Kimberly B.

Key Skills

Software

Other

Top Subject Matter

Materials science

nuclear fuel materials

microscopy (SEM)

Top Data Types

Image

Top Task Types

Segmentation

Bounding Box

Freelancer Overview

Physics Doctoral Student / Graduate Research Assistant — annotated SEM microscopy datasets for ML-based materials defect. Brings 7+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Doctor of Philosophy, The University of Texas at San Antonio (UTSA) (2031) and Bachelor of Science, The University of Texas at San Antonio (UTSA) (2025). AI-training focus includes data types such as Image and labeling workflows including Segmentation and Bounding Box.

Labeling Experience

Physics Doctoral Student / Graduate Research Assistant — annotated SEM microscopy datasets for ML-based materials defect analysis

ImageSegmentation

Labeled and annotated thousands of microscopy images to train machine learning models for materials science. Built AI-based image annotation tools to automate measurement and classification of materials defects in SEM imagery. Implemented quality control procedures to ensure accuracy and consistency of research data annotations. • Annotated microscopy images for model training • Automated measurement and classification workflows • Ensured guideline adherence via quality control • Supported nuclear fuel materials analysis with labeled datasets

2026 - Present

Freelance Data Annotation Specialist (Self-Employed) — image and text labeling for AI/ML clients

OtherImageBounding Box

Performed image annotation for computer vision projects, including bounding boxes, polygon segmentation, and keypoint labeling. Delivered text classification and sentiment analysis labels for natural language processing applications. Maintained a 98%+ accuracy rate by following detailed annotation guidelines and quality expectations. • Bounding box, polygon segmentation, and keypoint labeling • Text classification and sentiment analysis labeling • Sustained 98%+ accuracy through guideline adherence • Completed 1,000+ tasks monthly while meeting deadlines

2024 - Present

CONNECT Undergraduate Researcher — nuclear materials image annotation for AI image analysis

ImageSegmentation

Contributed to research on advanced nuclear fuel materials requiring substantial image data annotation and labeling. Gained hands-on experience working with scanning electron microscopy data and materials characterization workflows to inform labeling for AI analysis. Supported the development of foundational AI-based image analysis tools by combining annotation expertise with machine learning context. • Annotated image data for nuclear materials research • Worked with SEM and materials characterization data • Informed AI-based image analysis tool development • Applied labeling to support ML-ready datasets

2025 - 2026

Education

Work History