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Tiffany Luo

Tiffany Luo

AI Data Labeling Lead – Structured Annotation for Mental Health AI

China flagshenzhen/shanghai, China
$20.00/hrEntry Level

Key Skills

Software

No software listed

Top Subject Matter

Mental Health
Psychology Domain Expertise
Digital Health

Top Data Types

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Top Task Types

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Freelancer Overview

Scientific R&D & AI Training Specialist | Psychological Logic & Structured Evaluation High-potential researcher with an MSc from the University of Glasgow and a published first-author background in cognitive mechanisms. Expert in bridging the gap between complex psychological frameworks (CBT, ACT) and digital AI logic. Proven track record in high-scale data environments, including managing and analyzing mental health datasets for over 600,000 users using R and SPSS. Core Expertise: LLM Benchmarking & Expert Annotation Specialized in 0-1 R&D for AI-enabled assessment tools and mental health applications. Extensive experience in LLM-based personalization, prompt framework design, and structured output evaluation. Sets apart through the ability to translate "systemic principles" into digital tasks, ensuring both scientific validity and risk management in high-stakes behavioral health contexts.

Entry LevelEnglish

Labeling Experience

AI Data Labeling Lead – Structured Annotation for Mental Health AI Personalization

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Led the structured annotation of over 55 mental health tasks to enable AI-powered personalization for a mental health application. Developed a multi-dimensional tagging schema and evaluated the quality of labeled data across several key dimensions. Collaborated with cross-functional teams to refine and optimize the annotation and model training pipeline. • Designed and applied a schema labeling therapy type, task goal, target issues, cognitive load, and difficulty progression • Evaluated annotation quality by testing user profile matching, issue coverage, safety screening, and technical integrity • Worked iteratively through three evaluation cycles, fixing annotation and coverage issues after each review • Supported data enrichment and structured content creation for AI-driven mental health tools

Led the structured annotation of over 55 mental health tasks to enable AI-powered personalization for a mental health application. Developed a multi-dimensional tagging schema and evaluated the quality of labeled data across several key dimensions. Collaborated with cross-functional teams to refine and optimize the annotation and model training pipeline. • Designed and applied a schema labeling therapy type, task goal, target issues, cognitive load, and difficulty progression • Evaluated annotation quality by testing user profile matching, issue coverage, safety screening, and technical integrity • Worked iteratively through three evaluation cycles, fixing annotation and coverage issues after each review • Supported data enrichment and structured content creation for AI-driven mental health tools

2025 - Present

Education

U

University of Glasgow

Master of Science, Psychological Science

Master of Science
2023 - 2024
G

Guangzhou Medical University

Bachelor of Science, Applied Psychology

Bachelor of Science
2019 - 2023

Work History

S

Shanghai Soulmate

Psychology R&D Specialist

Shanghai
2025 - Present