Johanna C.

Key Skills

Software

No software listed

Top Subject Matter

AI-driven cognitive decline detection via self-figure drawings

clinical assessment

Clinical trial evaluation

Top Data Types

Text

Top Task Types

Emotion Recognition

Data Collection

Freelancer Overview

Co-PI, AI-driven cognitive decline detection project (Ministry of Science, NIS 400K). Brings 11+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Doctor of Philosophy, Ben-Gurion University (2013) and Postdoctoral Fellowship, University of Arizona Cancer Center (2015). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Emotion Recognition.

Labeling Experience

Full Professor, designed and validated DRAWEP (drawing-based emotional processing scale)

OtherTextEmotion Recognition

Developed and validated the Drawing-based Emotional Processing Scale (DRAWEP) involving systematic content annotation and rubric creation for drawing responses. Established a structured labeling scheme to map observed features in drawings to emotional processing constructs. Ensured annotation procedures were suitable for reliable psychometric evaluation and downstream analytic use.• Created a detailed annotation rubric for consistent labeling of drawing content.• Produced a systematic approach for scoring emotional processing from drawings.• Validated the scale to support repeatable labeling and measurement.• Supported integration of the labeling scheme into research workflows for analysis.

2024 - Present

Co-PI, AI-driven cognitive decline detection project (Ministry of Science, NIS 400K)

OtherText

Coordinated evaluation and structured scoring for an AI-driven cognitive decline detection project using self-figure drawings as input data. Oversaw how complex drawing outputs were assessed consistently to support downstream AI use. Worked with research teams to ensure labeling/rubric design aligned with clinical evaluation needs.• Designed and applied structured evaluation rubrics for drawing-based outputs.• Led systematic annotation approaches to make model training data consistent.• Participated in instrument and data-collection methodology used for scoring.• Contributed to research supervision supporting correct labeling workflows.

2022 - Present

Co-PI, NIH RO1 REPAT study (~$961K)

OtherText

As Co-PI on the NIH RO1 REPAT study, designed intervention protocols and evaluation rubrics that functioned as structured scoring guidance for research outputs. Developed data-collection instruments that required consistent rating of outcomes across participants. Helped translate therapeutic constructs into labelable, rubric-based evaluation for analysis and reporting.• Built evaluation rubrics to standardize outcome scoring across study activities.• Designed data-collection instruments supporting consistent labeling of research measures.• Supported structured assessment workflows for intervention evaluation.• Collaborated on monitoring and refinement of evaluation criteria throughout the study period.

2018 - 2022

Education

Work History