Regression Analysis
Lecturer, bachelor level course, University of Southern Denmark, 2025
Course for the Economics bachelor’s program (10 ECTS).
Teaching
Here you can find some of my teaching activities. The list is non-exhaustive.Historical Perspectives on Current Economics Issues: Big Data and Applications
Lecturer, PhD and master level course, University of Southern Denmark, 2025
PhD-course and elective summer course for the Economics master’s program (10 ECTS).
Machine Learning in Economics & Finance
Lecturer, master level course, University of Southern Denmark, 2025
Elective course for the economics master’s program (10 ECTS). The aim of this course is to enable students to use state-of-the-art methods in machine learning, including their applications in economics and finance.
Statistics
Lecturer, bachelor and master level course, University of Southern Denmark, 2024
Course for the PDI engineering bachelors’s and master’s program (5 ECTS). The course cover introductory statistics, including probability theory, confidence intervals, hypothesis testing, linear regression analysis, factor analysis, and cluster analysis. The goal is to give students the ability to confidently perform and interpret statistical analyses.
Historical Perspectives on Current Economics Issues: Big Data and Applications
Lecturer, PhD and master level course, University of Southern Denmark, 2024
PhD-course and elective summer course for the Economics master’s program (10 ECTS).
Applied Statistics
Lecturer, bachelor level course, University of Southern Denmark, 2024
Course for the GMM engineering bachelors’s program (5 ECTS). The course cover introductory statistics, including probability theory, confidence intervals, hypothesis testing, linear regression analysis, factor analysis, and cluster analysis. The goal is to give students the ability to confidently perform and interpret statistical analyses.
Applied Machine Learning
Guest lecturer, master level course, University of Southern Denmark, 2023
Course for the Data Science master’s program (10 ECTS). The course covers support vector machines, random forests, boosting, and deep learning, with an emphasis on deep learning. The goal is to give students the ability to confidently apply state-of-the-art machine learning methods to a broad class of problems, including computer vision and natural language processing.
Deep learning model deployment on supercomputers
Guest Speaker, Brigham Young University (virtual), 2022
Invited speaker at the Record Linking Lab at Brigham Young University on deep learning model deployment on supercomputers.
Applied Machine Learning
Lecturer, master level course, University of Southern Denmark, 2020
Course for the Data Science master’s program (10 ECTS). The course covers support vector machines, random forests, boosting, and deep learning, with an emphasis on deep learning. The goal is to give students the ability to confidently apply state-of-the-art machine learning methods to a broad class of problems, including computer vision and natural language processing.
Regression Analysis
Guest Lecturer, bachelor level course, University of Southern Denmark, 2019
Course for the Economics bachelor’s program (10 ECTS).
Microeconometrics
TA, master level course, University of Southern Denmark, 2019
Course for the Economics master’s program (10 ECTS).