PhD Candidate in Theoretical Physics (i.e. Quantum physics, Atomic and Molecular physics)

In my internship with the Predictive Analytics team at Solandeo, a company involved in Germany's energy transformation, I analyzed renewable energy sources such as solar, wind, and biogas. I applied deep learning to refine next day's energy production predictions, aiding the startup's efforts in improving energy efficiency and sustainability.

I developed models to analyze the interdependencies among key tipping elements in the climate system, such as the Amazon rainforest, AMOC, and Greenland ice sheet. My research explored their potential to trigger cascading tipping events. The results lead to a publication https://doi.org/10.1098/rsos.200599

I interned in the cybersecurity department, focusing on C++ development. I contributed to projects involving end-to-end encryption and authentication schemes. My key responsibility was implementing a Bayesian detection system for flagging suspicious activities based on network protocols, thereby enhancing the overall security posture.

Before embarking on my academic path, I interned in systems biology under Prof. Olaf Wolkenhauer in Rostock, concurrent with my military service. This role capitalized on my prior experience with C++ simulation projects in astrophysics and agent-based modeling. My focus was on modeling colon epithelium cancer cells, utilizing differential equations for biochemical cell cycle processes and agent-based modeling to simulate the biophysical aspects, such as cellular attraction and repulsion. The project involved extensive use of C++ programming, including parallelization techniques.