CURRICULUM VITAE
Nicola Orlando
Born in Taranto, Italy, 23-05-1986
Lives & works in Geneva, Switzerland
Languages: Italian (native), English (fluent), French (beginner)
Education
2011 - 2014 Ph.D. in Physics. Salento University (Lecce, Italy). Graduated with maximum evaluation (Excellent) | Ph.D. thesis https://cds.cern.ch/record/1755832.
2008 - 2010 M.Sc. in Physics. Salento University (Lecce, Italy). Graduated with 110/110 and honours.
2005 - 2008 B.Sc. in Physics. Salento University (Lecce, Italy). Graduated with 110/110 and honours.
Positions
2018 - present Research Scientist. Barcelona Institute of Science and Technology, Institut de Fisica d'Altes Energies (Barcelona, Spain).
2015 - 2018 Research Staff. The University of Hong Kong (Hong Kong, SAR China).
2014 - 2015 Postdoctoral Researcher. Aristotle University of Thessaloniki (Thessaloniki, Greece).
2014 Short term fellow. University College London (London, United Kingdom).
2012 - 2013 Research Fellow. European Organisation for Nuclear Research (Geneva, Switzerland).
Skills and research experience
Development and maintenance of multiple software projects for data mining, data visualisation, and statistical analysis.
Engineering of machine learning classification algorithms based on decision trees and feed-forward neural networks. Development of related software for high-level feature engineering and data visualisation. Application of decision trees and feed-forward neural networks to big-data research problems, mainly classification.
Statistical data analysis (development of likelihood models, hypothesis testing) for big-data research problems.
Engineering of a naïve Bayesian classifiers based on use of predictive models, application to big-data research problems.
Development of algorithms for data deconvolution and application to big-data research problems.
Development and software engineering of algorithms for parametric or non-parametric linear regression and
application to big-data research problems.
Developments of advanced analytical or numerical predictive models.