semohr.github.io - Sebastian Mohr - Index

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About Hello and welcome! I am a physicist and data scientist with a passion for web development and visualization. My interests in these fields were sparked during my studies, where I learned the power of effective communication through data-driven visualizations. As a data scientist, I have had the opportunity to work on a variety of projects, including Covid-19 research, where I applied Bayesian inference techniques to gain insights into spreading dynamics. Through my work, I have developed a deep appreci

Here, you can find a comprehensive list of my publications, each one accompanied by a visually appealing graphic and an abstract. In the descriptions, you will also find links to the publications as well as supplementary materials. I take great pride in my work and strive to make my research accessible to anyone who is interested. If you have any questions or would like to learn more about any of my publications, please do not hesitate to contact me.

Large-scale events like the UEFA Euro 2020 football (soccer) championship offer a unique opportunity to quantify the impact of gatherings on the spread of COVID-19, as the number and dates of matches played by participating countries resembles a randomized study. Using Bayesian modeling and the gender imbalance in COVID-19 data, we attribute 840,000 (95% CI: [0.39M, 1.26M]) COVID-19 cases across 12 countries to the championship.

Links to semohr.github.io (2)