- Artur Czumaj, University of Warwick
- Milan Vojnovic, Microsoft Research
- Jingren Zhou, Microsoft
- Cara Freeman, Microsoft Research
- Microsoft Research Ltd
- Centre for Discrete Mathematics and its Applications, University of Warwick
We witness a rapid development of the research and technology for efficient processing of big data. There is a surge of commercial and open source platforms for big data analytics, including platforms for querying of massive datasets, batch processing, real-time analytics, streaming computations, iterative computations, graph data processing, and distributed machine learning. There have been some remarkable achievements on the side of designing scalable and efficient algorithms for processing of massive amounts of data, as well as on the side of architecture of systems and infrastructure. The goal of this workshop is to bring together researchers and system architects to discuss and identify the most important and challenging directions to push forward the area of algorithms and systems for big data. The topics of the workshop include but are not limited to computation and storage platforms, querying of massive datasets, sketches, streaming, scaling up distributed machine learning, iterative computations, and large-scale graph processing.