brain NAVigation Lab

Gloria Menegaz is Professor of Bioengineering at the Dept. of Engineering for Innovation Medicine, University of Verona (Italy) and head the BraiNAVLab. She holds a PhD in Applied Sciences (EPFL 2000) a MSc in Electronic Engineer (1993) and a post-grade Master's in information technology (1995) (Politecnico di Milano, Italy). From 2000 to 2002 she was first research assistant at the Telecommunications Lab (LCAV) of EPFL, headed by Prof. Martin Vetterli, that she left to join the Computer Science Dept. of the University of Fribourg (Switzerland) as an Assistant Professor. In 2004 she was awarded the Rita Levi Montalcini grant by the Italian Ministry of University and Research (MIUR)(DM 20/03/2003 n. 501) and joined the Dept. of Information Engineering of the University of Siena (Italy) as an Assistant Professor. In 2007 she joined the Dept. of Computer Science of the University of Verona (Italy) as an Associate Professor and became full Professor in 2017. Prof. Menegaz is a Senior Member of the IEEE, the Signal Processing Society (SPS), Liason representative of the IEEE-SPS and member of the steering committee of the IEEE Transactions on Medical Imaging (TMI), member of the Challenges and Data Collection Technical Committee of the SPS, Chair of the Technical Committee for Challenges and Data Collections of the IEEE Bioimaging and Signal Processing (BISP) Committee of the IEEE (Co-chair Prof. Vince Calhoun, Georgia Institute of Technology), and member of the IEEE Woman in Engineering. She is also a member of Member of the Medical Image Computing and Computer Assisted Intervention Society (MICCAI) Special Interest Group on Biomedical Image Analysis Challenges (SIG-BIAC), of the Ad Hoc Group (AHG) on Digital Media Storage using DNA (JPEG-DNA) and Observer for the DICOM WG-32 (Neurophysiology data). She is Associate Editor of the IEEE Transactions on Medical Imaging and Scientific Reports (Nature), has served as Guest Editor of the IEEE-SPM and for other venues. She has been Vice-Chair for the FET-REA and the MSCA-IF for many years and Independent Expert for many international Institutions including European Science Foundation (ESF), SKF, Sweden, among others. She authored more than 130 publications in international journals and conference proceedings and has been chair, area chair and technical committee member of many international conferences, especially of the IEEE.
Curriculum Vitae available here

Silvia F. Storti is Associate Professor in Bioengineering at the Dept. of Computer Science, University of Verona, Italy. She received the Master Degree in Electronic Engineering from the University of Padova (2007) and the Ph.D. Degree in Neuroscience from the University of Verona, Italy (2012). From 2008 to 2014 she worked as Research Associate/PhD student and then as Post-doc Researcher in the Clinical Neurophysiology and Functional Neuroimaging Unit leaded by Prof. Paolo Manganotti at the Dept. of Neurological and Movement Sciences, University of Verona. In the 2014 she moved at the Dept. of Computer Science, University of Verona and from 2014 to 2018 she was Post-doc Researcher in the Neuroimaging Lab headed by Prof. Gloria Menegaz. From Nov 2018 to Oct 2021 she was Assistant Professor (tenure-track position, senior researcher RTDb) and since Nov 2021 she is Associate Professor in Bioengineering at the same Department. Silvia Storti’s main research interests are in the area of Neuroengineering, and are focused on multimodal functional neuroimaging integration, brain functional connectivity inference, network analysis, and brain computer interfaces (BCIs). She is co-author of 57 publications on International Peer-Reviewed Journals on bioengineering and neurophysiological topics (13 as first author, 12 as second author, 4 as last author, all peer-reviewed), 16 short-papers (proceedings) on international and 2 on national conferences, 1 national book chapter and 50 international and 18 national conference abstracts. Silvia F. Storti has H-Index 20/19 (Scopus/WOS) and her papers count 1039/921 citations (Scopus/WOS).
Curriculum Vitae available here

Ilaria Boscolo Galazzo is an Assistant Professor (RTDB) in Bioengineering at the Dept. of Computer Science, University of Verona. She graduated cum laude in Biomedical Engineering at the University of Padova (2010) and received the Ph.D. degree in Neuroscience from the University of Verona (May 2014). She took a position as Research Associate at the Institute of Nuclear Medicine, UCL, London from 2014 to 2016 and then at the Dept. of Computer Science, University of Verona from 2016 to July 2020 as Post-Doc in the BraiNAVLab headed by Prof. Gloria Menegaz. Since August 2020 she is RTDa in Bioengineering at the same Department. Her main research activities include imaging genetics, statistical/machine learning for neuroimaging data and multimodal integration, Arterial Spin Labeling and functional MRI modeling, and brain connectivity from non-invasive recordings. She is Associate Editor for IEEE Access and Review Editor for Frontiers in Neuroinformatics.
Curriculum Vitae available here

