Bachelor Thesis: Automated Process Family Identification and Anomaly Detection in Semiconductor Manufacturing
Research-focused work on identifying process families and detecting anomalies in manufacturing data pipelines.
Computer Science at TU Berlin
I build practical software systems and enjoy working on automation, cloud infrastructure, data processing, and AI-related projects.
I am a B.Sc. Computer Science student at Technische Universitat Berlin and a working student in tech. My interests center around backend systems, cloud deployments, automation, and AI/ML, with a strong preference for building reliable, practical products.
Research-focused work on identifying process families and detecting anomalies in manufacturing data pipelines.
Hands-on work with Kubernetes, structured logging, deployment automation, and practical infrastructure operations.
This website, built with Next.js and Tailwind CSS, designed for fast deployment and iteration on Vercel.
Open to internships, student roles, and software engineering collaborations.