Philipp Petermeier 🔍
Philipp Petermeier

Seeker

About Me

I have a B.S. in Business Information Systems with a focus on Data Science and Data Engineering specialising in Reinforcement Learning.
I’m interested in data and models related to energy systems and the green transition, bioinformatics and materials science.
In my spare time I am amateurishly dabbling in climate change and policy as well as macro- and political economy, though not exclusively.

What I experienced so far

I spent a lot of time studying humanities with a focus on philosophy, only to change course and start my B.S. to learn how to build complex things with a clear purpose using software.

This part of my education is not listed here, mainly because I find it difficult to explain what concrete practical skills I have acquired during my time there.

At the same time, I’m sure that my experiences have structured many of my cognitive processes and views in a fundamental way, and have made me a much better software engineer, developer, modeller, team member and human being.

If you are curious about this side of me, I would encourage you to visit the About this place-Section of my substack. How I think about things I find interesting can be seen in the posts themselves. I hope you like it.

Experience

  1. Intern and Working Student

    Developed a scientific Python package to implement a reinforcement learning environment for electricity trading. This included:

    • Design and implementation
    • Benchmarking and adapting the development process to optimise runtime performance
    • Modelling the appropriate data structure
    • Setting up the required MongoDB
    • Designing, building and deploying the ETL-Pipeline
    • Orchestrate initial experiments using Ray on an on-premises HPC cluster to ensure runtime performance
    • Participate in the writing of a paper documenting initial results

Education

  1. BA in Business Information Systems

    Technische Hochschule Mittelhessen
    THM_Logo_RGB

    Final Grade: 2.2 (78%)
    210 CP (7 Semesters)

    Thesis: “A Deep Reinforcement Learning Environment for the Limit Orderbook Intraday Electricity Market: Development and efficient Implementation”
    Grade: 1,2 (92%) \

    Winner the Karl-Heinz Lust Innovation Award 2024 in the area Digital Economy / Industry 4.0 / AI Awarded by the foundation for applied Research, Innovation and Transfer Mittelhessen

    Elective modules:

    • Introduction to Machine Learning
    • Predictive Analytics with Python
    • Introduction to Decision and Game Theory
    • Introduction to Julia
What I learned doing it
Python
Python
numpy
pandas
scikit-learn
keras
matplotlib & Seaborn
Jupyter Notebooks
Other
SQL
MongoDB
R
Julia
Git & CI/CD
Markdown & LaTeX
UML & Architecture
How I can interact with you
100%
🇩🇪 German
90%
🇬🇧 English