Lorenza Brusini is Temporary Assistant Professor (RTDa) in Bioengineering at the Dept. of Computer Science, University of Verona, Italy. She received the Master Degree in Bioinformatics and Medical Biotechnologies from the University of Verona (2014) and the Ph.D. Degree in Computer Science with mention Doctor Europaeus from the University of Verona, Italy (2017). From 2017 to 2021 she worked as Post-doc Researcher in the BraiNAVLab headed by Prof. Gloria Menegaz, and she is still working in the same lab as junior researcher. Her main research interests are in the area of Neuroengineering and are focused on brain microstructure and structural connectivity characterization derived from diffusion magnetic resonance imaging signal modelling. She is also interested in integrating such data with other types like images from different magnetic resonance modalities, genetic information, etc. For this purpose, she is developing artificial intelligence models and interpretability methods to make them explainable and thus more reliable to use for many applications, especially for clinical ones. Artificial intelligence models and connected explainable methods are revealing potential also in her recent research interest in brain computer interface where she can contribute mainly to the exploitation of such a models for real time applications and validation experiments.
https://www.di.univr.it/?ent=persona&id=21304

Coming soon

Walter received his BSc in Multimedia Information Technology and his MSc in Visual Computing and Pattern Recognition both at University of Verona, respectively in 2012 and 2014. He then won two research grants respectively focused on Information Retrieval and Data Mining techniques. He is now working as Technical EMEA lead for AI at Intel Corporation, while pursuing his Ph.D. In federated learning and distributed systems. He mainly focuses on applied research at different level: from testing novel scientific approaches, to tackle production and deployment challenges. The main research area concern the Medical environment, but eventually includes collaborations on many other segments.

Ilaria Siviero received her B.S. in biomedical engineering and M.S. in bioengineeeing from the University of Padova in 2021. She is currently a PhD student in Computer Science at the University of Verona (Programma Operativo Nazionale “Ricerca e Innovazione” 2014-2020 - PON). Her Ph.D. project title is "AI4Health: empowering Telemedicing through explainable AI methods for personalized diagnosis, monitoring and treatment" and the main research interests are: i) biological signal processing; ii) brain computer interface; iii) eXplainable Artificial Intelligence clinical applications.

Ettore Cinquetti received his Bachelor's degree in Computer Science, and his Master's degree in Computer Science and Engineering, from University of Verona, respectively in November 2019 and March 2022. His M.S. thesis is titled "Multi-Channel Variational Autoencoder for Data Integration in Imaging Genetics". Still bound to University of Verona, he's now a research collaborator, working with the BraiNAVlab group. He's currently focused on the following topics: deep learning and neural networks, multivariate signal analysis and processing, BCI.

Giorgio Dolci received his B.Sc. in Bioinformatics and M.Sc. in Medical Bioinformatics cum-laude from the University of Verona in 2023. He is currently a PhD student in Computer Science at the University of Verona. He took a position as external researcher at the Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA, from March 2022 to July 2022, and from May 2023 to August 2023, under the supervision of prof. Vince D. Calhoun. Additionally, he made two different internships at the BraiNavigationLab under the supervision of prof. Gloria Menegaz. His research interests include: 1) Magnetic Resonance Imaging processing and analysis; 2) Genetics data analysis; 3) Artificial Intelligence models applied to biomedical and clinical domains, with more focus to deep learning; 4) Integration and fusion of heterogenous data through deep multimodal learning architectures; 5) Application and validation of eXplainable Artificial Intelligence methods in clinical and biomedical domains.

Edoardo Paolini is a Ph.D student at the Dept. of Computer Science, University of Verona, Italy. He received the Bachelor Degree in Computer Science at the University of Verona (2020) and the Master Degree in Quantitative and Computational Biology at the University of Trento (2023). For his Bachelor’s thesis, he investigated the reliability of several functional connectivity (FC) and graph metrics applied to resting-state functional magnetic resonance imaging (rs-fMRI) data, while for his Master’s thesis, he investigated part of the metabolic pathways of Mycobacterium Tuberculosis in the field of systems biology. He is currently applying multivariate statistical techniques to analyse brain connectivity in patient at different stages of Alzheimer’s disease (AD) and developing EEG-TMS systems based on brain connectomics for personalized treatment of epilepsy.

Coming soon

Coming soon

Coming soon