Research, corporate-transferable, and soft skills
My academic interests revolve around both classic, orthodox topics, and cutting-edge fields, both in computer science and
socio-economic research. The former include data-driven (often big data) research based on classical evolutionary algorithms
(i.e. neural networks, genetic algorithms and genetic programming, classifier systems), and machine learning (graph-based
semi-supervised learning in particular); econometrics, computational economics, novel applications of operational research
are part of the latter skill set. Complex systems, the overarching research area, lie at the interdisciplinary intersection of the
two; graph theory – complex networks in particular – and agent-based modelling are two of the analytic approaches I apply.
Tightly knit to my research, my experience in the private sector includes managing small-to-medium sized distinctly heterogeneous task forces. I have successfully led a large EU-funded project, starting from securing grant money, all the way down
to multi-site deployment of a production-grade software providing a supply chain optimization solution.
I have succesfully completed very demanding cross-domain collaborations, often spanning multiple countries and time
zones, in diverse areas: between those completed and ongoing, a cutting-edge ML effort on networked data labelling; a datadriven research on industrial conglomerates in Japan; a computationally-heavy exploration of language formation, and an
agent-based modelling of research hierarchies driving scientific discovery make for a prime example.
My data science vision is both wide and deep: I have acquired ample experience in multiple subfields and had the opportu –
nity to get actively involved in every stage of the analytics pipeline, from surveying potential data sources down to a convenient visual presentation of results, including devising appropriate storytelling skills.
I am considered a patient and empathic person, a good listener, also communicative and extrovert in very diverse environments; when needed, I don't pull back from challenging circumstances and can take care of solving conflicts, keeping groups
focused, morale high, and stick everybody's commitment to timely delivery. The Voltairean motto “Perfect is the enemy of
good” underpins most of my managing decisions.
Having spent more than a decade lecturing courses and teaching, up to the postgraduate level, and being routinely involved
in delivering both specialist and non-technical speeches, I am a natural when it comes to keeping an audience captivated, and in knowledge transfer.

Education
2017 PhD in Computer Science; dissertation title: “Tools for Understanding the Dynamics of Social Networks”. École Doctorale d'Informatique et Mathématiques, École Normale Supérieure, Lyon, France.

2001 MS in Economics; thesis on supply chain optimization (“job shop problem”), genetic algorithms-based optimization of
an agent-based model. Università degli Studi, Torino; further development funded within the EU-FP5 IST-2000-28221 cluster (EUTIST-AMI, MODA-ML activity, “Penelope” project); budget: 480.000€.

Employment history
Current positions
2018-present Universität Koblenz-Landau, E-Government Research Group at the Institut für Wirtschafts- und Verwaltungsinformatik, postdoctoral researcher, Koblenz, Germany. Research position in which – owing to my multidisciplinary
experience – I liaise between the business-oriented and the fundamental research computer science teams. My topics include
big data analysis, including mining data for socio-economic modelling, natural language processing, also involving large-scale distributed computing efforts.

2008-present (on leave) University of Torino, Department of Economics and Statistics, tenured research scientist, Torino,
Italy. My position requires multitasking capabilities to keep track of multiple assignments, spanning from data analytics to
knowledge transfer, to pure research. I brought novel computational approaches into my field of research, leaving behind standard econometric approaches in favor of algorithmic simulations (far-from-equilibrium dynamics in economics) and graph theoretical metrics. 

Previous positions
2008 University of Milan, Department of Information Technologies, “Simulation and Optimization Models for EMS
Management” fellowship, Milano, Italy. Regional emergency medical services were in need of an overhaul, with shrinking
budgets and strict requirements to rationalize expenditure; on this assignment, I developed a model of (heli)ambulance services, providing decision-makers with a tool to experiment and perform alternate scenario testing.

2004 Exystence Thematic Institute for Complexity and Innovation, member of the Regional Innovation Systems and Complexity WG, ARC Systems Research, Vienna, Austria. My involvement consisted in providing guidance in the project modelling effort, including Agent-Based formalization, calibration and validation, based on data and empirical evidence provided.

2001-2008 LABORatorio – Centre for Employment Studies Riccardo Revelli – Collegio Carlo Alberto Foundation, researcher, on a series of grants with the Università degli Studi di Torino. Since 2006, on an ISI (Institute for Scientific Interchange Foundation) Progetto Lagrange scholarship. Moncalieri, Italy. In this challenging position I complemented mainstream econometrics and simulation-based approaches into large scale analysis of economic administrative data. The diversity
of sources required integrating and harmonizing data from legacy and current systems. The resulting published works present
novel and compelling evidence of bounded rationality in economic behaviour.

2001-2004 EU-FP5 “Penelope Project”, leader (Agent-Based supply chain simulator), Torino, Italy; Barcelona, Spain; Saarbrücken, Germany; Athens, Greece. As a freelance consultant, in a leading capacity I provided industrial partners with a
production-grade supply chain optimization solution. Optimized production plans were computed by a combination of simulated processes evaluation and evolutionary algorithms (Agent-Based models and Genetic Algorithms). 

Visiting and other positions
2018 Visiting scholar, National Institute of Informatics, Tokyo, Japan.

2016 Santa Fe Institute “Complex Systems Summer School”, Santa Fe, NM.

2014-present Member of the board of directors, Vice president (since 2015), Swarm Development Group – SDG

CS skills
In coding Agent-Based Models, I tend to start prototyping in NetLogo, then move to a middle-ground object-oriented language (Python being my current choice), if needed also implementing distributed computing (e.g. Spark), eventually down
to a lower-level language (C++). I also happen to take care of data (ETL) myself, in calibrating and validating. In develop –
ing network-based algorithms, metrics and visualizations, I am familiar and rely on Python, Java, C, C++, Objective C, For –
tran; (non-)relational database solutions (e.g. Postgre/MySQL, MongoDB); other useful tools include R, Gephi, the
Swarm, Repast, Mason libraries; I prefer working under UNIX major flavours, GNU/Linux in particular.

Languages
Italian: native language; English and French: full professional proficiency; Spanish: limited working proficiency.