• Fuglesangs Allé 4, 2621, 16

    8210 Aarhus V

    Denmark

20122024

Research activity per year

Personal profile

Research

Jesper's primary lines of research is data analytics, specifically how researchers understand and use statistics, and how their use of data and statistics can be improved. He also contributes his expertise as a statistician and a data scientist to empirical studies spanning corporate finance, social epidemiology, and public administration.

Jesper has published in top field journals such as Organizational Research Methods, Journal of International Business Studies, the Leadership Quarterly, Public Administration Review, Journal of Corporate Finance, British Journal of Management, and Strategic Organization.

Profile

Jesper N. Wulff is an Associate Professor at the Department of Economics and Business Economics, Aarhus University. He holds a PhD in Economics and Business Economics from Aarhus University (2015), an MA in Data Analysis from the University of Essex (2015), and an MA in Business Administration from Aarhus University (2011).

Jesper serves as an Associate Editor and Method Reviewer for the Leadership Quarterly and as a Methods Consultant for the Journal of Management Methods Task Force.

Teaching

Jesper teaches deep learning in the master's course in Machine Learning for BI 2, a mandatory course for Msc. in Business Intelligence. He also teaches an elective master's course in Generative AI with LLMs offered both for Msc. in Business Intelligence and Msc. in Data Science students. In addition, Jesper undertakes supervision of master theses and topic reports as well as Ph.D. supervision. 

For his teaching efforts, Jesper has been awarded the Aarhus BSS Lecturer of the Year Award.

Job responsibilities

Jesper is the programme coordinator for the Master's in Business Intelligence degree programme (cand.merc with specialisation in Business Intelligence) and teaching coordinator for statistics courses at HA/BSc(B)/HA(jur). 

Keywords

  • Machine learning
  • Quantitative Methods

Areas of expertise

  • Data Analytics
  • Applied Data Science
  • Organizational Research Methods
  • Meta Science

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