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Scale AI
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Segmentation
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Text GenerationMedical Doctor and Biomedical Researcher – Multiplexed Imaging & Data Annotation. Brings 12+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal Tooling. Education includes Doctor of Philosophy, University of Oxford (2026); Master of Science, University of Oxford (2020); and Medicine (2017). AI-training focus includes data types such as clinical case training and image and labelling workflows including Segmentation.
Labelling clinical data and creation of bespoke prompts/questions testing and training Medical AI models
Developed computational pipelines for spatial image analysis enabling segmentation and phenotyping of complex cell populations in human thymic tissue. Generated and analyzed a spatial atlas integrating imaging and quantitative analysis of over 9 million cells and more than 50 phenotypes. Designed custom algorithms to quantify spatial organization, cell interactions, and microenvironment structures in complex tissue datasets. • High-throughput validation of computational outputs across >70 imaging experiments • Labeled, classified, and segmented multiplexed tissue images using CODEX/PhenoCycler imaging workflows • Integrated single-cell RNA-seq annotations with spatial proteomic datasets for improved cell-type labeling • Coordinated acquisition, curation, and processing of dataset images from over 30 human tissue samples.
Master of Science, Immunology
Bachelor of Medicine, Bachelor of Surgery, Medicine and Surgery
Spatial Omics Researcher
Immunology Researcher
