Debanjan Basu

Built and operated Python/Django data platforms, JSON APIs and web-crawling pipelines. Improved distributed workloads 5–10× with Dask/Celery. Implemented LLM application observability and trajectory analysis with Arize Phoenix. Developed GenAI prediction and web-extraction workflows. Deployed via Docker, S3/MinIO and GitLab CI/CD. Delivered an HR platform across five EU/EMEA countries in three months. Recommendation letter available — sehr gut.

Built the Flask and Django backend for web and Android IoT energy products, including REST APIs, PostgreSQL and device-data services. Developed physics-informed heat models and time-series forecasting with TensorFlow/XGBoost. Co-built an IoT pipeline for hundreds of devices with online changepoint detection and OpenStack/Ansible deployment; GDPR-compliant data handling.

Investigated phonon dynamics and thermoelectric transport using classical molecular dynamics. Extended a Fortran/C molecular-dynamics codebase for force-constant extraction, phonon band structures and thermal transport. Published in Physica Status Solidi A (DOI: 10.1002/pssa.201532488). Tutored ab-initio electronic-structure methods. Supervisor: Prof. Peter E. Blöchl.