High-throughput native environments, privileged teachers, edge-shaped policies, telemetry, and staged gates.
Tübingen, Germany / Research & practice
An idea is
a starting point.
I build AI systems and the environments they learn in. Working across simulation, autonomous systems, markets, and learning.
Let’s talk01 / The shape of learningHeight = loss
Gradient descent
Selected work
01 — 04Market structure, positioning, macro context, native research tooling, and read-only account context.
Language models
Dialogue research
Testing whether smaller language models can predict what users say next.
QLoRA next-turn prediction with multi-step dialogue rollout evaluation.
Professor-owned sources, enforced unlocks, typed tutor capabilities, and learner-owned work.
Notes & observations
All writing ↗Why Brains and LLMs Both Become Modular
XGBoost and the Map of Machine Learning Approaches
Parameter Golf and Distributed Autoresearch
A little context.
I moved from self-taught builder and backend engineer to research engineer and founder. Today I work through Sunderlabs and HB Capital while studying computer science at Tübingen.
View my CV ↗