La "data factory"

Faten Amama

Faten Amama
Data Scientist

Training and Experience

  • Master's degree at Sophia Antipolis university as a data scientist.
  • Data Scientist, MindLytix (internship, March - September 2017)
    MindLytix is a start-up company working in the field of digital advertising, who helps firms to better target their advertisements. Faten's main task was to process textual data to understand users' moods and to know their interests via their browsing history.

Methodologies

  • Textual analysis
  • Unsupervised processing of textual documents
  • Automatic text segmentation
  • Topic modelling
  • Sentiment analysis

Programming Languages and databases

  • Programming languages : C++, JAVA, Pascal, Maple, Python, R, Spark
  • Databases : SQL, MySQL, NOSQL, Oracle, Hadoop

Bruno Chaves

Bruno Chaves
Coordinator of the project

A double background in computer sciences and economics / econometrics

  • CNRS Engineer in Information Technology, data analyst and project manager since more than 10 years.
    (Nanterre University, Ecole Normale Supérieure and Dauphine University)
  • Previously : Research and teaching assistant in econometrics / statistics (Sorbonne University)

Coordinator for several international research projects :

  • SIOE - Society for Institutional & Organizational Economics (coordinator since 2007)
  • IOEA - Institutional & Organizational Economics Academy (co-coordinator since 2002)
  • DIME - Dynamics of Institutions and Markets in Europe (IT manager 2005-2011)

Methodologies and tools

  • Project management, object and test driven development, continuous integration methodologies.
  • Data analyst (Python, SQL and NoSQL databases), full stack web development (JavaScript, CSS, PHP, HTML5).

Svitlana Galeshchuk

Svitlana Galeshchuk
Post-doctoral fellow in data science

Training

PhD in Economics (Ukraine, 2015): Accounting and Analysis of Foreign-Exchange Operations

Publications / Award

Awards

  • 2017 : Visiting Researcher at the National Bank of Poland (May 15-26/17)
  • 2017 : Invited Professorship at Université Grenoble-Alpes, France (01/17-07/17)
  • 2015 : Fulbright Faculty Development Research Scholarship, IIE, USA
  • 2013 : Eiffel excellence scholarship, French Ministry of Foreign Affairs, France

Research Fields

Financial Markets, Monetary Policy, Economic Forecasting, Data Analysis, Neural Computing

Methodologies and tools

  • Data Analysis: high-dimensional problems, clustering, genetic algorithms
  • Neural Computing and Forecasting: neural networks, deep learning
  • Software: Python, R, Tensorflow

Mohammad M. Habibpour

Mohammad M. Habibpour
Post-doctoral fellow in economics

Training

Ph.D. in Economics from University of Brussels (VUB), Belgium
Doctoral fellows program, Center for Social Impact Strategy, University of Pennsylvania, USA
Master of Science in Economics from University of Siegen, Germany

Publications / Award

  • How giving affects giving: a long-term analysis of donations. Applied Economics (2017, 66, 35-42 ). Coauthor with Peiffer, M., Jegers, M. & Pepermans R.
  • Resource rents distribution, income inequality and poverty in Iran. Energy Economics (2017, 50:21, 2402-2413). Coauthor with Farzanegan M.
  • The importance of sector stereotypical images in relation to job pursuit intentions. Nonprofit Manage-ment and Leadership (2018, DOI: 10.1002/nml.21304).
  • Coauthor with Peiffer, M., Pepermans R., & Jegers, M.
  • Effects of Releasing Subsidies on the Wage Rates and the Gender Wage Inequality. In: Jon Strand (Editor): The Politics and Political Economy of Energy Subsidies. Cambridge, MA: MIT Press. Forth-coming, 2016. Coauthor with Seiban N.
  • Iran economy. In: The Europa Regional Surveys of the World. The Middle East and North Africa. 2016 Routledge. Taylor & Francis Group. Coauthor with Farzanegan M.

Research Fields

Economic Developments (Resource rents, Inequality, Poverty)
Economics of NPOs (non-profit organizations), (Donations, Social networks, volunteering)
Econometrics

Methodologies and tools

  • Timeseries analysis, Bayesian estimations, structural equation modeling, spatial analysis.

Abir Jaza

Abir Jaza
Data Scientist

Training and Experience

  • Engineering degree from the National School of Computer Studies ENSI of Tunisia in Computer Science with the passion for Data Analysis.
  • DISP Laboratory Internship, from February till July 2018, working on a task in a European Project, consisting of implementing a solution for managing and treating enterprises’s documents and data.

Methodologies

  • Textual analysis
  • Web Scrapping
  • Web Development
  • Sentiment analysis
  • Modeling

Programming Languages and databases

  • Programming languages : C, C++, JAVA, JavaScript, PHP, Pascal, Python, R
  • Databases : SQL-> MySQL, NoSQL-> MongoBD, Hadoop

Ju Qiu

Ju Qiu
Post-doctoral fellow in economics

Training

PhD (Toulouse School of Economics, 2014), Thesis: Essays on Household Consumption Behaviour and Risk Sharing in Developing Countries

Publications

  • Impact of Tenure Reform on Forest Management Models: the Case of Fujian Province (with Yan Sun, Jintao Xu, and Ling Li), The Journal of Forestry Economics (a peer reviewed journal in Chinese), January, 2007, p.23-27.

Working papers:

  • Nonparametric Decomposition of the Distributional Change in Body Mass Index in China (with Professor Pierre Dubois)
  • Migration, Consumption Smoothing and Household Income: Evidence from Thai Villages (with Yaping Wu)
    Sorting in Risk-sharing Networks: Evidence from Thai Villages
  • Income Gains From Internal Migration in China (with Professor L. Alan Winters)

Research Fields

Applied Microeconomics, Development Economics, Health Economics

Methodologies and tools

  • Econometrics: identification of causality and program evaluation, Nonparametric Decomposition method, Panel data analyses, Discrete Choice model
  • Types of Data: Cross-sectional, short and long panels, network data
  • Statistical Softwares: Stata, Matlab, R