Publications de Thomas Heinis | EPFL Graph Search

Efficient Bundled Spatial Range Queries

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

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, Thomas Heinis, Mirjana Pavlovic, Darius Sidlauskas

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, Farhan Tauheed, Thomas Heinis, 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, Farhan Tauheed, Thomas Heinis, 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, Thomas Heinis, Mirjana Pavlovic, Eleni Tzirita Zacharatou, Darius Sidlauskas

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, Farhan Tauheed, Thomas Heinis

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, Farhan Tauheed, Thomas Heinis, 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

Nenad Buncic, Jean-Vincent Le Bé, Selim Arsever, Henry Markram, Gilad Silberberg, Sébastien Lasserre, Vincent Delattre, Raphael Dumusc, Rodrigo de Campos Perin, Imad Riachi, Thomas Berger, Felix Schürmann, James Gonzalo King, Rajnish Ranjan, Srikanth Ramaswamy, Michael Lee Hines, Sean Lewis Hill, Juan Bautista Hernando Vieites, Georges Khazen, Shruti Muralidhar, Anastasia Ailamaki, Eilif Benjamin Muller, Farhan Tauheed, Jean Pierre Ghobril, Julie Meystre, Daniel Keller, Idan Segev, Michael Reimann, Thomas Heinis, John Richard Walker, Martin Telefont, Yun Wang, Ying Shi, Joseph William Graham, Marwan Muhammad Ahmed Abdellah, Julian Charles Shillcock, Jean-Denis Georges Emile Courcol, Ahmet Bilgili, Werner Alfons Hilda Van Geit, Athanassia Chalimourda, , , , , , , , , , , , , , , , , , , , , , , , , , , ,

Configuring Spatial Grids for Efficient Main Memory Joins

Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis

The performance of spatial joins is becoming increasingly important in many applications, particularly in the scientific domain. Several approaches have been proposed for joining spatial datasets on disk and few in main memory. Recent results show that in ...

Springer-Verlag Berlin2015

Just-In-Time Data Virtualization: Lightweight Data Management with ViDa

Anastasia Ailamaki, Ioannis Alagiannis, Thomas Heinis, Miguel Sérgio De Oliveira Branco, Manolis Karpathiotakis

As the size of data and its heterogeneity increase, traditional database system architecture becomes an obstacle to data analysis. Integrating and ingesting (loading) data into databases is quickly becoming a bottleneck in face of massive data as well as i ...

2015

OCTOPUS: Efficient Query Execution on Dynamic Mesh Datasets

Henry Markram, Felix Schürmann, Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis

Scientists in many disciplines use spatial mesh models to study physical phenomena. Simulating natural phenomena by changing meshes over time helps to understand and predict future behavior of the phenomena. The higher the precision of the mesh models, the ...

2014

Spatial Data Management Challenges in the Simulation Sciences

Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis

Scientists in many disciplines have progressively been using simulations to better understand the natural systems they study. Faster hardware, as well as increasingly precise instruments, allow the construction and simulation of progressively advanced mod ...

2014

Data-driven Neuroscience: Enabling Breakthroughs Via Innovative Data Management

Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis, Alexandros Stougiannis, Mirjana Pavlovic

Scientists in all disciplines increasingly rely on simulations to develop a better understanding of the subject they are studying. For example the neuroscientists we collaborate with in the Blue Brain project have started to simulate the brain on a superco ...

2013

TOUCH: In-Memory Spatial Join by Hierarchical Data-Oriented Partitioning

Anastasia Ailamaki, Farhan Tauheed, Sadegh Heyrani Nobari, Thomas Heinis

Efficient spatial joins are pivotal for many applications and particularly important for geographical information systems or for the simulation sciences where scientists work with spatial models. Past research has primarily focused on disk-based spatial jo ...

2013

GIPSY: Joining Spatial Datasets with Contrasting Density

Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis, Mirjana Pavlovic

Many scientific and geographical applications rely on the efficient execution of spatial joins. Past research has produced several efficient spatial join approaches and while each of them can join two datasets, the problem of efficiently joining two datase ...

2013

Enabling Scientific Discovery Via Innovative Spatial Data Management

Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis, Mirjana Pavlovic

Researchers in several scientific disciplines are struggling to cope with the masses of data resulting from either increasingly precise instruments or from simulation runs on ever more powerful supercomputers. Efficiently managing this deluge of data has b ...

2013

Computational Neuroscience Breakthroughs Through Innovative Data Management

Anastasia Ailamaki, Farhan Tauheed, Sadegh Heyrani Nobari, Thomas Heinis, Laurynas Biveinis

Simulations have become key in many scientific disciplines to better understand natural phenomena. Neuroscientists, for example, build and simulate increasingly fine grained models (including subcellular details, e.g., neurotransmitter) of the neocortex to ...

2013

Accelerating Spatial Range Queries

Anastasia Ailamaki, Farhan Tauheed, Thomas Heinis, Alexandros Stougiannis

It is increasingly common for domain scientists to use computational tools to build and simulate spatial models of the phenomena they are studying. The spatial models they build are more and more detailed as well as dense and are consequently difficult to ...

2013