Publications de Thomas Heinis | EPFL Graph Search

Efficient Bundled Spatial Range Queries

Anastasia Ailamaki, Darius Sidlauskas, Thomas Heinis, Eleni Tzirita Zacharatou, Farhan Tauheed

Efficiently querying multiple spatial data sets is a growing challenge for scientists. Astronomers query data sets that contain different types of stars (e.g., dwarfs, giants, stragglers) while neuroscientists query different data sets that model different ...

ASSOC COMPUTING MACHINERY2019

QUASII: QUery-Aware Spatial Incremental Index

Anastasia Ailamaki, Darius Sidlauskas, Thomas Heinis, Mirjana Pavlovic

With large-scale simulations of increasingly detailed models and improvement of data acquisition technologies, massive amounts of data are easily and quickly created and collected. Traditional systems require indexes to be built before analytic queries can ...

2018

BLOCK: Efficient Execution of Spatial Range Queries in Main-Memory

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed, Matthaios Alexandros Olma

The execution of spatial range queries is at the core of many applications, particularly in the simulation sciences but also in many other domains. Although main memory in desktop and supercomputers alike has grown considerably in recent years, most spatia ...

ACM New York, NY, USA2017

TRANSFORMERS: Robust Spatial Joins on Non-Uniform Data Distributions

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed, Mirjana Pavlovic

Spatial joins are becoming increasingly ubiquitous in many applications, particularly in the scientific domain. While several approaches have been proposed for joining spatial datasets, each of them has a strength for a particular type of density ratio amo ...

IEEE2016

Space Odyssey - Efficient Exploration of Scientific Data

Anastasia Ailamaki, Darius Sidlauskas, Thomas Heinis, Mirjana Pavlovic, Eleni Tzirita Zacharatou

Advances in data acquisition—through more powerful supercomputers for simulation or sensors with better resolution—help scientists tremendously to understand natural phenomena. At the same time, however, it leaves them with a plethora of data and the chall ...

ACM2016

THERMAL-JOIN: A Scalable Spatial Join for Dynamic Workloads

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed

2015

Reconsolidating Data Structures

Anastasia Ailamaki, Thomas Heinis

2015

Towards the Identification of Disease Signatures

Anastasia Ailamaki, Thomas Heinis, Manolis Karpathiotakis

The identification of biological signatures of diseases will enable the development of new biologically grounded classifications of brain diseases, leading to a new systematic understanding of their causes, and new diagnostic tools. In this paper we presen ...

Springer International Publishing2015

RUBIK: Efficient Threshold Queries on Massive Time Series

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed, Eleni Tzirita Zacharatou

An increasing number of applications from finance, meteorology, science and others are producing time series as output. The analysis of the vast amount of time series is key to understand the phenomena studied, particularly in the simulation sciences, wher ...

2015

Reconstruction and Simulation of Neocortical Microcircuitry

Anastasia Ailamaki, Henry Markram, Sean Lewis Hill, Eilif Benjamin Muller, Rodrigo de Campos Perin, Lida Kanari, Srikanth Ramaswamy, Vincent Delattre, Michael Reimann, Ying Shi

We present a first-draft digital reconstruction of the microcircuitry of somatosensory cortex of juvenile rat. The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse ex ...

Elsevier2015