Natalia Cantavella Franch
Zurich
Summary
Highly structured, problem-solving professional with 5 years experience in deep learning in neuroimaging. Biomedical engineering and neuroscience background specialized in neuroimaging and brain diseases. Exceptional cross-cultural communication & presentation skills.
Overview
6
6
years of professional experience
Work History
PhD Researcher
Universitätsspital Zürich (USZ)
Zürich
09.2024 - Current
• Developing deep learning-based models to enhance brain tumor detection and follow-up care through neuroimaging techniques.
• Conducting patient scans and collecting data to support research on improving diagnostic precision and treatment planning.
Senior Software Developer
GatetoBrain
05.2024 - 08.2024
- Developing deep learning-based software for neurodegenerative disease classification using MRI images in order to find new biomarkers
Software Developer
Siena Imaging
03.2021 - 04.2024
- Developed a Python-based infrastructure that, given a set of quantitative MR-extracted imaging features, is able to automatically identify the best machine learning technique to solve a specific classification or regression tasks
- Contributed to the development of a new python library to automatically perform hyperparameters optimization in deep learning-based classification tasks
Internship Research Student
Amsterdam UMC
10.2020 - 02.2021
- Contributed to develop a CNN based deep learning algorithm to segment the thalamus, putamen and caudate structures in Multiple Sclerosis patients
Researcher
University Autonomous of Barcelona
10.2019 - 09.2020
- Researcher at the Department of psychiatry and legal medicine
- Thesis based on the comparative analysis of different video tracking softwares available at INc-UAB (Institute of Neuroscience) in order to analyze the Morris Water Maze test from 3xTg-AD (Alzheimer's disease mice model)
Research Student
Quibim
10.2018 - 07.2019
- Developed a new analysis infrastructure to segment hypoxic-ischemic lesions using deep learning in MRI images in patients with Alzheimer's disease at QUIBIM's company
Education
PhD - Clinical Science
Universitätsspital Zürich (USZ)
03.2025
MSc. - Neuroscience
University Autonomous of Barcelona
09.2020
BSc. - Biomedical Engineering
University of Malaga
07.2019
Skills
- Deep learning
- Python
- Neuroimaging
- Medical Imaging
- Machine learning
- Image Processing Techniques
- Bash
- Github
- Statistical Analysis
- Matlab
- Ecient management
- Communicating ability
- Teamwork
- Proactive
- Structured
Congresses
- RRMS group stratification of thalamic atrophy using deep learning approach reflects a clinical disability worsening, N.Cantavella, M.Battaglini, F. Sforazzini, M.L. Stromillo, L. Luchetti, G. Gentile, R. Cortese, N. De Stefano, ECTRIMS Congress, Milano, 2023
- Discriminating MS from MOGAD Using Deep Learning Attention Maps, R. Cortese, F. Sforazzini, N. Cantavella Franch, M. Battaglini, F. Prados, A. Bianchi, et al., ECTRIMS Congress, Milano, 2023
- Long-Term Accumulation of Slowly Expanding Lesions is Associated with Grey Matter Atrophy and Disability Worsening in MS, G. Gentile, F. Cacciante, N. Cantavella Franch, M.L. Stromillo, R. Cortese, M. Leoncini, L. Luchetti, F. Aprile, F. Sforazzini, M. Battaglini, N. De Stefano, ECTRIMS Congress, Milano, 2023
- MS-specific Deep Learning Segmentation of Deep Gray Matter, K. Koopman, I. Brouwer, N. Cantavella, A. de Sitter, F. Barkhof, H. Vrenken, ECTRIMS Congress, Vienna, 2021
- How Artificial Intelligence and Algorithms can Fight Alzheimer's disease and Related Dementias, N.Cantavella, L. Giménez, Alzheimer's Research UK congress, 2020
- IPA/SEPG International Psychogeriatric Association and Sociedad Española de Psicogeriatría, Santiago de Compostela, 2019
- VII Scientific Conferences of the INc-UAB, Sant Feliu de Guixols, 2019
- 12th International Conference on Alzheimer's Disease, Valencia, 2018
- Neuroscience Conference, Sölden, Austria, 2018
Scientific Divulgator
Regularly deliver scientific talks at universities promoting the importance of research and advancements in neuroimaging, biomedical engineering and artificial intelligence.
Timeline
PhD Researcher
Universitätsspital Zürich (USZ)
09.2024 - Current
Senior Software Developer
GatetoBrain
05.2024 - 08.2024
Software Developer
Siena Imaging
03.2021 - 04.2024
Internship Research Student
Amsterdam UMC
10.2020 - 02.2021
Researcher
University Autonomous of Barcelona
10.2019 - 09.2020
Research Student
Quibim
10.2018 - 07.2019
MSc. - Neuroscience
University Autonomous of Barcelona
BSc. - Biomedical Engineering
University of Malaga
PhD - Clinical Science
Universitätsspital Zürich (USZ)
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