Publications

Pre-prints

• Hierarchical storage management in user space for neuroimaging applications

  Valérie Hayot-Sasson, Tristan Glatard
  

• Scaling up ridge regression for brain encoding in a massive individual fMRI dataset

  Sana Ahmadi, Pierre Bellec, Tristan Glatard
  

• Predicting Parkinson's disease trajectory using clinical and functional MRI features: a reproduction and replication study

  Elodie Germani, Nikhil Baghwat, Mathieu Dugré, Rémi Gau, Albert Montillo, Kevin Nguyen, Andrzej Sokolowski, Madeleine Sharp, Jean-Baptiste Poline, Tristan Glatard
  

• Classification of Anomalies in Telecommunication Network KPI Time Series

  Korantin Bordeau-Aubert, Justin Whatley, Sylvain Nadeau, Tristan Glatard, Brigitte Jaumard
  

• A numerical variability approach to results stability tests and its application to neuroimaging

  Yohan Chatelain, Loïc Tetrel, Christopher J. Markiewicz, Mathias Goncalves, Gregory Kiar, Oscar Esteban, Pierre Bellec, Tristan Glatard
  

• Predicting Parkinson's disease progression using MRI-based white matter radiomic biomarker and machine learning: a reproducibility and replicability study

  Mohanad Arafe, Nikhil Parag Bhagwat, Yohan Chatelain, Mathieu Dugré, Andrzej Sokolowski, Michelle Wang, Yiming Xiao, Madeleine Sharp, Jean-Baptiste Poline, Tristan Glatard
  

• Sea: A lightweight data-placement library for Big Data scientific computing

  Valérie Hayot-Sasson, Mathieu Dugré, Tristan Glatard
  

• A Conceptual Marketplace Model for IoT Generated Personal Data

  Victor Molina, Marta Kersten-Oertel, Tristan Glatard
  

Published papers

(including contributions from lab members as co-authors)

• The Impact of Hardware Variability on Applications Packaged with Docker and Guix: a Case Study in Neuroimaging

  Gaël Vila, Emmanuel Medernach, Inés Gonzalez Pepe, Axel Bonnet, Yohan Chatelain, Michaël Sdika, Tristan Glatard, Sorina Camarasu-Pop
  2024 ACM Conference on Reproducibility and Replicability, 2024
  

• Longitudinal brain structure changes in Parkinson's disease: a replication study

  Andrzej Sokołowski, Nikhil Bhagwat, Yohan Chatelain, Mathieu Dugré, Alexandru Hanganu, Oury Monchi, Brent McPherson, Michelle Wang, Jean-Baptiste Poline, Madeleine Sharp, Tristan Glatard
  PLOS ONE, 2024
  

• Numerical Stability of DeepGOPlus Inference

  Inés Gonzalez Pepe, Yohan Chatelain, Gregory Kiar, Tristan Glatard
  To appear in PLOS ONE, 2024
  

• Numerical Uncertainty of Convolutional Neural Networks Inference for Structural Brain MRI Analysis

  Inés Gonzalez Pepe, Vinuyan Sivakolunthu, Hae Lang Park, Yohan Chatelain, Tristan Glatard
  2023 MICCAI workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (UNSURE 2023)
  

• Mondrian Forest for Data Stream Classification Under Memory Constraints

  Martin Khannouz, Tristan Glatard
  Data Mining and Knowledge Discovery (to appear, 2023)
  

• Reproducibility of Tumor Segmentation Outcomes with a Deep Learning Model

  Morgane des Ligneris, Axel Bonnet, Yohan Chatelain, Tristan Glatard, Micha ̈el Sdika, Gaël Vila, Valentine Wargnier-Dauchelle, Sorina Pop, and Carole Frindel
  2023 International Symposium on Biomedical Imaging


• PyTracer: Automatically profiling numerical instabilities in Python

  Yohan Chatelain, Nigel Yong, Gregory Kiar, Tristan Glatard
  IEEE Transactions on Computers, 2022

• Dynamic Ensemble Size Adjustment for Memory Constrained Mondrian Forest

  Martin Khannouz, Tristan Glatard
  7th Workshop on Real-time Stream Analytics, Stream Mining, CER/CEP & Stream Data Management in Big Data, Osaka, 2022
  

