In October of 2022 I joined Bloomberg as a Software Engineer! I am working on C++ infrastructure in the context of financial analytics.

In 2022, I interned at Google as an SRE intern! Here's a brief summary of what I did:

• Developed an internal log filtering tool using Go and TypeScript for Google Cloud Compute Engine, which is used during outages.
• Reduced query response time by 40% for all queries and by an additional 32% for specific queries by optimizing the SQL queries.
• Reduced query response time by 28% for certain teams by moving critical computations from SQL to Go and developing a typing system.
• Took ownership of the entire project's front- and backend, assisted other engineers with bug resolution.
• Improved usability of the tool by implementing autocompletion and improving the documentation.

In 2022, I interned at AWS Dublin as an SDE intern! Here's a brief summary of what I did:

• Developed an internal auditing tool using AWS, MySQL, and Django for AWS CloudWatch, which is used by hundreds of teams across AWS.
• Reduced the duration of auditing meetings by multiple hours each week, saving hundreds of engineering hours per year.
• Took ownership for the entire development lifecycle of the project, spanning multiple software packages.
• Communicated with multiple teams, located across the world.
• Raised the test coverage of a core package from 33% to 90%.

Improving the German AI student landscape!

In 2019, I was a national finalist at the German National Competition for AI, which saw over 2500 participants that year but only invited 4 teams to the finale. In 2020, I joined the organizational team and have been volunteering for the competition ever since. I have contributed to many aspects of the organization, but here's a brief summary of the key points:

• Developed several extensive technical courses for high school students covering various machine learning and programming topics with thousands of attendants.
• Organized and coordinated our annual machine learning hackathon with over 100 participants.
• Developed an interactive browser-based Python plotting console using Pyodide and React.
• Initiated and lead the development of a new AI challenge for students which do not feel ready yet to participate in the competition.
• Was member of the initial and national jury.
• Wrote several short articles for the course platform and filmed videos for the social media channels of the competition.

Helping people become better at machine learning!

Since high school, I have worked as a research assistant at the Fraunhofer Institute of Technological and Economical Mathematics (ITWM).
I have worked in the optimization department, mainly focusing on developing ml methods to replace costly physics-based simulations. Here's a summary of my work:

• Implemented machine learning to predict quality of cups before manufacturing to replace costly physics-based simulations.
• Decreased model error by 30% by implementing machine learning models in Python with TensorFlow, PyTorch, and scikit-learn.
• Developed data processing, cleaning, and visualization pipelines for handling datasets of 50+GB in size containing millions of entries.
• Increased explainability of neural networks for classification and regression-based tasks by creating visualizations with Matplotlib.

I graduated from the RPTU with a degree in CS, doing so at the very top of the class. I was
For my outstanding academic achievements and my volunteering activities, I have been awarded the
three distinct, highly-renowned scholarships.
During my undergraduate studies, I have specialized myself in intelligent systems, taking several courses
in the mathematical foundations as well as shallow and deep machine learning and collaborative intelligence.
I have also taken several courses of the software engineering specialization, including functional programming.