Work and teaching experience
|Jan 2013 — present||Researcher at IDSIA, Dalle Molle Institute for Artificial Intelligence,
Department of Innovative Technologies - SUPSI,
University of Applied Sciences of Southern Switzerland
|Feb 2015 — present||Lecturer at SUPSI. Courses Taught: Computational Mathematics and Algorithms,
Mathematical computation tools, Applied statistics.
|May — Jun 2012,
Apr — Sep 2011,
Jun — Sep 2010,
Jun — Oct 2009
|Visiting researcher at the Computerized Operation
Support Systems division of the
Institute for Energy Technology -
OECD Halden Reactor Project, Halden, Norway. Development and
application of data-mining and machine learning to component diagnostics
and prognostics in the fields of nuclear energy and oil&gas production.
|Sep 2011 — May 2012||Teaching assistant at Politecnico di Milano for the
courses Nuclear power plants operations and maintenance and
Computational methods for safety and risk analysis I and II .
|March 2017 — August 2018||AI based models for the forecast of electric energy production and price.
Development of predictive models based on probabilistic and artificial intelligence
methods for the forecast of energy production from renewable power plants (solar and wind farms)
and the support of selling and buying decisions on the commodity market.
|May 2015 — July 2016||Adaptive systems for foreign languages teaching.
Development of an adaptive e-learning system to evaluate students competences.
Based on AI reasoning techniques, the system estimates student' skills
and automatically selects the questions more suited to the student in order
to maximize the accuracy of the evaluation while limiting the duration of the test
(e.g., by avoiding questions that are too easy or too difficult).
A prototype has been released for language teaching at SUPSI.
|Jul 2015 — 2017||GoEco! A community based eco-feedback approach to promote sustainable personal mobility styles. Statistical analysis and mining of mobility tracking data for transport mode detection and user profiling.|
|Jan 2013 — Dec 2014||Learning under near-Ignorance: models and methods. Development of robust methods for learning from data in situations of uncertainty and lack of knowledge. By modeling a situation of prior near-ignorance by means of set of prior distributions, these methods naturally lead to indeterminate (i.e., set-valued) predictions, so that, when the information from data is not enough to draw stronger conclusions, they originate very credible and reliable models.|
|Jan 2010 — Mar 2013||Ph.D. in Energy and Nuclear Science and Technology, Department of Energy, Politecnico di Milano, Italy. Dissertation title: “Development of advanced computational methods for Prognostics and Health Management (PHM) in energy components and systems.”|
|Sep 2007 — Dec 2009||MSc in Nuclear Engineering, Department of Energy,
Politecnico di Milano, Italy
|Sep 2005 — Dec 2009||MSc in Engineering,
Ecole Centrale Paris, France.
|Sep 2005 — Jun 2007||BSc in Fundamental Physics,
Université Paris-Sud 11, France.
|Sep 2003 — Sep 2007||BSc in Physics Engineering,
Politecnico di Milano, Italy.
Computer and programming skills
Extensive knowledge of Python, Matlab and R.
Good knowledge of Java.