• NeuroCI: Continuous Integration of Neuroimaging Results Across Software Pipelines and Datasets

  Jacob Sanz-Robinson, Arman Jahanpour, Natalie Phillips, Tristan Glatard, Jean-Baptiste Poline
  IEEE eScience 2022
  

• A Scalable Multi-factor Fault Analysis Framework for Information Systems

  H.H. Phan-Vu, B. Jaumard, T. Glatard, J. Whatley and S. Nadeau
  2021 IEEE International Conference on Big Data (Big Data), Orlando, FL, USA, 2021, pp. 2621-2630
  

• Reducing numerical precision preserves classification accuracy in Mondrian Forests

  Marc Vicuna, Martin Khannouz, Gregory Kiar, Yohan Chatelain, Tristan Glatard
  6th Workshop on Real-time Stream Analytics, Stream Mining, CER/CEP & Stream Data Management in Big Data, 2021
  

• Can we Estimate Truck Accident Risk from Telemetric Data using Machine Learning?

  Antoine Hébert, Ian Marineau, Gilles Gervais, Tristan Glatard, Brigitte Jaumard
  2021 IEEE International Conference on Big Data, 2021
  

• Data and Tools Integration in the Canadian Open Neuroscience Platform

  Jean-Baptiste Poline, Samir Das, Tristan Glatard, Cécile Madjar, et al.
  to appear in Scientific Data, 2021

• The benefits of prefetching for large-scale cloud-based neuroimaging analysis workflows

  Valerie Hayot-Sasson, Tristan Glatard, Ariel Rokem
  16th Workshop on Workflows in Support of Large-Scale Science, 2021
  

• A Recommender System for Scientific Datasets and Analysis Pipelines

  Mandana Mazaheri, Gregory Kiar, Tristan Glatard
  16th Workshop on Workflows in Support of Large-Scale Science, 2021
  

• Numerical Instabilities in Analytical Pipelines Lead to Large and Meaningful Variability in Brain Networks

  Gregory Kiar, Yohan Chatelain, Pablo de Oliveira Castro, Eric Petit, Ariel Rokem, Gaël Varoquaux, Bratislav Misic, Alan C. Evans, Tristan Glatard
  PLOS ONE, to appear, 2021
  

• Accurate simulation of operating system updates in neuroimaging using Monte-Carlo arithmetic

  Ali Salari, Yohan Chatelain, Gregory Kiar, Tristan Glatard
  2021 MICCAI workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (UNSURE 2021)
  

• Centering inclusivity in the design of online conferences—An OHBM–Open Science perspective

  Elizabeth Levitis, Cassandra D Gould van Praag, Rémi Gau et al.
  GigaScience, 10(8), giab051.
  

• Data Augmentation Through Monte Carlo Arithmetic Leads to More Generalizable Classification in Connectomics

  Gregory Kiar, Yohan Chatelain, Ali Salari, Alan C Evans, Tristan Glatard
  Neurons, Behavior, Data Analysis and Theory, 2021
  

• Brainhack: Developing a culture of open, inclusive, community-driven neuroscience

  Rémi Gau, Stephanie Noble, Katja Heuer, Katherine L Bottenhorn, et al.
  Neuron, 109(11), pp 1769-1775, 2021
  

• Modeling the Linux page cache for accurate simulation of data-intensive applications

  Hoang-Dung Do, Valerie Hayot-Sasson, Rafael Ferreira da Silva, Christopher Steele, Henri Casanova, Tristan Glatard
  to appear in IEEE Cluster 2021
  

• An Analysis of Security Vulnerabilities in Container Images for Scientific Data Analysis

  Bhupinder Kaur, Mathieu Dugré, Aiman Hanna, Tristan Glatard
  GigaScience, Volume 10, Issue 6, June 2021, giab025.
  

• A benchmark of data stream classification for human activity recognition on connected objects

  Martin Khannouz, Tristan Glatard
  Sensors, 2020, 20(22), 6486.
  

• File-based localization of numerical perturbations in data analysis pipelines

  Ali Salari, Gregory Kiar, Lindsay Lewis, Alan C. Evans, Tristan Glatard
  Giga Science, Volume 9, Issue 12, December 2020.
  

