Robert Jideofor Chukwuanilo

Key Skills

Software

AWS SageMaker

Data Annotation Tech

Dataloop

Datumbox

Labelbox

OpenCV AI Kit (OAK)

SuperAnnotate

Internal/Proprietary Tooling

Label Studio

Top Subject Matter

Healthcare- Medical Records and Patient Data

Top Data Types

Audio

Image

Medical Dicom

Top Task Types

Data Collection

Evaluation Rating

Polygon

Question Answering

Translation Localization

Freelancer Overview

Presently, I work with Awarri Technologies as a Data Annotator, contributing to the creation of high-quality training datasets that power AI and machine learning solutions across Africa. I specialize in labeling image, text, and medical datasets with precision, ensuring accuracy and consistency that enhance model performance. My expertise spans data quality assurance, annotation tool utilization, and collaboration with cross-functional AI teams to optimize workflow efficiency. I have contributed to several impactful AI projects focused on computer vision, healthcare intelligence, and conversational AI, where I helped refine data pipelines for disease prediction models, chatbot systems, and object recognition tasks relevant to Nigeria’s health and development sectors. With a background in biomedical science, public health, and data science, I bring a multidisciplinary approach to AI data preparation combining technical skill with domain understanding to produce reliable, contextualized datasets that drive real-world innovation in Africa’s tech space.

Labeling Experience

AI-Driven Medical Image and Text Annotation for Cardiovascular Disease Prediction

Label StudioImageBounding BoxEntity Ner Classification

This project focused on curating and annotating cardiovascular health datasets to train AI models for disease prediction in Nigerian primary healthcare contexts. I worked as part of a multidisciplinary data science team at Awarri Technologies to ensure high-quality data labeling for both structured and unstructured health data. Using tools such as Label Studio and Roboflow, I annotated over 10,000 patient records and diagnostic images to identify symptoms, medical entities, and disease indicators. My annotations improved model accuracy and helped develop an AI-powered system capable of predicting cardiovascular risk factors prevalent in sub-Saharan African populations.

This project focused on curating and annotating cardiovascular health datasets to train AI models for disease prediction in Nigerian primary healthcare contexts. I worked as part of a multidisciplinary data science team at Awarri Technologies to ensure high-quality data labeling for both structured and unstructured health data. Using tools such as Label Studio and Roboflow, I annotated over 10,000 patient records and diagnostic images to identify symptoms, medical entities, and disease indicators. My annotations improved model accuracy and helped develop an AI-powered system capable of predicting cardiovascular risk factors prevalent in sub-Saharan African populations.

2025 - 2025

Education

Work History