2023 — 2027 (expected)
PhD in Information Systems
University of Zurich — Thesis: "Personalized Adherence Companion: Realizing Human-Centric Persuasion Through Generative Artificial Intelligence"
Academic profile
PhD candidate at the University of Zurich working on persuasive AI: information systems help people stay on track with their treatment, therapy, and study plans.
At a glance
Current Role
Research Assistant & PhD Candidate, Information Management Research Group, University of Zurich
Research Areas
Persuasive GenAI, applied conversational AI, digital health
Education
PhD in Information Systems (expected mid-2027); M.A. Computational Linguistics
Formal training
2023 — 2027 (expected)
University of Zurich — Thesis: "Personalized Adherence Companion: Realizing Human-Centric Persuasion Through Generative Artificial Intelligence"
2018 — 2022
University of Zurich — Thesis: "Cross-lingual Projection of Text Zoning Labels for Job Advertisements"
2012 — 2017
Lanzhou University, China — Thesis: "Assessment of the Quality of Neural Machine Translation (NMT) in German-Chinese Translation"
Appointments
2023 — Present
Information Management Research Group, Department of Informatics, University of Zurich
2025 — Present
Public administration and university career services
2021 — 2022
Clearidium A/S, Denmark
2018
Cromine GmbH, Leipzig, Germany
Community contributions
2027
PERSUASIVE Conference
2025
Elsevier Researcher Academy
2026
Davos Tech Summit
2024 — 2027
Computer-Supported Cooperative Work, University of Zurich
Additional record
LLM applications on hosted APIs (Anthropic, OpenAI, Google) and self-hosted models; agent architecture and stateful prompt orchestration; prompt engineering, RAG, fine-tuning, and evaluation design; AI-assisted development with Claude Code.
Natural language processing, machine learning, and data science; PyTorch, Hugging Face.
Linux administration, Ansible, Nginx, Docker; Azure OpenAI, GPU-backed model serving, on-premises deployment.
Python, Java, Go, R, SQL, Bash, JavaScript; Git.
Design science research, mixed methods (surveys, interviews, user data), experiment design, statistics.
Additional record
Mandarin Chinese — native
English — C2
German — C1 (TestDaF 5-4-4-5)