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Assessing your cultural and operational fit
lematerial-llm-synthesis
May 28, 2025 – Present
An open-source multi-modal toolbox for extracting structured synthesis procedures and performance data from materials science literature at scale.
View ProjectAlphaZeroFromScratch
January 28, 2023 – September 3, 2023
AlphaZeroFromScratch — GitHub repository
View ProjectAnki-Project
September 22, 2022 – June 12, 2023
We created these Anki-Decks in preparation for our Abitur.
View ProjectGANFTs
January 23, 2022 – March 6, 2022
I trained a Generative Adversarial Network (GAN) using 10.000 images of CryptoPunks. In order to prevent mode collapse, I used the Wasserstein loss function together with gradient penalty.
View ProjectDQpoNg
December 4, 2021 – May 10, 2025
Use the movements of your thumb to play Pong against a pre-trained Double-DQN-Agent. I used Google-Colab for training the pyTorch model and created the Pong environment with Pygame.
View ProjectMNIST-Drawer
June 30, 2021 – March 6, 2022
Streamlit web application that uses trained models (e.g. CNNs) to classify digits drawn by users or generated by a Conditional-WGAN-GP. One can choose between models from Pytorch, Keras, and Scikit-learn.
View ProjectStock-Prediction-UI
March 13, 2021 – October 24, 2021
Stock analyzing program with live data coming from Yahoo finance. I also use fbprophet to predict upcoming prices.
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards personal research and development in advanced AI topics. While this demonstrates initiative and passion, the lack of team-based projects or professional experience makes it difficult to assess collaboration and broader cultural fit within a typical organizational structure. The projects are highly focused on specific technical areas, which might indicate a preference for deep individual work over broader team contributions.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.