Hey there, my name is Daniel,
a CS master's student focused on deep learning for the simulation of physical systems — and a student AI & Data Scientist at Statista+.
About me
Full CV## Education
2024 — today
M.Sc. Computer Science · AI & Data Science
HAW Hamburg
- GPA 1.0
- Neural ODEs/PDEs & operators, transformers, VAEs, diffusion & flow matching
02/2026 — 07/2026
Postgraduate Exchange Semester Scholarship
UNSW Sydney
- Led a five-student NLP research project on LLM context faithfulness — High Distinction
2020 — 2024
B.Sc. Media Computer Science
University of Flensburg
- Programming, databases, artificial neural networks
## Experience
2025 — today
Working Student · AI & Data Science
Statista
- RAG systems, data automation pipelines, scraping & structuring
2021 — 2025
Working Student · Fullstack Development
Jung von Matt TECH, SOFTSTACK, Events United
- 4+ years of fullstack engineering — projects for dfb.de, bmw.com and more
## Honors
Deutschlandstipendium
Scholarship for Gifted and High-Achieving Students
Latest Posts
All posts
Neural Networks as Wave Equation Approximators
A deep dive into the wave equation, its reformulation for neural network approximation, and the challenges of learning dynamics with finite speed.
Deriving the Wave Equation
A step-by-step derivation of the wave equation from first principles, exploring how tension and mass density lead to wave propagation with finite speed.
Partial Differential Equations and Neural PDEs
From the mathematics of change to neural networks that learn dynamics — understanding PDEs, numerical solvers, and how modern generative models are PDEs in disguise.
Ordinary Differential Equations and Neural ODEs
From the mathematics of change to neural networks that learn dynamics — understanding ODEs, numerical solvers, and how modern generative models are ODEs in disguise.
The Mathematics Behind Flow and Diffusion Models
A deep dive into the mathematical foundations of flow-based models and diffusion processes in deep learning.
Context-Parametric Inversion
A controlled faithfulness study on how QASPER fine-tuning affects context reliance across a RAG pipeline for NLP research papers.
Recent Projects
All projectsDual MIDI Transformer
A MIDI Event based transformer architecture, utilizing two seperate transformers operating on the global MIDI events and local event parameters.
Basic MIDI Transformer
A basic transformer architecture for MIDI generation, utilizing a single decoder to enable faster training and inference speed.
MoodWave
A real-time streaming pipeline correlating German news sentiment (GDELT) with Spotify Top 200 musical features, using Kafka and Spark Streaming for dual-stream aggregation.