[Forum SIS] 3rd Seminar "D2 Seminar Series" - Florence Center for Data Science

[datascience a unifi.it]

Dear all,

The Florence Center for Data Science is happy to present the third 
Seminar of the “D2 Seminar Series” launched by the FDS. The Seminar will 
be held online Friday 18th of June 2021, from 2-3.30 pm.
The Seminar will be held by two new Fellows of the Center: the research 
unit COPERNICUS Earth Observation and Spatial Analysis and some 
researchers of the Magnetic Resonance Center (CERM). The speakers are 
Gherardo Chirici from COPERNICUS and the Department of Agriculture, 
Food, Environment and Forestry (University of Florence) and Enrico 
Ravera from the Magnetic Resonance Center (CERM) and the Department of 
Chemistry, University of Florence (see abstract below).

Register in advance for this webinar:
https://us02web.zoom.us/webinar/register/WN_I9bCjz_cQ_K_8nOP94usTw

After registering, you will receive a confirmation email containing 
information about joining the webinar.

We hope to see you there! You are invited to invite also your students, 
PhDs and colleagues who may be interested in the Seminar (you find a 
Flyer with all the info attached).

Kind Regards,
Florence Center for Data Science

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Speaker: Enrico Ravera - Magnetic Resonance Center (CERM) and Department 
of Chemistry, University of Florence

Title: From algebra to biology: what does the math of ensemble averaging 
methods can tell us

Abstract: Our work aims at a quantitative comparison of different 
methods for reconstructing conformational ensembles of biological 
macromolecules integrating molecular simulations and experimental data. 
This field has evolved over the years reflecting the evolution of 
computational power and sampling schemes, and a plethora of different 
methods have been proposed. These methods can vary extensively in terms 
of how the prior information from the simulation is used to reproduce 
the experimental data, but can be coarsely attributed to two categories: 
Maximum Entropy or Maximum Parsimony. In any case, the problem is 
severely underdetermined and therefore additional information needs to 
be provided on the basis of the chemical knowledge about the system 
under investigation. Maximum entropy looks for the minimal perturbation 
of the prior distribution, whereas Maximum Parsimony looks for the 
smallest possible ensemble that can explain in full the experimental 
data. On these grounds, one can expect radically different solutions in 
the reconstruction, but surprises are still possible - and can be 
justified by a rigorous geometrical description of the different 
methods.

Speaker: Gherardo Chirici - COPERNICUS Earth Observation and Spatial 
Analysis and Department of Agriculture, Food, Environment and Forestry, 
University of Florence

Title: Big data from space. Recent Advances in Remote Sensing 
Technologies

Abstract: Since the 1970s, remote sensing technologies for terrestrial 
observation have generated a constant flow of data from different 
platforms, in different formats and with different purposes. From these, 
through successive steps, spatial information is generated to support 
the Earth resources monitoring and planning. Indispensable in various 
sectors: from urban planning to geology, from agriculture to forest 
monitoring and, more generally, any type of information to support 
environmental monitoring. For this reason, remotely sensed information 
is recognized as a typical example of big data ante litteram. Today the 
new cloud computing technologies (such as Google Earth Engine) allow to 
face the complex problem of data management and processing of big data 
from remote sensing with new strategies that have revolutionized the 
these data sources are used. From experiments on small areas, today we 
have moved to the possibility of operationally processing vast 
multidimensional and multitemporal datasets on a global scale. The 
increased availability of information from space is exemplified by the 
numerous services offered by the European Copernicus program. The 
presentation, starting from a brief introduction to remote sensing 
techniques, illustrates some examples of applications developed within 
the geoLAB - Geomatics Laboratory of the Department of Agriculture, 
Food, Environment and Forestry (DAGRI) and the UNIFI COPERNICUS Research 
Unit.
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