Inhaltspezifische Aktionen

Dr. David Lenz

Dr. David Lenz

Projektmitarbeiter

Telefon: 0641 / 99-22655

Sekretariat: 0641 / 99-22641

E-Mail:


Anschrift:

Justus-Liebig-Universität Gießen

Fachbereich Wirtschaftwissenschaften

Professur für Statistik und Ökonometrie

Licher Str. 64

35394 Gießen

 

 

Responsibility

  • Postdoctoral Researcher DynTOBI Project
  • DynTOBI - Dynamische Textdaten-basierte Output-Indikatoren als Basis einer neuen Innovationsmetrik
    (TOBI - dynamic text data based output indicators as basis for a novel innovation metric)
  • In cooperation with Centre for European Economic Research (ZEW) in Mannheim

Research Interests

  • Data Science
  • Machine Learning
  • Forecasting
  • Deep Learning
  • Text Mining
  • Neural Networks
  • Big Data
  • CryptoCurrencies

Grants

Articles in Refereed Journals

Discussion Papers & Conference Proceedings

Expertises

Talks

  • 2019: Predicting Innovative Firms using Web Mining and Deep Learning, Seminar Webscraping von Unternehmensdaten, Statistisches Bundesamt, Germany
  • 2019: Predicting Innovative Firms using Web Mining and Deep Learning, LISH Harvard University Seminar, Cambridge, Massachusetts, Vereinigte Staaten von Amerika (USA)
  • 2019: Predicting Innovative Firms using Web Mining and Deep Learning, International Business School Brandeis University Seminar, Waltham, Massachusetts, Vereinigte Staaten von Amerika (USA)
  • 2019: Predicting Innovative Firms using Web Mining and Deep Learning, Deutsche Bundesbank Seminar, Deutsche Bundesbank in Frankfurt am Main, Germany
  • 2018: Measuring the Diffusion of Innovations with Paragraph Vector Topic Models, 23rd International Conference on Computational Statistics (COMPSTAT), Iasi, Romania
  • 2018: Measuring the Diffusion of Innovations with Paragraph Vector Topic Models, 16th ZEW Conference on the Economics of Information and Communication Technologies, ZEW - Zentrum für europäische Wirtschaftsforschung in Mannheim, Germany
  • 2018: Measuring the Diffusion of Innovations with Paragraph Vector Topic Models, 20th ZEW Summer Workshop for Young Economists, ZEW - Zentrum für europäische Wirtschaftsforschung in Mannheim, Germany
  • 2018: Measuring the Diffusion of Innovations with Paragraph Vector Topic Models, 1st CRoNoS Workshop on Multivariate Data Analysis and Software, Limassol, Cyprus

Repositories