Biomedical imaging (MRI) R&D | Data analysis pipelines | ML,
May, 2022 - Present
Self-employed (chartered engineer Italy)
MRI
R&D
dL
Background
About
About
I'm interested in combining modeling and experimental practice with biomedical data. Particularly images (MRI, PET, CT) applying numerical methods to solve biologically interpretable inverse problems: tissues structural characterization with Quantitative Susceptibility Mapping (QSM) and Magnetic Resonance Fingerprint (MRF), neuro-pathological alteration functional connectivity (rs-fMRI) and multi-modal fusion with positron emission tomography (PET). Recent interest include scientific validation of those methodologies as reliable deployed systems for compliance (FDA, EMA) in regulated trials and clinical practice alike.
Work Experience
Work Experience
MRI Scientist | R&D Team lead,
Aug, 2021 - Present
R&D development of MRI simulation tools and analytic solution for sequence optimisation.
MRI
R&D
Image Scientist,
Sep, 2020 - Present
Development of analytic pipelines and scientific validation within regulated frameworks. Operational support coordination on live studies.
MRI
PET
CSV
R&D
Product
GAMP
Associate Image Scientist,
Jan, 2019 - Aug, 20201 year 8 months
Imaging analysis research and development of analytic pipelines for clinical trial in neuroimaging of dementia.
MRI
PET
CSV
R&D
Research Intern,
Jan, 2018 - Jun, 20186 months
Sequence and reconstruction development for high-resolution 3D-MRF at 7T. Brain tissue relaxometry-based segmentation.
MRF
Relaxometry
7T
Modelling
Skills
Skills
- Working software/scripting
Matlab
Bash
Python
Docker
- General software/scripting
R
SPSS
C++
Java
Comsol
Kubernetes
Git / Mercurial
SQL (MS) / NoSQL (MongoDB)
- Imaging modalities experience (MRI)
rs-fMRI
MRF
sMRI
DWI
ASL
SV-MRS
- Imaging modalities experience (PET)
FDG-PET
Ab-PET
Tau-PET
FDG-dynPET
- Imaging related libraries
FSL
ANTs
Freesurfer
IRTK
- Methodology experience
Bayesian deconvolution
Compartmental models
Bloch complete or simplified models (EPG)
Numerical optimisation and resource management
Software validation (GAMP5)
Statistical inference testing
- Machine learning experience
Tensorflow (2+)
PyTorch (1.5+)
CNN-based MRI segmentation
Pathology classification
Image synthesis / enhancement (U-net / cyc-GAN)
Education
Education
Quantitative neuroimaging: MRI, dynPET, PhD, The University of Padova, IT
Oct, 2015 - Sep, 2018
Biomedical Engineering: data modeling and statistical methods, MSc, The University of Padova, IT
Dec, 2012 - Jul, 2015
Biomedical Information Engineering: signal processing, BCs, The University of Trieste, IT
Dec, 2012 - Oct, 2009
DESIGN AND INTERPRETATION OF CLINICAL TRIALS, Specialisation course, John Hopkins University SAIS Online
Sep, 2020 - Sep, 2020
TENSORFLOW IN PRACTICE, Specialisation course, deeplearning.ai
Sep, 2020 - Sep, 2020
DEEP LEARNING, Specialisation course, deeplearning.ai
May, 2020 - May, 2020
POSITRON EMISSION TOMOGRAPHY (PET) METHODOLOGY, Specialisation course, King's College London, UK
Oct, 2019 - Oct, 2019
ICH-GCP, Specialisation course, Whitehall Training
Jan, 2021 - Jan, 2023
Interests
Interests
Gardening
Climbing
Open Source / Open Science