Academic Positions

Education

Practical Experience

SS 2026

Business Intelligence (Übung)

Due to my background in psychology and human factors, I bring an interdisciplinary perspective to LLM research in psychiatric diagnostics. My research focuses on the patient perspective of AI implementation, examining how design decisions - such as modality, identity framing, and embodiment - shape patients' willingness to disclose sensitive symptom information and the psychological conditions under which they do so, including factors such as trust and privacy concerns. I am particularly interested in user-centered approaches that address not just whether these systems work technically, but whether they elicit the data quality that clinical decision-making actually requires. Alongside this, I am involved in applied work evaluating LLMs for psychiatric symptom extraction and diagnostic support, with a focus on affective disorders such as major depressive disorder and bipolar disorder, and exploring how such systems might be developed into fully conversational diagnostic agents.

Master’s thesis opportunity: Interface Design for Experimental LLM Assessments