Kurniawan Yudi Wicaksono

Key Skills

Software

Appen

Clickworker

Telus

Top Subject Matter

No subject matter listed

Top Data Types

Document

Image

Text

Top Task Types

Classification

Data Collection

Evaluation Rating

Prompt Response Writing SFT

Translation Localization

Freelancer Overview

I have hands-on experience in data labeling and AI training data through reputable platforms such as Clickworker, UHRS, Appen, and Telus International. Over time, I’ve worked on diverse projects including search engine evaluation, intent recognition, sentiment analysis, image annotation, and text categorization. These roles have honed my attention to detail, ability to follow complex guidelines, and understanding of how labeled data directly impacts machine learning model performance. My work consistently met quality benchmarks, and I’m adept at adapting to project-specific requirements and shifting priorities. What sets me apart is my ability to combine accuracy with efficiency, even in high-volume tasks. I’ve successfully handled nuanced projects involving natural language understanding, web relevance ratings, and speech/text transcription across different languages and dialects. My familiarity with multiple platforms has helped me build a strong foundation in AI development workflows, and I bring a disciplined, quality-focused approach to every assignment.

Labeling Experience

UHRS

ClickworkerImageData Collection

During my time working on UHRS, I was involved in AI data collection tasks that focused on analyzing and categorizing images. The main goal was to help improve computer vision systems by accurately labeling various objects, scenes, or features within the images. This required a high level of attention to detail, consistency, and an understanding of visual context to ensure the data collected was reliable and useful for training AI models. The experience helped me develop a deeper appreciation for how small labeling decisions can significantly impact machine learning outcomes.

During my time working on UHRS, I was involved in AI data collection tasks that focused on analyzing and categorizing images. The main goal was to help improve computer vision systems by accurately labeling various objects, scenes, or features within the images. This required a high level of attention to detail, consistency, and an understanding of visual context to ensure the data collected was reliable and useful for training AI models. The experience helped me develop a deeper appreciation for how small labeling decisions can significantly impact machine learning outcomes.

2023

Education

Work History