Formal Methods for Event Processing

Bios: Alexander Artikis is a research associate in NCSR Demokritos (Athens, Greece). He holds a PhD from Imperial College London on norm-governed multi-agent systems, while his research interests lie in the areas of artificial intelligence and distributed systems. Alexander has been working on several international projects on event processing; currently, he is the technical director of the FP7 SPEEDD project that develops a Big Data system for proactive event-driven decision-making. Alexander has also developed a highly scalable, logic-based, open-source event processing system.

Georgios Paliouras is a senior researcher in NCSR Demokritos (Athens, Greece). He holds a PhD from Manchester University on machine learning for event recognition. He has performed basic and applied research in machine learning for the last 17 years. He is involved in many European and national research projects and has the role of scientific coordinator in some of them, including the FP7 SPEEDD project. He has given a number of invited talks and tutorials at various institutions and conferences, such as ECML/PKDD, DEBS and IJCAI.
Abstract: Today's organisations require techniques for automated transformation of the large data volumes they collect into operational knowledge. This requirement may be addressed by employing event processing systems that detect activities/events of special significance within an organisation, given streams of `low-level' information that are very difficult to be utilised by humans. Numerous event processing approaches have been proposed in the literature. In this tutorial, we will review formal methods for event processing and discuss the open research issues of this field. We will present temporal reasoning systems, systems that explicitly deal with uncertainty, and machine learning techniques automating the construction and refinement of event structures. To illustrate the reviewed approaches we will use real-world case studies, including event processing for city transport and traffic management.


An In-Depth Look at Modern Database Systems

Bios: Dr. C. Mohan has been an IBM researcher for 32 years in the information management area, impacting numerous IBM and non-IBM products, the research community and standards, especially with his invention of the ARIES family of locking and recovery algorithms, and the Presumed Abort commit protocol. This IBM, ACM and IEEE Fellow has also served as the IBM India Chief Scientist. In addition to receiving the ACM SIGMOD Innovation Award, the VLDB 10 Year Best Paper Award and numerous IBM awards, he has been elected to the US and Indian National Academies of Engineering, and has been named an IBM Master Inventor. This distinguished alumnus of IIT Madras received his PhD at the University of Texas at Austin. He is an inventor of 40 patents. He serves on the IBM Software Group Architecture Board’s Council. More information can be found in his home page at
Abstract: This tutorial is targeted at a broad set of database systems and applications people. It is intended to let the attendees better appreciate what is really behind the covers of many of the modern database systems (e.g., NoSQL and NewSQL systems), going beyond the hype associated with these open source, commercial and research systems. The capabilities and limitations of such systems will be addressed. Modern extensions to decades old relational DBMSs will also be described. Some application case studies will also be presented.


Managing Personal Data with Strong Privacy Guarantees

Bios: Nicolas Anciaux is a researcher at INRIA Paris-Rocquencourt, France. He received his Ph.D. from University of Versailles in 2004 and was in 2005 and 2006 a researcher at University of Twente, Netherlands. His main areas of interest are core database systems, embedded databases, database security and privacy.


Benjamin Nguyen is Associate Professor at University of Versailles St-Quentin (UVSQ), member of the CNRS PRiSM Lab and INRIA Secured and Mobile Information Systems (SMIS) team. He received his Ph.D. from University of Paris-XI in 2003, joined UVSQ in 2004 and INRIA-SMIS in 2010. His current research topics revolve around privacy protection in data centric applications, personal data over-exposure and anonymization.


Iulian Sandu Popa is Assistant Professor in Computer Science at the University of Versailles Saint-Quentin (UVSQ) and member of INRIA-SMIS since 2012. He received his Ph.D. in Computer Science from UVSQ in 2009. His main research interests are embedded database management systems, spatiotemporal databases, and mobile data management, with a particular interest in topics revolving around privacy and personal data management.
Abstract: Managing personal data with strong privacy guarantees has become an important topic in an age where your glasses record and share everything you see, your wallet records and shares your financial transactions, and your set-top box records and shares your energy consumption. More and more alternatives are proposed based on user centric and decentralized solutions, capitalizing on the use of trusted personal devices controlling the data at the edges of the Internet. In this tutorial, we review existing solutions and present a functional architecture encompassing such alternatives. We then expose the underlying techniques proposed recently and the open issues dealing with embedded data management in secure client devices and global query processing within a user centric architecture. We then conclude by presenting implementations of this approach, as the prefiguration of what can be perceived as the holy grail of personal data management.