Tech Share Day 2021, research meets companies and investors: SISSA participates with a webinar on machine learning in biomedical domain

Tech Share Day is a completely free and digital event that connects the world of public research with that of companies, investors and innovators. This 2021 edition (from November 24 to 26 ) will focus on IoT and Artificial Intelligence, with 8 thematic webinars and panels of international speakers.

This year, together with the historical organizers - Netval, UIBM (Ufficio Italiano Brevetti e Marchi del Ministero dello Sviluppo Economico and the collaboration of the Politecnico di Torino PoliTo - played a central role the Jotto network (Joint Technology Transfer Office) of the six Italian School of Excellence. 

 

SISSA will participate by organizing a webinar with the theme "From Data to Knowledge to action: machine learning in the biomedical domain" (November 24  from 4 to 6 pm).

Biomedicine is fast becoming a prime domain of application for data science. Technological breakthroughs offer the possibility of harvesting data at scale in a variety of contexts, from genomics to imaging to physiological and neurological signals. The complexity and diversity of the data offers phenomenal challenges to data science in a high impact area. In this webinar, we will illustrate recent research from SISSA scientists in four major areas of application: 1) cancer genomics, the problem of reconstructing the evolutionary history of cancers from sequencing data; 2) the problem of selecting automatically the relevant features to perform a prediction or develop a model in a clinical context; 3) the analysis and modelling of neuronal spiking data, uncovering the high-level functions of the brain; 4) the modelling of blood flow in the cardiovascular systems, marrying the physics and mathematics of fluids with data science and high performance computing.

AGENDA WEBINAR November 24 from 4 to 6 pm 

Prof. Guido Sanguinetti Cancer genomics, the problem of reconstructing the evolutionary history of cancers from sequencing data

Prof. Alessandro Laio The problem of selecting automatically the relevant features to perform a prediction or develop a model in a clinical context

Prof. Eugenio Piasini  The analysis and modelling of neuronal activity data, uncovering the high-level functions of the brain

Prof. Gianluigi Rozza The modelling of blood flow in the cardiovascular systems, marrying the physics and mathematics of fluids with data science and high performance computing

Here to register