Mercoledì 23 marzo Nicola Toschi sarà speaker del nuovo appuntamento con il ciclo di seminari Artificial Intelligence and Mathematics 2022. Nicola Toschi èNicola Toschi e' Professore Associato di Fisica Applicata presso l'università di Roma Tor Vergata e si occupa di fisica MRI, sviluppo di modelli meccanicistici e statistici per la comprensione di fenomeni fisiologici, image-processing, imaging MR non Gaussiano in patologie neurodegenerative, imaging MRI a campi ultra-alti e stime predittive del rischio emodinamico intraoperatorio.
Per l'occasione, presenta un talk dal titolo "Specialization of deep learning architectures for modelling brain activity and function" con il seguente abstract:
In the last 5 years, the advent of deep learning (DL) paradigms has revolutionized the field of artificial intelligence (AI). Previously, the contribution of AI across disciplines was confined to applications whose overall complexity is low, and towered by that of human physiology. However, modern DL paradigms offer unprecedented ability to integrate multimodal, multi-domain, and multiscale data with previously unimaginable prediction performance and little or no need for data preprocessing. With advent of ‘big’, publicly available, and often multidomain data repositories it is now possible to build and validate AI frameworks with a tangible potential to boost neuroscience research, enhance decision-making in disease management algorithm, and enrich next-generation clinical trials. This seminar will focus on the latest developments and deep architectures for modeling and studying biomedical data in general and brain structure and function in particular, as measured through e.g.. MEG, EEG, or MRI. Particular emphasis will be given to key architectural developments like e.g. separable convolutions, multi-head attention networks, spiking neural networks graph and contrastive learning. Every example will include a use-case stemming from an ongoing or published study.
Il seminario sarà in inglese.