• Variability in the analysis of a single neuroimaging dataset by many teams

  Rotem Botvinik-Nezer, Felix Holzmeister, Colin F. Camerer et al.
  Nature, 582, 84-88 (2020).
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• Comparing Perturbation Models for Evaluating Stability of Post-Processing Pipelines in Neuroimaging

  Gregory Kiar, Pablo de Oliveira Castro, Pierre Rioux, Eric Petit, Shawn T. Brown, Alan C. Evans, Tristan Glatard
  International Journal of High-Performance Computing Applications, May 21, 2020, arXiv:1908.10922.
  

• Performance benefits of Intel® Optane™ DC persistent memory for the parallel processing of large neuroimaging data

  Valerie Hayot-Sasson, Shawn T Brown, Tristan Glatard
  IEEE/ACM CCGrid 2020, arXiv:1912.11794.
  

• A Quantitative Comparison of Overlapping and Non-Overlapping Sliding Windows for Human Activity Recognition Using Inertial Sensors

  Akbar Dehghani, Omid Sarbishei, Tristan Glatard, Emad Shihab
  Sensors 2019, 19(22), 5026

• High-Resolution Road Vehicle Collision Prediction for the City of Montreal

  Antoine Hébert, Timothée Guédon, Tristan Glatard, Brigitte Jaumard
  2019 IEEE International Conference on Big Data, arXiv:1905.08770.

• A performance comparison of Dask and Apache Spark for data-intensive neuroimaging pipelines

  Mathieu Dugré, Valérie Hayot-Sasson, Tristan Glatard
  14th Workshop on Workflows in Support of Large-Scale Science - WORKS 2019, in conjunction with Supercomputing'19, arXiv:1907.13030.
  

• OrpailleCC: a Library for Data Stream Analysis on Embedded Systems

  Martin Khannouz, Bo Li, Tristan Glatard
  Journal of Open-Source Software, 2019.
  

• Evaluation of pilot jobs for Apache Spark applications on HPC clusters

  Valerie Hayot-Sasson, Tristan Glatard, IEEE eScience 2019
  

• Performance Evaluation of Big Data Processing Strategies for Neuroimaging

  Valérie Hayot-Sasson, Shawn T Brown, Tristan Glatard
  arXiv:1812.06492, IEEE/ACM CCGrid 2019.
  

• A Serverless Tool for Platform Agnostic Computational Experiment Management

  Gregory Kiar, Shawn T Brown, Tristan Glatard, Alan C Evans
  arXiv:1809.07693, Frontiers in Neuroinformatics, vol 13, 2019.
  

• A multi-dimensional extension of the Lightweight Temporal Compression method

  Bo Li, Omid Sarbishei, Hosein Nourani, Tristan Glatard
  3rd Workshop on Real-time and Stream Analytics in Big Data & Stream Data Management, in conjunction with IEEE Big Data 2018.
  

• Data models for service failure prediction in supply-chain networks

  Monika Sharma, Tristan Glatard, Éric Gélinas, Mariam Tagmouti, Brigitte Jaumard
  2018 IEEE International Conference on Big Data.
  

• Predicting computational reproducibility of data analysis pipelines in large population studies using collaborative filtering

  Soudabeh Barghi, Lalet Scaria, Ali Salari, Tristan Glatard
  2018 IEEE International Conference on Big Data.
  

• Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure

  Olivier Commowick, Audrey Istace, Michaël Kain, Baptiste Laurent, Florent Leray, Mathieu Simon, Roxana Améli, Jean-Christophe Ferré, Thomas Tourdias, Frédéric Cervenansky, Tristan Glatard, Jérémy Beaumont, Senan Doyle, Florence Forbes, Jesse Knight, April Khademi, Amirreza Mahbod, Chunliang Wang, Richard McKinley, Franca Wagner, John Muschelli, Elizabeth Sweeney, Eloy Roura, Xavier Lladó, Michel M. Santos, Wellington P. Santos, Abel G. Silva-Filho, Xavier Tomas-Fernandez, Hélène Urien, Isabelle Bloch, Sergi Valverde, Mariano Cabezas, Francisco Javier Vera-Olmos, Norberto Malpica, Charles Guttmann, Sandra Vukusic, Gilles Edan, Michel Dojat, Martin Styner, Simon K. Warfield, François Cotton, Christian Barillot
  Scientific Reports volume 8, Article number: 13650 (2018).
  

