After completing my master's degree, I was eager to delve deeper into the intersection of Economics and Computer Science. This led me to pursue a Ph.D. at Bielefeld University, renowned for its pioneering work in Computational Economics. My decision was significantly influenced by my keen interest in economic modeling and the application of computational techniques in economic research.

The Chair for Economic Theory and Computational Economics at Bielefeld University, led by Prof. Dawid, presented an unparalleled opportunity. The department is at the forefront of integrating advanced computational methods with economic theory, a synergy that perfectly matched my academic pursuits.

Computational Economics, being a relatively new but rapidly evolving field, is not yet a mainstay in all economics departments. Bielefeld University stands out as a leading institution in Germany in this specialty. Joining Bielefeld University allowed me to build upon a substantial foundation of expertise and contribute to a field that is reshaping how economic analysis and modeling are conducted.

Uncertainty plays a pivotal and multifaceted role in my research, especially considering the dynamic and often unpredictable nature of economic systems: Technological innovations, for instance, bring about disruptive changes by their very nature, which can have far-reaching implications for markets, industries, and entire economies. My research is dedicated to gaining a deeper understanding of how economic actors navigate various uncertainties and the extent to which their attitudes towards uncertainty shape key economic decisions, behaviors, and outcomes. This involves examining the strategies and mechanisms employed by individuals and organizations to manage and respond to uncertain economic environments, and how these approaches impact their decision-making processes and subsequent economic activities.

The Center for Uncertainty Studies has significantly broadened my horizons, fostering opportunities for interdisciplinary collaboration with leading researchers across various social sciences. My aspiration is to make substantive contributions to these fields by employing a combination of empirical research and simulation methods. Through this methodology, I aim to effectively identify, distinguish, and model the diverse sources of and strategies for managing uncertainty. I believe, this approach will facilitate the identification and more nuanced characterization of strategies for navigating uncertainty across diverse disciplines.

The field of computational economics is fundamentally interdisciplinary, drawing essential insights not only from Economics and Computer Science but also from a broader range of disciplines, especially within the social sciences. This interdisciplinarity is crucial in my work, given the complex and interconnected nature of today's economic systems. By integrating diverse academic perspectives, particularly from other areas of social sciences, my research benefits from an enriched and expanded scope. This fusion of disciplines enhances the depth and breadth of analysis, allowing for a more thorough and effective understanding of complex economic environments. Such a comprehensive approach is indispensable for accurately interpreting and predicting economic phenomena in an interconnected world.

 

What could possibly be more monotonous than a life scripted down to the last detail, where surprise is as rare as a unicorn? Predictability might have its comforts, but it's the uncertainty that adds the spice of excitement and opportunity. As for strategies, I don't adhere to a rigid playbook. Instead, I prefer to see uncertainty as a canvas of possibilities, a space where the unknown becomes a playground for innovation and discovery. It's in this uncharted territory that the most interesting chapters of our stories are written.