Boxi C.

Key Skills

Software

Other

Top Subject Matter

Traffic Sign Detection

Environmental Sound Classification

Alzheimer’s Disease Structural MRI Classification

Top Data Types

Image

Audio

Computer Code Programming

Top Task Types

Object Detection

Classification

Segmentation

Freelancer Overview

Traffic-Sign Detection (YOLOv8): Dataset Labeling Contributor. Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Master of Engineering, The University of Sydney (2025). AI-training focus includes data types such as Image, Audio, and Medical and labeling workflows including Object Detection, Classification, and Segmentation.

Labeling Experience

MRI Grey Matter Segmentation and Labeling for AD Classification

OtherSegmentation

I contributed to structural MRI Alzheimer’s Disease classification by segmenting medical images and registering them to atlas maps. My labeling included grey-matter segmentation and feature extraction from multiple regions of interest, enabling the development of reliable classification models. These efforts ensured quality input data for SVM training and performance evaluation. • Segmented grey-matter regions in MRI scans using medical imaging tools. • Registered segmented datasets to corresponding anatomical atlases. • Extracted features from labeled regions for downstream classification tasks. • Worked with FSL FAST and NiftyReg for accurate medical data labeling.

2025 - 2025

Environmental Sound Classification: Audio Data Labeling

OtherAudioClassification

During the Environmental Sound Classification project, I was involved in data preparation and preprocessing of audio clips for use with CNN models. My tasks included data augmentation of audio and organizing correctly-labeled audio events for model training. The labeled audio data were crucial for achieving high validation accuracy and robust inference in the final system. • Labeled and categorized sound events in an environmental audio dataset. • Applied augmentation techniques to enhance audio data variety. • Used Python and PyTorch to preprocess and validate labeling correctness. • Helped create reliable ground truth labels for model evaluation.

2025 - 2025

Traffic-Sign Detection (YOLOv8): Dataset Labeling Contributor

OtherImageObject Detection

I participated in a project training a YOLOv8 detector specifically for multi-class traffic-sign detection using computer vision techniques. I was responsible for dataset labeling and augmentation, which involved preparing annotated image datasets suitable for object detection algorithms. The labeling work contributed directly to the mAP/PR curve evaluation and the improvement of system robustness in challenging image scenarios. • Labeled hundreds of traffic sign images for bounding box object detection. • Performed data augmentation to improve model generalization and accuracy. • Used YOLOv8 and related evaluation tools to verify labeling quality. • Supported error analysis by examining labeled data under different background conditions.

2025 - 2025

Education

Work History