not limited to sequential behavior but include notions of concurrency and exclusive choices. However, their discovery requires a high computational effort, and their analysis should be facilitated by a compact visualization and by a methodology helping users to understand correlations between patterns and their context. In this talk we therefore present an approach to efficiently discover contextual behavioral patterns. Moreover, we show how to analyze the discovered contextual behavioral patterns in terms of causal relations between context information and the patterns, as well as correlations between the patterns themselves. We conclude by identifying future research directions.
Title : Towards Active Inference for Distributed Intelligence in the Computing Continuum
Prof. Schahram Dustdar
Head of the Research Division of Distributed Systems at the TU Wien, Austria and part-time ICREA Professor at UPF, Barcelona
Bio: Schahram Dustdar is a Full Professor of Computer Science at the TU Wien, heading the Research Division of Distributed Systems, Austria as well as and part-time ICREA Professor at UPF, Barcelona. He holds several honorary positions: University of California (USC) Los Angeles; Monash University in Melbourne, Shanghai University, Macquarie University in Sydney, and University Pompeu Fabra, Barcelona, Spain. From Dec 2016 until Jan 2017 he was a Visiting Professor at the University of Sevilla, Spain and from January until June 2017 he was a Visiting Professor at UC Berkeley, USA. From 1999 – 2007, he worked as the co-founder and chief scientist of Caramba Labs Software AG in Vienna (acquired by ProjectNetWorld AG), a venture capital co-funded software company focused on software for collaborative processes in teams. He is the co-founder of CooVally.com in Barcelona and co-founder and chief scientist of Sinoaus.net, a Nanjing, China-based R&D organization focusing on IoT and Edge Intelligence. He serves as Editor-in-Chief of Computing (Springer). Dustdar is the recipient of multiple awards: IEEE TCSVC Outstanding Leadership Award (2018), IEEE TCSC Award for Excellence in Scalable Computing (2019), ACM Distinguished Scientist (2009), ACM Distinguished Speaker (2021), IBM Faculty Award (2012). He is an elected member of the Academia Europaea. The Academy of Europe, as well as an IEEE Fellow(2016) and an Asia-Pacific Artificial Intelligence Association (AAIA) Fellow (2021) and was AAIA president (from 2020-2021).
Abstract: Modern distributed systems also deal with uncertain scenarios, where environments, infrastructures, and applications are widely diverse. In the scope of IoT-Edge-Fog-Cloud computing, leveraging these neuroscience-inspired principles and mechanisms could aid in building more flexible solutions able to generalize over different environments. A captivating set of hypotheses from the field of neuroscience suggests that human and animal brain mechanisms result from a few powerful principles. If proved to be accurate, these assumptions could open a deep understanding of the way humans and animals manage to cope with the unpredictability of events and imagination.
Title : Edge AI and 6G
Dr. Tao Zhang, National Institute of Standards and Technology (NIST) – USA
Bio: Dr. Tao Zhang has been leading research, development, and corporate strategies over 30 years. He is now managing the Transformational Networks and Services Group at the National Institute of Standards and Technology (NIST), leading research in areas including 6G networks, edge and distributed AI, and automated driving. Prior to joining NIST, Tao was the CTO for the Smart Connected Vehicles Business Unit at Cisco Systems, and the Chief Scientist for mobile and vehicular networking at Telcordia Technologies (formerly Bell Communications Research). He holds over 60 US patents, co-authored two books on vehicular networks and all-IP (Internet Protocol) mobile networks, and published over 150 technical papers. He served as the CIO and a Board Governor of the IEEE Communications Society and a Distinguished Lecturer of the IEEE Vehicular Technology Society. Dr. Zhang is a Fellow of the IEEE, a Fellow of the Society for Information Reuse and Integration, and a Fellow of the Asia-Pacific Artificial Intelligence Academy. He has been named an “AI 2000 Most Influential Scholar” by AMiner in 2024.
Abstract: As edge computing matures and becomes essential to advanced networks (e.g., 5G and 6G), general computing platforms, and a growing range of applications, the research community and industries have recently moved to the next frontier – edge artificial intelligence (AI). At the same time, a data-driven world is emerging, where networks, systems, and things function and improve themselves automatically based on dynamically available data. Edge AI is expected to be a cornerstone for this new paradigm. This talk will examine, and illustrate with examples, the evolution from edge computing toward edge AI, the potential roles of edge AI in 6G systems, and selected challenges.
Title :
Dr. Edward Griffor, National Institute of Standards and Technology (NIST), USA
Bio: Dr. Edward Griffor is the Associate Director for Cyber Physical Systems at the National Institute of Standards and Technology (NIST). Prior to joining NIST, Griffor served as Walter P. Chrysler Technical Fellow, Chair of the Chrysler Technology Council and Chair of The MIT Alliance. He was named NSF/NATO Postdoctoral Fellow in Science and Engineering in 1980. Dr. Griffor holds a Ph.D. in Mathematics from MIT and Habilitation in Mathematics and Engineering from the University of Oslo. Dr. Griffor is adjunct to the Center for Molecular Medicine and Genetics at the Wayne State University School of Medicine, to the Computing Laboratory at McMaster University, and to the Institute for Assured Autonomy at Johns Hopkins University.
In the automotive industry Dr. Griffor led the development of automated driving systems. His books include the Handbook of System Safety and Security, the Handbook of Computability, and the Mathematical Theory of Domains. He has published extensively in professional journals and has given invited presentations to the American Mathematical Society, North American Software Certification Consortium, SAE International, the Federal Reserve Bank and other US government agencies.
Dr. Griffor’s current research combines methods from mathematics, computing foundations and biomedical science to the assurance of CPS and IoT, including the safety and security of autonomous systems. At NIST, Griffor leads research in Automated Driving Systems (ADS), AI Trust Measurement and Autonomous Systems.