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Thomas Heinis

Cette personne a quitté l’EPFL

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Publications associées (23)

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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

Spatial Data Management Challenges in the Simulation Sciences

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed

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

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

Enabling Scientific Discovery Via Innovative Spatial Data Management

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed, 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

Accelerating Spatial Range Queries

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed

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

Reconstruction and Simulation of Neocortical Microcircuitry

Anastasia Ailamaki, Henry Markram, Felix Schürmann, Eilif Benjamin Muller, Sean Lewis Hill, Idan Segev, Srikanth Ramaswamy, Michael Reimann, Daniel Keller, Thomas Heinis, Werner Alfons Hilda Van Geit, Rodrigo de Campos Perin, Marwan Muhammad Ahmed Abdellah, James Gonzalo King, Lida Kanari, Farhan Tauheed, Julian Charles Shillcock, Pramod Shivaji Kumbhar, Gilad Silberberg, Ying Shi, Vincent Delattre, Jean-Denis Georges Emile Courcol, Rajnish Ranjan, Juan Bautista Hernando Vieites, Stefan Eilemann, Michael Emiel Gevaert, Giuseppe Chindemi, Jean-Vincent Le Bé, Julie Meystre, Taylor Howard Newton, Max Christian Nolte, Nicolas Antille, Georges Khazen, Sébastien Lasserre, Jean Pierre Ghobril, Jeffrey Christopher Muller, Aleksandr Ovcharenko, Shruti Muralidhar, Ahmet Bilgili, Daniel Nachbaur

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

Efficient Bundled Spatial Range Queries

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed, 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

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

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed

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, Thomas Heinis, Farhan Tauheed, 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

SCOUT: Prefetching for Latent Structure Following Queries

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

Today's scientists are quickly moving from in vitro to in silico experimentation: they no longer analyze natural phenomena in a petri dish, but instead they build models and simulate them. Managing and analyzing the massive amounts of data involved in simu ...

2012

Configuring Spatial Grids for Efficient Main Memory Joins

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed

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

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

Computational Neuroscience Breakthroughs Through Innovative Data Management

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed

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

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

Challenges and Opportunities in Self-Managing Scientific Databases

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed, Ioannis Alagiannis, Renata Borovica-Gajic, Miguel Sérgio De Oliveira Branco

Advances in observation instruments and abundance of computational power for simulations encourage scientists to gather and produce unprecedented amounts of increasingly complex data. Organizing data automatically to enable efficient and unobstructed acces ...

2011

OCTOPUS: Efficient Query Execution on Dynamic Mesh Datasets

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

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

Accelerating Range Queries For Brain Simulations

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

Neuroscientists increasingly use computational tools to build and simulate models of the brain. The amounts of data involved in these simulations are immense and the importance of their efficient management is primordial. One particular problem in analyzin ...

2012

Data-driven Neuroscience: Enabling Breakthroughs Via Innovative Data Management

Anastasia Ailamaki, Thomas Heinis, Farhan Tauheed, 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

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