Darius Sidlauskas

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DIAS
Postal addressEPFL IC IINFCOM DIAS
BC 222 (Bâtiment BC)
Station 14
CH-1015 Lausanne
Switzerland
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DIAS
DIAS
 
SSC-ENS
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I am postdoc in the Data-Intensive Applications and Systems (DIAS) laboratory at EPFL, working on scientific data management with the Human Brain Project.

My research interests cover data-intensive systems and their practical applications on modern hardware focusing on scientific data management, spatial, temporal, and spatio-temporal indexing, query processing, concurrency control, parallel computation, architecture-sensitive database design.

My take on what every programmer should know about in-memory processing: "Spatial Joins in Main Memory: Implementation Matters!" (only 4-pages!)

Publications (DBLP, Google Scholar)


D. Sidlauskas, S. Chester, E. T. Zacharatou, A. Ailamaki: "Improving Spatial Data Processing by Clipping Minimum Bounding Boxes." In ICDE, 2018.

M. Pavlovic, D. Sidlauskas, T. Heinis, A. Ailamaki: "QUASII: QUery-Aware Spatial Incremental Index." In EDBT, pp. 325–336, 2018.

K. S. Bøgh, S. Chester, D. Sidlauskas, I. Assent: "Template Skycube Algorithms for Heterogeneous Parallelism on Multicore and GPU Architectures." In SIGMOD, pp. 447–462, 2017.

M. Pavlovic, E. T. Zacharatou, D. Sidlauskas, T. Heinis, A. Ailamaki: "Space odyssey: efficient exploration of scientific data." In ExploreDB, pp. 12–18, 2016.

S. Chester, D. Sidlauskas, I. Assent, K. S. Bøgh: "Scalable Parallelization of Skyline Computation for Multi-core Processors." In ICDE, pp. 1083–1094, 2015. [poster] [source code]

K. S. Bøgh, S. Chester, D. Sidlauskas, I. Assent: "Hashcube: A Data Structure for Space- and Query-Efficient Skycube Compression." In CIKM, pp. 1767–1770, 2014. [source code]

D. Sidlauskas and C. S. Jensen: "Spatial Joins in Main Memory: Implementation Matters!" In PVLDB, 2014.

A. Skovsgaard, D. Sidlauskas,C. S. Jensen: "A Clustering Approach to the Discovery of Points of Interest from Geo-Tagged Microblog Posts." In MDM, 2014.

D. Sidlauskas, S. Saltenis, C. S. Jensen: "Processing of extreme moving-object update and query workloads in main memory." In VLDB J., 2014.

A. Skovsgaard, D. Sidlauskas, C. S. Jensen: "Scalable Top-k Spatio-Temporal Term Querying." In ICDE, 2014.

D. Sidlauskas, C. S. Jensen, S. Saltenis: "A Comparison of the Use of Virtual Versus Physical Snapshots for Supporting Update-Intensive Workloads." In DaMoN, 2012.

D. Sidlauskas, S. Saltenis, C. S. Jensen: "Parallel Main-Memory Indexing for Moving-Object Query and Update Workloads." In SIGMOD, 2012.

D. Sidlauskas, K. A. Ross, S. Saltenis, C. S. Jensen: "Thread-Level Parallel Indexing of Update Intensive Moving-Object Workloads."
In SSTD, 2011.

D. Sidlauskas, S. Saltenis, C. W. Christiansen, J. M. Johansen, D. Saulys: "Trees or grids? Indexing moving objects in main memory." In GIS, 2009.

S. Axelsson, D. Baca, R. Feldt, D. Sidlauskas, D. Kacan: "Detecting Defects with an Interactive Code Review Tool Based on Visualisation and Machine Learning." In SEKE, 2009.

Darius Sidlauskas