Loïc Tetrel
DATA SCIENTIST · MEDICAL IMAGING

France (Auvergne-Rhône-Alpes) / Remote (phone number upon request) | loic.tetrel.pro@proton.me|  ltetrel.github.io/|  ltetrel|  loïc tetrel

With 5+ years of experience building data science projects in medical imaging for both industry andacademia, my main goal is always to deliver high quality work. I define myself as curious and autonomous.

Professional profile
MRI, ultrasound, open source, machine learning, distributed training, statistics, GPU computing, image/volume registration, 3D reconstruction and rendering, tracking, camera optics, computer science.

Education
ÉTS (École de technologie supérieure) Montréal (including McGill courses)

Montréal, CANADA

M. A. SC. IN ELECTRICAL ENGINEERING, GRADUATED WITH HONORS

Sept. 2014 - Aug. 2016

Lyon INSA (National Institute of Applied Sciences of Lyon)

Lyon, FRANCE

M. ENG. IN ELECTRICAL ENGINEERING

Sept. 2012 - Aug. 2016

IUT (University Institutes of Technology) Lyon 1

Lyon, FRANCETECHNICAL DEGREE IN INDUSTRIAL ENGINEERING AND MAINTENANCE, GRADUATED WITH HONORS

Sept. 2010 - Jun. 2012

SkillsLow-level programmingHigh-level programming
Softwares
Operating systems
Languages

Bash, C, C++11 (OpenCV, Ceres, Boost, Eigen), Golang, CUDA, Assembly
Python3 (NumPy, Matplotlib, PyTorch, TensorFlow), MATLAB (statistical and ML toolbox)
SLURM, Git, Docker, Jupyter, FFmpeg, GNU Make, Kubernetes, Openstack, LATEX, Blender, 3D slicer
Ubuntu 18, Windows 10
French (mother tongue), English (professional, TOEIC 925), Polish (fluent)Work Experience
SIMEXP lab, CRIUGM - University of Montreal

Remote / Montréal (QC), CANADADATA SCIENCE ENGINEER*: NEUROIMAGING RESEARCH

Nov. 2018 - May 2022

• Software tools for neuroimaging. https://github.com/SIMEXP
HPC scalable fMRI preprocessing and quality-control on BIDS datasets [3] (fMRIPrep, Datalad, SLURM)
fMRIPrep Long-Term Support and reproducibility testing [1] (Datalad, SLURM)• Machine learning. https://github.com/courtois-neuromod
Graph convolution network package for fMRI data: feature preprocessing, training, evaluation and testing/visualization (Nilearn, PyTorch).
Fast and accurate fMRI registration with quaternions using convolutional neural network [4] (TensorFlow)
Benchmarking distributed training applied to brain-state annotation [5, 6] (Intel collaboration) and SoundNet using HEAR (PyTorch, SLURM)• Research data platforms. https://github.com/neurolibre
NeuroLibre [2] administrator: Compute cluster and backend APIs to build/publish submissions (Openstack, Kubernetes/Binderhub)
Data organization, user documentation and maintenance for SIMEXP (bash)• Upstream contributions (TensorFlow, Nilearn, Binderhub), oral presentations and hackaton trainer (MAIN, OHBM)

Straumann Group, Digital Business Unit

Montréal (QC), CANADACOMPUTER VISION DEVELOPER*: 3D SOLUTIONS FOR DIGITAL DENTISTRY.

Dec. 2016 - Oct. 2018

• 3D reconstruction algorithms
State of the art research on stereoscopy using phase-shift model (C++, Ceres, Eigen)
Optical calibration and distorsion correction (OpenCV, Ceres, NumPy)
Metrology reports and software documentation
Conception of a virtual scanner for software experimentation and hardware validation (Blender)• Conferences attendance (CVPR 2018, Agile Tour 2017), open days for recruiting interns (Concordia, Polytechnique, McGill)

LATIS, ÉTS Montréal

Montréal (QC), CANADARESEARCH ASSISTANT* : GRAPH-BASED ESTIMATION OF PROBE TRAJECTORY FOR SENSORLESS FREEHAND 3D US.

Jan. 2015 - Nov. 2016

• Calibration of optical and electromagnetic probes for freehand 3D US (C++, 3D slicer/PLUS, Make)• Master thesis [7]: Sensorless image reconstruction for ultrasoundImage registration from echographic sequence using speckle-decorrelation (C, Make)
Trajectory estimation by a directed graph with gaussian process uncertainty and Lie Algebra [8] (Matlab, C++, Boost)• Conferences attendance (REPARTI 2016, MICCAI/MLMI 2016)* REFERENCES AVAILABLE UPON REQUEST.

