Short Summary

I am a mathematical microeconomist focusing on providing efficient software solutions for large-scale mathematical decision modeling and econometric estimations using big data with novel formats, statistical learning, and distributed technologies. My research focuses on market models, game theory, and industrial organization. I have previously studied mathematics and economics and have some professional experience in software design and development.

I am occupied as a postdoctoral researcher at the Department of Operations in the University of Groningen. Moreover, I am a research affiliate of Leibniz Institute for Financial Research SAFE, and a researcher of the EurHisFirm consortium.

If you are looking for something more formal, you can take a look at my Curriculum Vitae. I also include more details for the interested reader about the things that I am passionate about in science, research, and technology.

More Details

From my point of view, reproducibility, comparability, and accountability are concepts that are essential not only in STEM but also in economics. Therefore, I actively contribute to open-source solutions to promote these concepts in my fields. In this respect, I am the maintainer of the statistical R package markets, which is distributed by CRAN, under open access and open source terms, and provides methods for estimating markets in equilibrium and disequilibrium. I am involved with the architecture and the implementation of a German financial historical database based on historical firm-level data extracted from historical archives with semi-automated techniques. Finally, I am developing entity-matching software (in Python, R, and C++) that can be used when linking various types of formatted and unformatted data using artificial neural networks and a novel similarity encoding approach.

For those who share a passion for mathematics, I am interested in recursive, dynamic stochastic problems (e.g., optimal control and Bellman theory), potentially entailing strategic interaction elements and general equilibrium theory (e.g., Riesz spaces). I like to approach these topics from a function-analytic perspective. This approach is also very appropriate when it comes to implementing parallelized, cluster-scalable numerical methods to solve problems without analytical solutions (e.g., fixed-point methods).

For those interested in software development, I write in programming languages following different paradigms, ranging from procedural, object-oriented, and functional, depending on the case. As a LISP enthusiast and because of my mathematical background, I enjoy functional programming the most. I mostly use C and C++ when writing for high-performing cluster computing.

In any case, do not hesitate to contact me for anything that you may think that it is of interest.