Hollyleann C.

Key Skills

Software

Other

Appen

Top Subject Matter

Physics and scientific/technical reasoning

Optics Domain Expertise

Electromagnetism Domain Expertise

Top Data Types

Text

Document

Top Task Types

Question Answering

Data Collection

Freelancer Overview

AI Data Labeling & Evaluation Specialist (Project-Based). Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Master of Science, University of California, Berkeley (2021) and Bachelor of Science, University of California, Berkeley (2019). AI-training focus includes data types such as Text and Document and labeling workflows including Evaluation, Rating, and Question Answering.

Labeling Experience

Independent Physics Consultant (AI Projects)

OtherTextQuestion Answering

Created advanced physics problems used for AI benchmarking and evaluation pipelines, with verification of AI-generated solutions and reasoning chains. Developed datasets requiring deep reasoning in optics, electromagnetism, and mechanics to support robust model assessment. Collaborated with AI teams to refine problem difficulty and strengthen evaluation coverage.• Authored and structured physics benchmark questions and reasoning expectations.• Verified correctness of model solutions and multi-step reasoning chains.• Curated domain-specific datasets focused on deep technical reasoning.• Iterated with teams to tune difficulty and improve robustness of evaluation data.

2022 - Present

AI Data Labeling & Evaluation Specialist (Project-Based)

OtherText

Evaluated AI-generated responses for correctness in physics and technical domains while ensuring accuracy and consistency across training datasets. Created structured annotations for multi-step reasoning problems spanning scientific disciplines and validated reasoning quality. Identified model weaknesses and provided feedback to improve performance and alignment with labeling standards.• Reviewed and labeled complex dataset instances for accuracy and reasoning fidelity.• Assessed outputs against physics and technical correctness criteria.• Built multi-step annotation structures for advanced scientific reasoning tasks.• Performed quality control checks to maintain high-quality training data.

2022 - Present

Research Assistant – Optics & Photonics Lab

OtherDocumentData Collection

Supported research in optics and photonics by generating structured datasets from experimental results for subsequent analysis and modeling. Assisted with documenting research outputs to improve reproducibility and clarity of experimental data usage. Contributed data preparation workflows that feed downstream computational and AI-related evaluation activities.• Produced structured datasets derived from optical system experiments.• Organized experimental outputs for downstream analysis and modeling.• Helped ensure reproducibility through clear documentation and formatting.• Supported computational modeling inputs using experiment-driven data.

2020 - 2022

Education

Work History