I am a senior analyst in the Science, Technology and Innovation Policy Team at the Mercator Institute for China Studies (MERICS). My area of expertise includes geopolitics of technology, China’s self-sufficiency drive, also in semiconductors and state-sponsored hacking. I lead MERICS' effort to use data-driven research methodologies to answer questions about China.
I give talks on China’s technology development and its implications for Europe and digital China, in the past for example on Chinese state-sponsored hacking, surveillance technology in China, China’s progress on semiconductors and its internet architecture.
I am passionate about the importance of data literacy. In my free time, I analyze data using Python and R, and experiment with using Generative AI.
M.A. in International Relations/Political Science, 2014
Graduate Institute of International and Development Studies
B.A. in East Asian Politics and Economics, 2012
Ruhr-University Bochum
Use R for data analysis regularly, particularly Tidyverse and Rmd
Wrote multiple regression-based papers
Solved Advent of Code using Python
Wrote multiple papers with Tex
Have been administering my own server and workstation for >5 years
Good knowledge
Maintain over 80 scrapers
Gave multiple talks to audiences of up to 2000 people
Talks on Chinese economic development, especially China’s foreign economic relations and internet economy, e.g. for Schader Stiftung
Did data analysis work for publication for Bertelsmann Stiftung: What the West Is Investing along China’s New Silk Road

The Chinese Social Credit System (SCS) has been discussed a lot in Western media. However, we do not know currently how the system that is supposed to take nationwide effect by 2020 will look like, as there are more than 70 pilot projects currently undertaken. These pilots rank from commercial royalty and rewards programs (Sesame Credit) to an Orwellian system, where each action has a predetermined associated score (Rongcheng). In-between, there’s nebulous algorithmic systems that basically act as a Black Box (Honesty Shanghai). This talk, therefore, looks at some of these pilots and their implementation details, and through an agent-based modeling framework, discusses the likely effects of different implementations. In doing so, it shows that most of the systems currently being tested are prone to manipulation by leaders from all levels of government, and that the ostensible goal of allocating scarce resources more efficiently is unlikely to be served by the new system(s).