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Personal profile

Research information

Christian M. Dahl's research agenda is broad and interdisciplinary. One part is focusing on theoretical statistics and time series analysis with applications in finance. A second part is focusing on nonparametric estimation and causal inference, including random fields, neural networks and deep learning.  Christian has extensive experience working with deep neural networks and random fields (computer vision and machine learning techniques) and has made significant theoretical and empirical contributions to this research field. With the increasing availability of an exploding number of digitized historical documents constituting an incredible new, rich and for large parts still unused source of data Christian is directing his research and his expertise in computer vision and deep leaning towards developing tools for automated harvesting (transcribing) data from digitized historical (and possibly degraded) documents. Christian has established an interdisciplinary research unit on “Big Data Analytics and Digitization” (BDAD) within the Department of Business and Economics (DBE) at SDU. The aim of this research unit is to become a leading interdisciplinary research unit worldwide in harvesting, linking and analyzing individual data from digitized/scanned structured handwritten historical documents. Current research projects involve developing deep learning techniques for transcribing census and church records and about 20 million Danish death certificates. Christian and members of BDAD are currently working jointly with many national archives in developing citizen science data collection strategies (see, for example, www.basecrowd.dk) to begin digitalization of health data, including the Danish death certificates.  The harvested data will make it possible to study early-life health policies, parental investments, the formation of human capital, and socio-economic and health trajectories. Christian has recently received funding from the InnoBooster program regarding the development a web-based software application that based on AI and Machine Learning tools can assist citizens in evaluating (probabilistically) their prospect in case of lawsuits.

Research areas

  • Big Data Predictive Analytics
  • AI and Machine Learning
  • Computer Vision
  • Time series Econometrics
  • Quantile Regression
  • Panel Data Analysis

Curriculum

Christian M. Dahl acquired his PhD degree in economics in 2000 from Aarhus University. He is now Professor at the Department of Business and Economics, University of Southern Denmark after being affiliated with first the Krannert School of Management, Purdue University, USA, for several years and School of Economics and Management, Aarhus University. He is member of the editorial board for Annals of Finance. He is also member of the Danish Research Foundation (the council for social science) and sitting on the Danish Innovation Foundations Innoboster Panels on AI and Machine Leaning. His has published in leading journals, such as Journal of Econometrics, Journal of Labor Economics, Journal of Business and Economic Statistics, The Econometrics Journal, and International Journal of Forecasting.

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