Events Calendar

CS Colloquium - USC Student Series: George Konstantinidis, Leandro Soriano Marcolino

Speaker: George Konstantinidis, Leandro Soriano Marcolino, USC

Talk Title: Scalable Data Integration under Constraints, Agents Vote for the Environment: Designing Energy-Efficient Architecture

Series: Student Seminar Series

Abstract: Saving energy is a major concern nowadays. Hence, it is fundamental to design and construct buildings that are energy efficient. It is known that the early stage of architectural design has a significant impact on this matter. However, it is very complex to create designs that are optimally energy efficient, and at the same time balance and meet other essential design criteria such as economics, space, and safety. One state of the art approach is to create parametric designs, and use a genetic algorithm to optimize across complexly coupled objectives. In this work we further improve this method, by aggregating the solutions of multiple agents. We evaluate our approach across three design case studies of increasing complexity, and show that a team of agents are able to provide one order of magnitude higher number of 1st ranked solutions in the Pareto frontier. Therefore, our approach provides the designers with a higher number of optimized solutions to choose from, that they can further subjectively evaluate, thus leading to better and highly energy efficient building designs.

We witness an explosion of available data in all areas of human activity, from large scientific experiments, to medical data, to distributed sensors, to social media. Integrating data from disparate sources can lead to novel insights across scientific, industrial, and governmental domains. This integration is achieved by either creating a data warehouse, that is, by copying/transforming the data to a centralized site under a single schema for subsequent analysis (data exchange), or by leaving the data at their original sources and querying the data at analysis time ((virtual) data integration), making use of mappings or views between the source and the global schemas. In this work, we focus in scalable data integration and data exchange under constraints or dependencies (or ontologies). In both these problems we make use of the chase algorithm, a forward-chaining reasoning algorithm and the main tool to reason with dependencies. Our first contribution is to introduce the frugal chase, which produces smaller solutions than the standard chase, still remaining polynomial in data complexity. Our second contribution is to use the frugal chase to scale up virtual data integration, aka query answering using views, under constraints in the language of LAV-weakly-acyclic dependencies, a useful language capturing the W3C Recommendation RDF/S. The latter problem can be reduced to query rewriting using views without constraints by chasing the source mappings using the constraints. We construct a compact graph-based representation of the mappings and the constraints and develop an efficient algorithm to run the frugal chase on this representation. We show experimentally that our approach scales to larger problems, outperfomring the standard chase algorithm by close to two orders of magnitude and improving online data integration time by a factor of 3.

Biography: George Konstantinidis is a Ph.D. Candidate in the Computer Science Department at the University of Southern California (USC) and a Research Assistant at the Information Sciences Institute (ISI) at USC. He studied Computer Science at the University of Crete, Greece, and holds a M.Sc. degree in Computer Science from the University of Crete and the Foundation for Research and TechnologyHellas (FORTH). His research interests lie in the intersection of Databases and Artificial Intelligence, Knowledge Representation, Information and Data Integration and the Semantic Web, and in particular OntologyBased Data Answering, Integration and Evolution. He enjoys combining novel theory and practical implementations. He has been a reviewer for IJCAI and TKDE, and has published papers both in A.I. (e.g., ECAI, KAIS) and in Databases (e.g., SIGMOD, VLDB).

Leandro Soriano Marcolino is a 4th year PhD student at University of Southern California (USC). He is advised by Milind Tambe. Previously he was awarded the Monbukagakusho scholarship and obtained a M.A. in Systems Information Sciences in Future University Hakodate, Japan. His research work performed during his master's studies was a best paper nominee at AAMAS 2011. He has been researching since very early as an undergraduate student at Universidade Federal de Minas Gerais, Brazil, and was able to publish many papers before even entering graduate school. His research is mainly about teamwork and cooperation, and he has published on the topic in a variety of different domains such as swarm robotics, computer Go, and building design. He has published in several prestigious conferences in AI and robotics, such as AAAI, AAMAS, IJCAI, ICRA and IROS.

Host: CS Department

Location: Henry Salvatori Computer Science Center (SAL) - 101

Audiences: Everyone Is Invited

Contact: Assistant to CS chair