Über uns

Simon Deussen

Founder & Managing Partner

Simon founded control-f and runs it as Managing Partner and Lead Data Architect. A B.Sc. in media informatics at the Hochschule der Medien Stuttgart, with a bachelor thesis written at Daimler TSS on converting screen designs into HTML and CSS with deep learning, was followed by three years at inovex, first as a machine learning engineer and then, alongside a master's in autonomous systems at the Hochschule Bonn-Rhein-Sieg, in data management and analytics. That is the ground control-f is built on: turning disordered company data into decisions that can be trusted, predictive maintenance that catches plant and machine failures before they happen, and data pipelines that still run two years after handover. Pragmatic solutions rather than AI that stays in the slide deck.

Daniel Tremer

Managing Partner

Daniel joined control-f as Managing Partner, bringing over a decade of experience in data science and machine learning to the company's work with industrial enterprise clients. His background includes several years in the automotive industry across research and development, IT, and infrastructure roles, as well as running his own AI and data analytics practice before joining control-f. His interests span the full spectrum of applied AI, from large language models and generative systems to production data engineering, and he leads control-f's work building practical, cutting-edge AI solutions for enterprise clients.

Piet Brömmel

Data Engineer

Piet hat einen Hintergrund in Machine Learning und Data Engineering. Er hat einen Master in Informatik von der TU Dortmund und hat zuvor als Data Scientist bei Fraunhofer mit Robotern und Computer Vision gearbeitet. Seine Interessen umfassen Softwareentwicklung, LLMs und alles drumherum, Wandern und algorithmische Kunst.

Henry Beiker

Data Engineer

Henry brings software development and AI testing to control-f's data engineering work. A B.Sc. and then a master's in computer science at the Humboldt-Universität zu Berlin ran alongside three and a half years of development work. At Howto Health that has meant leading software and data engineering projects, APIs for data processing and integration, and an in-house task planning tool built against requirements taken straight from clients. In a research team at Fraunhofer FOKUS it has meant a simulation environment in Unreal Engine for testing object detection models, a test framework for autonomous robots on train tracks, and the evaluation workflows around both. That is the same question the master's thesis takes up, improving object detection by simulating the scenarios that provoke false negatives. The stack is Python, SQL and JavaScript with Django, FastAPI and Flask, React in front and PostgreSQL underneath.

Robin Marzucca

Data Engineer

Robin brings a background in theoretical particle physics to control-f's data engineering work. He completed his PhD in quantum field theory and spent several years as a postdoctoral researcher at the University of Zurich's Physik-Institut, working on scattering amplitudes and precision calculations in quantum field theory, alongside earlier research stints at UCLouvain and Durham University's Institute for Particle Physics Phenomenology.

Marie Ernø-Møller

Data Engineer

Marie brings a background in theoretical physics to control-f's data engineering work. An MSc in quantum physics from the University of Copenhagen, with a thesis on double-copy amplitudes and their applications in general relativity, led to gravitational-wave research at Humboldt-Universität zu Berlin, where quantum field theory and effective field theory methods were applied to black hole mergers. That research training now sits alongside a deliberate move into machine learning and full-stack engineering: an MLOps bootcamp, containerised data pipelines built with Airflow, MLflow, Grafana and Prometheus, backend work in FastAPI and PostgreSQL, and a self-built mobile application whose emphasis is relational schema design and time-series metrics.

Birk Burghardt

Data Engineer

Birk brings a computer science background and several years of applied data science to control-f's data engineering work. After a B.Sc. in computer science at Humboldt-Universität zu Berlin, including contract work for the university's Digital History group on web scraping and the image classification of heraldic material, the path led through predictive modelling on laboratory diagnostics data at a digital health company to a Data Science Expert role at Lyreco Deutschland. There the work covered Power BI data models and reporting, ETL processes and workflow automation in Python, and machine learning pipelines for churn analysis, customer lifetime value and cross-selling, alongside the backend of an internal assortment platform.