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H. Jost Reinhold

http://usi.to/vzs

Biografia

H. Jost Reinhold received his BS/MS degree in Industrial Engineering (Ingegneria Gestionale) from the Politecnico di Milano, Italy.

From 1988 to 1996 he worked for RHIAG SpA, the leading automotive parts distributor in Italy. Left as vice-president for logistics and information systems. Main projects: promoted and managed the introduction of personal computers and the following switch from a mainframe-based environment to a networked-distributed one; initiated and developed the restructuring of the forecasting methods and of the distribution system leading to daily (from bi-monthly) deliveries of the parts.

In 1998 he received a MS in Information Systems from the Stern School of Business and the Courant Institute of Mathematical Sciences at NYU, New York, USA.

For the following three years he worked as a consultant for Data Mining Systems, in New York, where he was part of a team, lead by prof. Vasant Dhar, that developed systematic trading models for commodities utilizing machine Learning methods (a genetic-based rule-learner was developed in-house by the team). The models were used by a major bank for their proprietary trading.

From 2005 he has been assisting prof. G. Arbia with the courses of Elementi di Statistica (2nd year of the Bachelor in Communication Sciences), Data Analysis (2nd year of the Masters in Marketing, Corporate Communication, Management), and Metodi Quantitativi (1st year of the Masters in Public Management and Policy and, formerly, Media Management).

For over five years he has been teaching the Statistics Tutorial offered to master students with little of no previous exposure to quantitative methods.

His focus, with regard to teaching, is on how technology can help students achieve the desired learning goals. The Elementi di Statistica course is one of the first courses offered in Italian that consistently utilized the MyMathLab online platform.

From 2008 to 2017 he helped and advised countless bachelor, master, and PhD students, with regard to the use of data science methods in their theses, field projects, dissertations, research projects.

  

Theses supervised by prof. Arbia.

Bachelor in Communication Sciences:

Recent (2016): Irene Bellora (Overview of Data Science Methods), Micol Dardani (Analysis of Quality of Life in Italian Provinces), Chantal Zengaffinen (within the project on the relocation of public access defibrillators). 

Current (2017): Giorgio Bignami (Data-Based Determinants of Suicide Rates across Countries), Carola Garré (Analysis of Swimming and Running Performances of Men and Women across the past 100 Years), Selim Süglün (Analysis of Police Interventions on Highways).

  

He is currently a PhD candidate in Data Science, with research interests in various fields (see publications).