About me

I'm Christopher, studying Sociology and People-Oriented Computing at the University of Zurich and working as a Research Assistant at the Department of Sociology.

My approach to demanding challenges has been shaped by three formative phases in my life: As a competitive basketball player, I learned discipline and team spirit. Above all, I learned to quickly recognize where and how I can most effectively contribute my personal strengths in changing group constellations. Professional poker taught me to make rational decisions based on probabilities and to trust a process with a calm mind, without losing my focus to intermediate results. As an actor, I discovered the complexity of human motivations and the ability to devote myself completely to a task.

Analytical precision, psychological understanding, and the willingness to fully immerse myself in new problems — this combination found its natural home in academic study. There, I learned to empirically analyze social phenomena, apply quantitative methods to social science research questions, and understand how the interaction between people and digital systems can be researched, designed, and improved. I've been particularly shaped by courses like Human-Computer Interaction, Computational Social Science, Social Computing, and Digital Sociology, where social science thinking and data-driven methods come together directly.

For nearly four years, I've been working as a research assistant at the Department of Sociology: I collect and analyze quantitative data, conduct qualitative research, and co-author publications. As a tutor, I've guided several hundred students through empirical methods and sociological foundations, learning above all how to communicate complex content in an accessible way and to adapt to different learning styles and levels of knowledge.

I'm driven by the conviction that many of the questions that matter to people today can only be answered by placing them in their social context — and that this requires a critical understanding of data: how it is collected, what methods produce it, and how differently it can be presented and interpreted. For me, using data strategically means creating transparency rather than deepening inequalities. Good answers don't emerge in a vacuum, but at the intersection of social science thinking and technical competence.

I love cinema, literature, and I'm a justice enthusiast.