Invited Speakers and Tutorial
Runtime-optimized analytics (slides)
Anastasia Ailamaki – EPFL and RAW Labs SA, Switzerland
Abstract: The ever-increasing demand for diverse real-time analysis on exponentially growing data has brought a series of new system design challenges: First, we can no longer afford to pre-load the data in a database in order to support interactive analytics. Second, with the semiconductor advancement predicted by the end of Dennard scaling, hardware in servers becomes increasingly heterogeneous. Third, the need for throughput is increased as a function of the number of concurrent queries issued by applications and users, but current work sharing techniques do not scale. Fourth, data pipelines are made of heterogeneous tools, each optimized for each processing step, but cross-tool communication introduces high overheads. Finally, we need real-time processing over fresh data (aka Hybrid Transactional Analytical Processing or HTAP), but interference between heterogeneous workloads results in suboptimal performance. The common theme is increasing heterogeneity which is impossible to address efficiently with system design decision made ahead of time, as at design time we know too little too early. Runtime decisions about both mechanisms and heuristics, on the other hand, always lead to efficient processing because optimal processing depends on the use case properties (dat, workload, hardware, concurrency). I will discuss novel just-in-time (JIT) systems which make and actuate decisions at runtime, and explain how the individual JIT solutions synthesise a real-time intelligence paradigm that helps resolve most system perfornance challenges.
Short bio: Anastasia Ailamaki is a Professor of Computer and Communication Sciences at the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland, as well as the co-founder and Chair of the Board of Directors of RAW Labs SA, a Swiss company developing systems to analyze heterogeneous big data from multiple sources efficiently. She earned a Ph.D. in Computer Science from the University of Wisconsin-Madison in 2000. She has received the 2019 ACM SIGMOD Edgar F. Codd Innovations Award and the 2020 VLDB Women in Database Research Award. She is also the recipient of an ERC Consolidator Award (2013), the Finmeccanica endowed chair from the Computer Science Department at Carnegie Mellon (2007), a European Young Investigator Award from the European Science Foundation (2007), an Alfred P. Sloan Research Fellowship (2005), an NSF CAREER award (2002), and ten best-paper awards in international scientific conferences. She has received the 2018 Nemitsas Prize in Computer Science by the President of Cyprus and the 2021 ARGO Innovation Award by the President of the Hellenic Republic. She is an ACM fellow, an IEEE fellow, a member of the Academia Europaea, and an elected member of the Swiss, the Belgian, the Greek, and the Cypriot National Research Councils.
From Database Systems to Global Platforms: Cyberspace and the new Rules of Geopolitics
Stéphane Grumbach – Inria, France
Abstract: Database systems have been designed to optimize legacy organizations, such as administrations or banks. They contributed to a considerable improvement of both the efficiency and the reliability of traditional functions of society. The progressive densification of a network infrastructure, which connects everything continuously thanks to standard protocols to a global system, triggered a radical change in the cybernetics of societies. The database community adapted to a new paradigm, dealing with poorly structured data from innumerable sectors, instead of forcing data into its rigorous models. The digital was on the verge of freeing itself from the constraints of the old world. New actors emerged, platforms, which are in control of the mediation over increasingly many two-sided markets, condemning many actors to obsolescence, while changing the norms and forcing the laws. Beyond people and institutions, platforms are also changing the geopolitical landscape at a time where the challenge is not only the positions of nations in a conflictual game, but the collective adaptation to a fundamentally new global scheme: stay in a safe operating space for humanity.
Short bio: Stéphane Grumbach, senior scientist at Inria, the French National Institute for Research in Digital Science and Technology, is a specialist of data systems. He has worked on theoretical issues in informatics regarding the processing of complex data types, such as spatial, statistical, as well as biological, and has designed the first compression algorithm, Biocompress, for DNA sequences. His interests have evolved to more global questions related to the impact of digital systems on society, such as the geopolitical implications of the digital, which triggers new imbalances and asymmetries between nations, the contrasting visions promoted in different regions of the world, such as North America, East Asia, and Europe, the emergence of a control society, while human societies are facing the challenges of a more constrained global environment, and more generally the contemporaneity of the anthropocene and the digital revolution. He joined IXXI, the Complex Systems Institute at ENS Lyon, in 2014, is affiliated with the GEODE Project on the Geopolitics of the Datasphere and works in collaboration with the Research Institute on Humanity and Nature, RIHN in Kyoto. He teaches Digital Economy in SciencesPo Paris. He has been strongly involved in international relations, has spent eight years in China, first as science counselor in the French Embassy, and then in the Chinese Academy of Sciences, where he headed the Sino-European IT Lab, LIAMA.
A Pragmatic Approach to Neural Information Retrieval
Franco Maria Nardini, Salvatore Trani, ISTI-CNR, Italy
This tutorial provides a gentle introduction to Neural Information Retrieval (NIR). In the last few years, neural techniques have been fruitfully applied to both Natural Language Processing and Information Retrieval (IR). We will review the recent approaches applying neural networks to the IR ad-hoc task, i.e., ranking documents given a textual query. The tutorial will also provide some practical hands-on sessions where attendees will learn how to experiment and apply the techniques reviewed to public datasets.
Short bio: Franco Maria Nardini is a senior researcher with the National Research Council of Italy. His research interests focus on web information retrieval and machine/deep learning. He authored more than 70 papers in peer-reviewed international journals and conferences. He received the Best Paper Award at ACM SIGIR 2015 and the Best Demo Paper Award at ECIR 2014. For more information: http://hpc.isti.cnr.it/~nardini
Short bio: Salvatore Trani is a researcher with the National Research Council of Italy. He received his PhD in Computer Science from the University of Pisa in 2017. His main research interests range from Information Retrieval to Web Mining and Machine Learning. He authored more than 15 papers on these topics, published in peer reviewed international journals and conferences. For more information: https://www.isti.cnr.it/en/about/people-detail/366/Salvatore_Trani