• Evaluation through Realistic Simulations of Data Placement Strategies for Large Heterogeneous Distributed Systems

  Anchen Chai, Sorina Camarasu-Pop, Tristan Glatard, Hugues Benoit-Cattin, and Frédéric Suter
  Sixteenth International Workshop for Parallel Computing on Heterogeneous Platforms (HeteroPar'2018), August 27th, 2018, Turin, Italy
  Best paper from the best Euro-Par 2018 workshop award

• The first MICCAI challenge on PET tumor segmentation

  Mathieu Hatt, Baptiste Laurent, Anouar Ouahabi, Hadi Fayad, Shan Tan, Laquan Li, Wei Lu, Vincent Jaouen, Clovis Tauber, Jakub Czakon, Filip Drapejkowski, Witold Dyrka, Sorina Camarasu-Pop, Frédéric Cervenansky, Pascal Girard, Tristan Glatard, Michael Kain, Yao Yao, Christian Barillot, Assen Kirov, Dimitris Visvikis
  Medical Image Analysis, 44 (2018) 177–195.
  

• Boutiques: a flexible framework to integrate command-line applications in computing platforms

  Tristan Glatard, Gregory Kiar, Tristan Aumentado-Armstrong, Natacha Beck, Pierre Bellec, Rémi Bernard, Axel Bonnet, Shawn T Brown, Sorina Camarasu-Pop, Frédéric Cervenansky, Samir Das, Rafael Ferreira da Silva, Guillaume Flandin, Pascal Girard, Krzysztof J Gorgolewski, Charles R G Guttmann, Valérie Hayot-Sasson, Pierre-Olivier Quirion, Pierre Rioux, Marc-Etienne Rousseau Alan C Evans
  GigaScience, Volume 7, Issue 5, 1 May 2018.
  

• Sequential algorithms to split and merge ultra-high resolution 3D images

  Valérie Hayot-Sasson, Yongping Gao, Yuhong Yan, Tristan Glatard
  2017 IEEE International Conference on Big Data, Boston, MA, 2017, pp. 415-424.
  

• Software architectures to integrate workflow engines in science gateways

  Tristan Glatard, Marc-Etienne Rousseau, Sorina Camarasu-Pop, Reza Adalat, Natacha Beck, Samir Das, Rafael Ferreira da Silva, Najmeh Khalili-Mahani, Vladimir Korkhov, Pierre-Olivier Quirion, Pierre Rioux, Silvia D. Olabarriaga, Pierre Bellec, Alan C. Evans
  Future Generation Computer Systems, Volume 75, October 2017, Pages 239-255.
  

• Modeling Distributed Platforms from Application Traces for Realistic File Transfer Simulation

  Anchen Chai, Mohammad Bazm, Sorina Camarasu-Pop, Tristan Glatard, Hugues Benoit-Cattin, Frédéric Suter
  17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), Madrid, Spain, pp. 54-63., 2017.
  

• Standards for Best Practices in Data Analysis and Sharing in Neuroimaging using MRI

  Thomas E. Nichols, Samir Das, Simon B. Eickhoff, Alan C. Evans, Tristan Glatard, Michael Hanke, Nikolaus Kriegeskorte, Michael P. Milham, Russell A. Poldrack, Jean­-Baptiste Poline, Erika Proal, Bertrand Thirion, David C. Van Essen, Tonya White, B.T. Thomas Yeo
  Nature Neuroscience 20, 299-303, 2017.
  

• Cyberinfrastructure for Open Science at the Montreal Neurological Institute

  S. Das, T. Glatard, C. Rogers, J. Saigle, S. Paiva, L. MacIntyre, M. Safi-Harab, M.-E. Rousseau, J. Stirling, N. Khalili-Mahani, D. MacFarlane, P. Kostopoulos, P. Rioux, C. Madjar, X. Lecours-Boucher, S. Vanamala, R. Adalat, Z. Mohaddes, V. S. Fonov, S. Milot, I.R. Leppert, C., T. M Durcan, T. Campbell, J. Moreau, A. Dagher, D L. Collins, J. Karamchandani, A. Bar-Or, E. A Fon, R. Hoge, S. Baillet, G. Rouleau, A. C. Evans
  Frontiers in Neuroinformatics, 10:53, 2017