I am a researcher with a strong technical and statistical background pursuing a PhD in computer science and computational biology at the Center for Computational Molecular Biology at Brown University. I am a member of the Crawford Lab and the Weinreich Lab. My research focuses on developing statistical methods and machine learning algorithms to study the genetic architecture of complex traits and how nonlinear interactions between multiple genes and between genes and the environment shape evolution.

Prior to returning to academic research, I worked as software consultant. My experience as a software consultant at TNG Technology Consulting GmbH has honed my practical skills in software development, automation, and cloud-based infrastructure. Working in a project that introduced DevOps and cloud technologies into the software projects of a publicly traded corporation, I learned about how to deliver a software product. These skills became an integral part of how I conduct my research. To deliver reproducible, tested, and accessible research, I publish the statistical methods I develop not only as open-access scientific articles but also as open-source software packages. Proficient in Python, R and C++, I thrive in projects requiring mathematical and technical expertise and creative problem-solving.

At the beginning of my academic training, I obtained a MS in physics. During that time, I gradually discovered my passion for statistical modeling of biological processes (e.g. through studying advanced statistical physics, pattern formation and non-linear dynamics, and stochastic processes in biology). While the domain-specific knowledge from my studies of physics and the origins of life only partly transferred to my doctoral research, these studies endowed me with a profound understanding of mathematical modeling and a complementary first principles view on biological processes.

When I am not working, I enjoy running, traveling, and reading.