Christoph Anders

Unlike traditional consultants who treat documentation as an afterthought, I have a "Compliance-by-Design" approach. I architect your technical backend to meet MDR and ISO requirements during development, offering both strategic guidance and hands-on engineering support.

I bridge the methodological rigor of elite medical research (experienced at Charité and University Hospital Bonn) with deep IT engineering expertise. Having personally initiated, executed, and published clinical AI studies in prestigious journals such as Nature Scientific Data and having been awarded the eTELEMED 2024 Best Paper award, I conceptualize, develop, and document complex ML models and automated pipelines to pass Notified Body audits.

I learned that valuable health insights are rarely found in "clean" laboratory datasets alone; they exist in the noise of daily life. As a PhD Candidate at the Hasso Plattner Institute (Dissertation submitted), I have spent five years navigating this complexity—from driving five self-initiated ethics applications to analyzing 500+ hours of real-world wearable data. My focus was on transforming high-dimensional biosignals (EEG, PPG, EDA) into validated digital biomarkers that remain robust in uncontrolled, naturalistic environments.

I am a Python and Backend specialist building production-ready, containerized pipelines (e.g., with Docker/Kubernetes) for the next generation of digital health tools. Whether optimizing deep learning models (e.g., CNNs, LSTMs, GANs) to outperform benchmarks or discussing explainable AI with medical doctors, I prioritize building transparent, evidence-based systems that can be trusted.

By merging high-level research with production-grade engineering, I minimize the risk of certification delays and strategically secure your market entry. Let's turn your raw sensor data into scalable, actionable, and audit-ready health insights.

I have a deep passion to make this world a better place, and I'm based in both Germany and Chile.