PhD Welcome Session 2017-2018

PhD Programme on Information and Communications Technology (DocTIC)

University of Vigo

Date: Wednesday,  October, 18, 2017

Place: "Salón de Grados" (Conference Room) of the Telecommunication Engineering School


Welcome session for new PhD Students and current PhD Students. The event is an opportunity  for all new Doc_TIC PhD students and faculty members to meet and also a talk by a distinguished speaker will be delivered.




Opening: Prof. Carmen Garcia-Mateo, Coordinator of DocTIC PhD Program

Prof. Manuel García-Sánchez, Secretary of the Academic Board


Lecture by Dr. Francesco A. Massucci  

Chairperson: Prof.Domingo Docampo



Dr. Francesco A. Massucci

SIRIS Academic

Lecture Title

Universities as Big Data mines: data science for evidence-based policies in Higher Education and Research.

Lecture Abstract

The technological developments in the ICT sector of the last few years allowed for the digitalisation of an ever growing array of data, at varying granularity: as media outlets emphatically stress, we are indeed in the age of Big Data. But beyond the rhetoric, one of the apparent bright sides of Big Data is how the latter may be profitably exploited to design newer policies, that are data-driven and thus informed and hopefully more effective.

In this talk, I will describe how text and data-mining techniques may be used in the context of Higher Education & Research (HE&R) for valorisation policies and benchmarking purposes, by taking three levels of data and metadata granularity as an example. I will first describe how to use aggregated research data (low granularity) and related indicators for comparing research institutions and setting meaningful targets in research policy. Second, I will discuss how to exploit publications metadata (medium granularity) to establish prestige rankings in a given discipline. Finally, I will show how the textual content of single publications (high granularity) may be fed to text-mining algorithms in order to i. characterise the research portfolio of a given institution and ii. to identify researchers dealing with a specific topic.

The type of analyses discussed in the talk may be of great profit for the management of research organisations and will be increasingly feasible as the sources of open HE&R data grow.


Francesco A. Massucci (Rome, 1983) received both his BSc and his MSc in Physics from the Università di Roma La Sapienza. He later obtained his PhD in Applied Mathematics at King’s College London, where he studied some applications of Statistical Mechanics to Biological Systems. Afterwards, he moved to Spain, where he carried out his postdoctoral research on Complex Systems and Network Science at Universitat Rovira i Virgili (Tarragona) and Universitat de Barcelona, respectively. From 2016 he holds a Senior Researcher position at SIRIS Academic. There, he works mainly as a data scientist specialised in modeling and applying text-mining methods to extracting insights from the large amount of data produced by higher education and research institutions.