For employers

Hire this AI Trainer

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

LoginCreate account
Invite to Job
A
Aimi Alina

Aimi Alina

AI Data Labeler/Researcher – Doctoral Research in Computer Science

Malaysia flagN/A, Malaysia
Intermediate

Key Skills

Software

No software listed

Top Subject Matter

Microalgae Image Analysis
Microalgae Deep Learning Dataset
Fish Vaccination Detection for Aquaculture

Top Data Types

ImageImage
TextText
DocumentDocument

Top Task Types

Object DetectionObject Detection
ClassificationClassification

Freelancer Overview

AI Data Labeler/Researcher – Doctoral Research in Computer Science. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal and Proprietary Tooling. Education includes Doctor of Philosophy, Kyushu Institute of Technology (2024) and Master of Philosophy, University of Technology Malaysia (2023). AI-training focus includes data types such as Image and labeling workflows including Object Detection and Classification.

Intermediate

Labeling Experience

Data Annotator/Researcher – Microalgae Image Dataset Project

ImageClassification
Published and labeled a deep learning dataset (LMFM-12) for microalgae image classification and transfer learning research. Conducted benchmarking with CNN models on the labeled dataset, comparing different initialization strategies. Applied advanced interpretability techniques to evaluate labeled data and model performance. • Labeled images for species identification using CNN architectures. • Performed data curation and label verification for academic use. • Used benchmarking frameworks and Python for model evaluation. • Focused on domain-specific feature representation for microscopic images.

Published and labeled a deep learning dataset (LMFM-12) for microalgae image classification and transfer learning research. Conducted benchmarking with CNN models on the labeled dataset, comparing different initialization strategies. Applied advanced interpretability techniques to evaluate labeled data and model performance. • Labeled images for species identification using CNN architectures. • Performed data curation and label verification for academic use. • Used benchmarking frameworks and Python for model evaluation. • Focused on domain-specific feature representation for microscopic images.

2025 - Present

AI Data Labeler/Researcher – Doctoral Research in Computer Science

ImageObject Detection
Responsible for creating and labeling a unified dataset for automated microalgal detection and classification. Utilized computer vision models such as YOLO and Detectron2 to perform annotations and train AI for species identification. Developed pipelines for multimodal vision-language tasks on microscopic imagery. • Labeled microalgae images for detection, classification, and morphological description. • Designed and executed training datasets for object detection and classification. • Used PyTorch and VSCode for development and annotation processes. • Focused on accuracy and biological relevance in annotation.

Responsible for creating and labeling a unified dataset for automated microalgal detection and classification. Utilized computer vision models such as YOLO and Detectron2 to perform annotations and train AI for species identification. Developed pipelines for multimodal vision-language tasks on microscopic imagery. • Labeled microalgae images for detection, classification, and morphological description. • Designed and executed training datasets for object detection and classification. • Used PyTorch and VSCode for development and annotation processes. • Focused on accuracy and biological relevance in annotation.

2024 - Present

Data Labeler/Developer – Fish Vaccination Detection System

ImageObject Detection
Developed and annotated a real-time fish vaccination detection dataset for aquaculture automation. Used YOLOv8 to label fish positions and vaccination points in video frames captured from live camera streams. Created species and vaccination label classes for system deployment. • Labeled image data for fish position classification and vaccination-point detection. • Designed custom annotation classes for aquaculture-specific applications. • Used YOLOv8 toolkits integrated with Python and embedded devices. • Ensured labeling consistency for real-time automation requirements.

Developed and annotated a real-time fish vaccination detection dataset for aquaculture automation. Used YOLOv8 to label fish positions and vaccination points in video frames captured from live camera streams. Created species and vaccination label classes for system deployment. • Labeled image data for fish position classification and vaccination-point detection. • Designed custom annotation classes for aquaculture-specific applications. • Used YOLOv8 toolkits integrated with Python and embedded devices. • Ensured labeling consistency for real-time automation requirements.

2024 - 2024

Education

U

University of Technology Malaysia

Master of Philosophy, Science

Master of Philosophy
2020 - 2023
U

University of Technology Malaysia

Bachelor of Science, Pure Biology Science

Bachelor of Science
2016 - 2020

Work History

A

Accenture

Quality Control Specialist, Transaction Monitoring

N/A
2024 - 2024