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I am a scientific associate in the Krembil Centre for Neuroinformatics at the Centre for Addiction and Mental Health (CAMH), Canada. My research topics include computer arithmetic, high-performance computing, reproducibility, and neuroimaging. In addition, my work aims to democratize the use of stability analysis of scientific computing codes through automatic tools to improve numerical quality.
Posts
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New paper accepted at UNSURE, MICCAI 2026
I am thrilled to announce that our paper “Uncertain but Useful: Leveraging CNN Training Variability into Data Augmentation“ has been accepted as a poster at the International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (UNSURE), MICCAI 2026.
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Invited lecture at ATPESC 2026: Verificarlo
I gave an invited lecture and hands-on tutorial, “Verificarlo: Debugging and optimising floating-point calculations”, at the Argonne Training Program on Extreme-Scale Computing (ATPESC 2026), in the Track 4b: Mixed Precision Computing session (Thursday, July 30, 2026, Q Center, St. Charles, IL).
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New paper (Scientific Reports 2026)
I am thrilled to announce that the paper titled “The practical impact of numerical variability on structural MRI measures of Parkinson’s disease“ has been accepted for publication in Scientific Reports.
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New preprint (bioRxiv 2026)
I am thrilled to announce the preprint “Untrained Convolutional Neural Networks as Feature Extractors for Structural MRI“ is available on bioRxiv.
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New paper (TMLR 2026)
I am thrilled to announce the paper “Fuzzy PyTorch: Rapid Numerical Variability Evaluation for Deep Learning Models“ has been published in Transactions on Machine Learning Research (2026).
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New preprint (bioRxiv 2026)
I am thrilled to announce the preprint “The practical impact of numerical variability on structural MRI measures of Parkinson’s disease“ is available on bioRxiv.
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New preprint (bioRxiv 2025)
I am thrilled to announce the preprint “Numerical Variability of functional MRI Graph Measures“ is available on bioRxiv.
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New paper (UNSURE 2025)
I am thrilled to announce that the paper titled “Numerical uncertainty in linear registration: An experimental study“ is available.
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New preprint (arXiv 2025)
I am thrilled to announce the preprint “Uncertain but useful: Leveraging cnn variability into data augmentation“ is available on arXiv.
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New paper (Imaging Neuroscience 2025)
I am thrilled to announce that the paper titled “Open-source platforms to investigate analytical flexibility in neuroimaging“ is published in Imaging Neuroscience.
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Floacon: A Web-Based Floating-Point Converter and Explorer
Floacon, a new web-based tool designed to help understand and explore floating-point numbers. This project aims to provide an interactive way to visualize floating-point formats, and to experiment with custom formats.
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New paper accepted (GigaScience 2025)
I am thrilled to announce that the paper titled “An analysis of performance bottlenecks in MRI preprocessing“ has been accepted at GigaScience 25.
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New paper (IEEE TC 2024)
I am thrilled to announce that the paper titled “A numerical variability approach to results stability tests and its application to neuroimaging” has been accepted for publication in IEEE Transactions on Computers (TC) journal.
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Best Paper Award (ACM REP 24)
I am thrilled to announce that the paper titled “The Impact of Hardware Variability on Applications Packaged with Docker and Guix: a Case Study in Neuroimaging“ has been awarded the Best Paper Award at ACM REP 24.
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Significant digits viewer
This post demonstrates how to visualize numerical instability in floating-point computations by simulating instability in Chebyshev polynomials using Monte Carlo Arithmetic with Verificarlo and displaying the results as an animated GIF.