Pouyan Alizadeh Golbaghi

Designed and shipped an AI-supported ecosystem combining a serious game and LLM-based clinical interview for pediatric chronic conditions; authored conversation flows and UX artifacts to improve safety and reproducibility. Evaluated model outputs, documented failure cases, and translated testing insights into product changes to increase reliability.

Evaluated and improved AI outputs using rubric-based reviews, authored labeling guidelines and prompt patterns, and visualized error trends to inform UX guardrails and experiment acceptance criteria. Identified recurring failure modes and recommended human-centered mitigations.

Planned and conducted human-subject studies in pain neurophysiology, handled ethics and recruitment, and analyzed multimodal data with Python/MATLAB/SPSS to generate actionable insights for researchers and clinicians. Produced clear figures and dashboards to communicate findings.

Consolidated complex datasets and established reproducible analysis workflows to clarify intervention outcomes, partnering with therapists to define metrics and translate evidence into practical recommendations for non-technical stakeholders.

Coordinated multi-site research translating psychological constructs into measurable tasks and producing publication-ready visuals and tables to support transparent interpretation of results.

Modeled and visualized complex urban and environmental datasets and designed decision-support visuals to help stakeholders evaluate constraints and trade-offs.