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Herviana Kamaluddin

Herviana Kamaluddin

High Voltage Engineer - AI Applications in Power Systems

INDONESIA flag
Makassar, Indonesia
$35.50/hrEntry LevelOther

Key Skills

Software

Other

Top Subject Matter

No subject matter listed

Top Data Types

ImageImage

Top Label Types

Classification
Computer Programming Coding

Freelancer Overview

I am a High Voltage Engineering researcher with over five years of experience in electrical systems and power asset management, now specializing in AI applications for power asset diagnostics. My work focuses on developing and training deep learning models for eco-friendly Gas-insulated Switchgear (GIS) and Partial Discharge (PD) fault recognition, which has given me hands-on expertise in data annotation, labeling, and preprocessing for machine learning workflows. I am proficient in Python (PyTorch), MATLAB, and COMSOL Multiphysics, and have contributed to industry-funded projects that require meticulous data handling and technical reporting. My background in both academic research and practical engineering allows me to bridge the gap between raw technical data and high-quality AI training datasets, particularly within the electrical engineering and industrial asset management domains.

Entry LevelEnglishIndonesianKorean

Labeling Experience

Research Data Annotator (Signal Processing & Computer Vision)

OtherImageClassificationComputer Programming Coding
Performed domain-specific data annotation for High Voltage Asset Management AI models. * Image Classification: Labeled Phase-Resolved Partial Discharge (PRPD) patterns, distinguishing between Void, Surface, and Corona discharge types. *Signal Denoising: Manually identified and tagged 'noise' vs. 'true signal' in electrical waveform datasets. *Quality Control: Verified Ground Truth data against physical experimental results to ensure training data accuracy."

Performed domain-specific data annotation for High Voltage Asset Management AI models. * Image Classification: Labeled Phase-Resolved Partial Discharge (PRPD) patterns, distinguishing between Void, Surface, and Corona discharge types. *Signal Denoising: Manually identified and tagged 'noise' vs. 'true signal' in electrical waveform datasets. *Quality Control: Verified Ground Truth data against physical experimental results to ensure training data accuracy."

2025

Education

U

Universitas Hasanuddin

Bachelor of Engineering, Electrical Engineering

Bachelor of Engineering
2007 - 2012

Work History

K

Korea National University of Transportation

Researcher

Chungju
2023 - Present
H

Hexa Mulia

Electrical Consultant

Makassar
2020 - 2023