For employers

Hire this AI Trainer

Sign in or create an account to invite AI Trainers to your job.

LoginCreate account
Invite to Job
W
Wendell Da Luz S.

Wendell Da Luz S.

Researcher in Modeling and AI / Data Annotation for Forensic Radiology Images

Brazil flagSão Paulo, Brazil
ExpertOther

Key Skills

Software

Other

Top Subject Matter

Forensic Radiology and Medical Imaging
Legal Radiology and Forensic Evidence
Advanced Imaging and Computational Analysis (Forensics, Veterinary, Medical)

Top Data Types

ImageImage
TextText
DocumentDocument

Top Task Types

SegmentationSegmentation
ClassificationClassification

Freelancer Overview

Researcher in Modeling and AI / Data Annotation for Forensic Radiology Images. Brings 11+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Master of Laws, Universidade de Santo Amaro (2024) and Professional Master of Science, Instituto de Pesquisas Energéticas e Nucleares (2025). AI-training focus includes data types such as Medical and DICOM and labeling workflows including Segmentation and Classification.

Expert

Labeling Experience

Peer Reviewer, Ad Hoc - Advanced Image Labeling and Annotation Methods

OtherSegmentation
Participated as an ad hoc peer reviewer for advanced image labeling in computational tissue analysis studies. Focused on ensuring methodological accuracy and scientific rigor in annotated DICOM and 3D imaging datasets. Validated and commented on the robustness of AI and computation-driven annotation protocols submitted to scientific journals. • Reviewed segmentation workflows and output data quality. • Assessed volumetric modeling methods for simulated biological analysis. • Critiqued consistency and labeling standards across research submissions. • Contributed to the advancement of best practices in forensic and advanced imaging research.

Participated as an ad hoc peer reviewer for advanced image labeling in computational tissue analysis studies. Focused on ensuring methodological accuracy and scientific rigor in annotated DICOM and 3D imaging datasets. Validated and commented on the robustness of AI and computation-driven annotation protocols submitted to scientific journals. • Reviewed segmentation workflows and output data quality. • Assessed volumetric modeling methods for simulated biological analysis. • Critiqued consistency and labeling standards across research submissions. • Contributed to the advancement of best practices in forensic and advanced imaging research.

2025 - Present

Researcher in Modeling and AI / Data Annotation for Forensic Radiology Images

Segmentation
Contributed to segmentation and quantitative analysis of medical images for AI model training in radiology and forensic applications. Participated in the annotation of DICOM images using digital processing and feature extraction for machine learning. Focused on modeling physical and statistical dynamics within heterogeneous biological media through radiological datasets. • Utilized segmentation and measurement of anatomical features in CT and MRI. • Supported deep learning model development in forensic casework involving post-mortem imaging. • Labeled and annotated image data to correlate radiological findings with legal and forensic interpretation. • Ensured consistency and scientific rigor in the labeling process for AI research.

Contributed to segmentation and quantitative analysis of medical images for AI model training in radiology and forensic applications. Participated in the annotation of DICOM images using digital processing and feature extraction for machine learning. Focused on modeling physical and statistical dynamics within heterogeneous biological media through radiological datasets. • Utilized segmentation and measurement of anatomical features in CT and MRI. • Supported deep learning model development in forensic casework involving post-mortem imaging. • Labeled and annotated image data to correlate radiological findings with legal and forensic interpretation. • Ensured consistency and scientific rigor in the labeling process for AI research.

2025 - Present

Data Labeler for Legal and Forensic Radiology Research

Classification
Annotated and classified radiological images for legal and forensic research projects using structured methods. Applied manual and semi-automated annotation techniques to label cases involving anthropological, traumatological, and legal analysis. Labeled and organized data for studies on the applicability of virtual autopsy (virtopsy) and radiological evidence in medical-legal contexts. • Processed and structured DICOM datasets for forensic and bioethics research. • Classified radiological events for anthropological and traumatological study. • Assisted in developing category schemas for AI models handling forensic imaging cases. • Adhered to standards for defensibility and traceability of image labels in legal contexts.

Annotated and classified radiological images for legal and forensic research projects using structured methods. Applied manual and semi-automated annotation techniques to label cases involving anthropological, traumatological, and legal analysis. Labeled and organized data for studies on the applicability of virtual autopsy (virtopsy) and radiological evidence in medical-legal contexts. • Processed and structured DICOM datasets for forensic and bioethics research. • Classified radiological events for anthropological and traumatological study. • Assisted in developing category schemas for AI models handling forensic imaging cases. • Adhered to standards for defensibility and traceability of image labels in legal contexts.

2022 - 2024

Education

U

Universidade de Santo Amaro

Master of Laws, Medical Law

Master of Laws
2022 - 2024
U

Universidade Nove de Julho

Bachelor of Technology, Radiology Technology

Bachelor of Technology
2019 - 2021

Work History

O

Open Veterinary Journal

Peer Reviewer (Ad Hoc)

N/A
2025 - Present
O

Ordem dos Especialista em Radiologia do Brasil

Coordinator (Volunteer)

São Paulo
2025 - Present