Alphonse Mudoh

Key Skills

Software

Label Studio

AWS SageMaker

Clickworker

Data Annotation Tech

Mercor

Micro1

Telus

Top Subject Matter

Healthcare - Medical Records and Patient Data

E-commerce

Computer Technologies

Top Data Types

Video

Image

Top Label Types

Text Summarization

Object Detection

Classification

Segmentation

Freelancer Overview

I am an AI data labeling and NLP annotation specialist with over 15 years of experience designing and executing large-scale multilingual data annotation projects. My expertise spans text classification, named entity recognition, sentiment and intent labeling, and semantic similarity analysis, with a strong focus on quality assurance and ethical AI practices. I have led the creation of annotation guidelines, taxonomies, and QA frameworks for diverse datasets in English, Swahili, and French, contributing to the development and fine-tuning of advanced transformer-based models. My background includes building open-source literary corpora, conducting bias detection, and evaluating AI-generated outputs for accuracy and fairness. I am proficient with tools such as Label Studio, Hugging Face, Python, and GCP, and am passionate about improving model performance through meticulous data labeling and innovative annotation methodologies.

Labeling Experience

Senior Research Scientist – Language & AI

Label StudioTextClassification

Designed and supervised multilingual text annotation workflows for NLP model training at Global AI Research Lab. Led dataset labeling initiatives for classification, summarization, and semantic search system development. Developed annotation taxonomies, created guidelines, and ensured data quality across diverse projects. • Conducted quality control audits to ensure inter-annotator agreement. • Labeled datasets to fine-tune transformer-based AI models. • Evaluated AI-generated responses for accuracy and bias. • Utilized tools such as Python, Hugging Face, and Label Studio for project execution.

Designed and supervised multilingual text annotation workflows for NLP model training at Global AI Research Lab. Led dataset labeling initiatives for classification, summarization, and semantic search system development. Developed annotation taxonomies, created guidelines, and ensured data quality across diverse projects. • Conducted quality control audits to ensure inter-annotator agreement. • Labeled datasets to fine-tune transformer-based AI models. • Evaluated AI-generated responses for accuracy and bias. • Utilized tools such as Python, Hugging Face, and Label Studio for project execution.

2020

Associate Professor – Digital Humanities & AI

TextClassification

Led corpus digitization and metadata annotation projects at the University of Nairobi. Supervised research projects involving structured linguistic tagging and annotation framework development. Trained postgraduate students in text labeling and QA methodologies. • Developed annotation frameworks for literary and linguistic corpora. • Managed metadata tagging for large text datasets. • Oversaw dataset preparation for AI research and training. • Ensured rigorous QA processes in all annotation tasks.

Led corpus digitization and metadata annotation projects at the University of Nairobi. Supervised research projects involving structured linguistic tagging and annotation framework development. Trained postgraduate students in text labeling and QA methodologies. • Developed annotation frameworks for literary and linguistic corpora. • Managed metadata tagging for large text datasets. • Oversaw dataset preparation for AI research and training. • Ensured rigorous QA processes in all annotation tasks.

2016 - 2020

Education

Work History