Postdoctoral researcher focusing on macroeconomics, forecasting, energy markets, and climate change.

Teaching

Interim Professorship for the undergraduate course in Macroeconomics

Interim Professorship, University of Leipzig, 2025

In this course, I teach the core foundations of modern macroeconomics at the undergraduate level. The course introduces students to short-run and long-run macroeconomic analysis, covering topics such as aggregate demand and supply, business cycles, fiscal and monetary policy, economic growth, labor markets, inflation, and open-economy macroeconomics. A strong emphasis is placed on analytical reasoning, graphical intuition, and the application of standard models (e.g. IS–TR/LM, AS–AD, Solow growth model) to real-world economic issues and policy debates.

Introduction to Octave/Matlab for Macroeconomics

Workshop, Central German Doctoral Program in Economics, 2024

This PhD-level workshop provides a hands-on introduction to Octave/Matlab for applied macroeconomic research. I cover the fundamentals of numerical computing, matrix algebra, scripting, and workflow organization with a focus on typical macroeconomic applications. The course introduces Dynare as a standard tool for solving and simulating dynamic stochastic general equilibrium (DSGE) models, including model specification, steady-state computation, linearization, and impulse response analysis. Emphasis is placed on reproducible research practices and building a solid computational foundation for quantitative macroeconomic modeling.

Practical Training: Macroeconomic Modeling of Climate Shocks (DGE–CRED)

Workshop / Capacity Building, Halle Institute for Economic Research (IWH) / GIZ, 2022

This technical practical training was conducted as part of the GIZ project “Climate-Resilient Economic Development in Vietnam”. The workshop taught advanced methods for integrating climate risks into Dynamic General Equilibrium (DGE) models.

Statistical Programming

Tutorial, Humboldt-Universität zu Berlin, 2016

This tutorial provides an introduction to statistical programming for students in economics and related fields. It covers core programming concepts, data manipulation, basic statistical analysis, and reproducible workflows. The focus is on developing practical coding skills for empirical research, enabling students to structure data-driven projects clearly and efficiently.