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Claudia Testa

Associate Professor

Department of Physics and Astronomy "Augusto Righi"

Academic discipline: PHYS-06/A Physics for Life Sciences, Environment, and Cultural Heritage

Head of SCUOLA DI SPECIALIZZAZIONE FISICA MEDICA (D.I. 716/2016)

Curriculum vitae

Education

2009: Specialization in Medical Physics: Università di Tor Vergata, Roma.

2004: Post High Degree in Biophysics - XVI ciclo. Medicine and Surgery Faculty, Università “La Sapienza” di Roma.

2000: Master Degree in Physics - Università “La Sapienza” di Roma.

Academic activity

From 2024: Director of the School of Medical Physics, Università di Bologna.

From 2018: Head of the NMR Laboratory of the Department of Physics and Astronomy at the University of Bologna.

From 2019: Associated Professor in Applied Physics at the Department of Physics and Astronomy, Università di Bologna.

Educational activity

From 2012: teaching activities relative to Applied Physics for Bachelor Degree’s courses of the School of Medicine, for the Bachelor’s and Master’s Degree in Physics in Applied Physics of the School of Science at the University of Bologna. Moreover, teaching activities for the School of Medical Physics at the University of Bologna. Tutor of many Master’s and Bachelor’s Degree students in Physics.

Research activity

Work in multidisciplinary teams from physicists to clinicians. Definition of protocols for efficient measurements of biomarkers and experimental acquisitions of Magnetic Resonance data for diagnosis of disorders.

Development of specific protocols for MRS and MRI; development of protocol for Quality Control for the use of new coils and sequences for specific purposes.

Imaging data analysis and statistical approaches for correlations of imaging and clinical data. Definition of pipelines of multimodal analysis of data, and on their quality control. Specifically, fMRI (functional Magnetic Resonance Imaging) tractography based on DWI, EEG-fMRI, QSM (Quantitative Susceptibility Mapping). Development of processing approaches for structural, functional, metabolic data using pattern recognition methods, machine learning methods and graph theory approach. Development of Deep learning approaches for quantitative MRI.

Projects

2024 - AIM_MIA Artificial Intelligence in Medicine

2022 - Horizon-MSCA-2022 NMR-IMPROV

2024- FutureData4EU programme: European Marie Curie COFUND project

2021 - COST project

 

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