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Thales Group, Thales Air Systems

Limours, FRANCE

INTERN* : FAST INITIALIZATION OF CARTESIAN TRACK USING FM BAND

Feb. 2014 - Aug. 2014

• Track initialization in cartesian coordinates with range measurements, using a custom non-linear filter and statistical methods ( MATLAB)• Validation on aircraft records (MATLAB, C++, Eigen)

Relevant Projects• Computer science blog (Jupyter, HTML) https://ltetrel.github.io/• Co-funder of bitprobe *, bitcoin price forecasting using blockchain features (TensorFlow)• Kodi/Jellyfin media server with custom tool for subtitle synchronization (Bash, FFmpeg, TensorFlow)• Video games tools and bots (Python, Golang)• PCB design of a detection system for an autonomous robot (C, Altium)

McGill, ÉTS Montréal

Montréal (QC), CANADA• Registration of MRI and CT images using Gaussian Process interpolation with uncertainty (Matlab)• GPU implementation of sobel filtering on Nvidia GTX (C, CUDA)• Automatic classification and prediction models for early Parkinson disease from SPECT imaging (Matlab)

2014 - 2016

Volunteer Experience
Big Band ÉTS

Montréal (QC), CANADAGUITARIST AND EVENT COORDINATOR

Sept. 2015 - Aug. 2016

ClubElek (Lyon INSA)

Lyon, FRANCEBEGINNER TEAM MANAGER

Sept. 2012 - Jun. 2013

• Coordinator assistant for InnoRobo Lyon 2013.

AwardsMar, 2016 Grant, Bourse interne ÉTS : merit scholarship for graduate students (3.000 CAD).

Montréal (QC), CANADA

May, 2015 24h de l’innovation: 1st place, Mobile app to teach science for children.

Montréal (QC), CANADA

Aug, 2014 Explora’sup grant, Regional merit scholarship for undergraduate students (2.000 EUR).

Lyon, FRANCE

May, 2013 Eurobot: qualification phase, International robotic contest with autonomous robots.

La Ferté B., FRANCE

Publications
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[4]
[5]
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[8]

Yohan Chatelain, Loïc Tetrel, Christopher J. Markiewicz, Gregory Kiar, Oscar Esteban, et al. “Testing the long-term
reproducibility of fMRIPrep results”. In: 2022. Poster presented at OHBM 2022, Glasgow, Scotland.
Agah Karakuzu, Elizabeth DuPre, Loïc Tetrel, Patrick Bermudez, Mathieu Boudreau, et al. “NeuroLibre : A preprint
server for full-fledged reproducible neuroscience”. 2022. Poster presented at OHBM 2020, Online.
Désirée Lussier, Natasha Clarke, Hao-Ting Wang, Arnaud Boré, Loïc Tetrel, et al. “Standardized preprocessed derivatives for the Comprehensive Assessment of Neurodegeneration and Dementia (COMPASS-ND) Study”. In: Alzheimer’s& Dementia None.None, Supplement (2022). Alzheimer’s Association International Conference 2022, None. Poster
presented at AAIC 2022, San Diego, CA.
Loïc Tetrel and Pierre Bellec. “Fast and accurate EPI spatial normalization using convolutional neural network”. In:2021. Poster presented at OHBM 2021, Online.
Yu Zhang, Loïc Tetrel, Bertrand Thirion, and Pierre Bellec. “Functional annotation of human cognitive states using
deep graph convolution”. In: NeuroImage 231 (2021), p. 117847.
Yu Zhang, Loïc Tetrel, and Pierre Bellec. “Benchmarking 3d-CNN models for brain decoding on CPU servers”. In:2019. Poster presented at MAIN 2019, Montreal, Canada.
Loïc Tetrel. “Estimation de la trajectoire d’une sonde ultrasonore pour l’échographie 3D main-libre sans capteur deposition”. MA thesis. École de technologie supérieure, 2016.
Loïc Tetrel, Hacène Chebrek, and Catherine Laporte. “Learning for Graph-Based Sensorless Freehand 3D Ultrasound”. In: Machine Learning in Medical Imaging. Ed. by Li Wang, Ehsan Adeli, Qian Wang, Yinghuan Shi, and Heung-Il
Suk. Springer. Cham: Springer International Publishing, 2016, pp. 205–212.

Interests
Travels
Hobbies

Europe, USA, Canada, Thailand, Morocco
Video games, IT, politics, reading books (fantasy, science-fiction), playing music (rock, jazz)* REFERENCES AVAILABLE UPON REQUEST.

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