Harikrishnan

Key Skills

Software

iMerit

Top Subject Matter

No subject matter listed

Top Data Types

3D Sensor

Image

Top Label Types

Bounding Box

Classification

Cuboid

Object Detection

Point Key Point

Polygon

Polyline

Segmentation

Tracking

Freelancer Overview

I am a detail-oriented data annotation specialist with over 2.5 years of experience working on 2D/3D labeling, LiDAR point-cloud annotation, and autonomous driving projects. My expertise spans across ADAS, geospatial mapping, and medical AI domains, where I have consistently delivered high-quality, accurate datasets for model training. I am skilled in using tools such as CVAT, AWS SageMaker, KOGNIC, and various LiDAR point cloud editors, and I have a proven track record of maintaining 97–98% accuracy on large-scale annotation tasks. My experience includes enforcing strict QA standards, conducting SQC-based quality checks, and collaborating with annotation and review teams to ensure all deliverables exceed client expectations. I am passionate about contributing to robust AI training pipelines and advancing the quality of data for machine learning applications.

Labeling Experience

Torc Robatics Project

Imerit3D SensorCuboidClassification

Worked on Advanced Driver Assistance Systems (ADAS) projects involving 2D and 3D object annotation for autonomous driving applications. Specialized in LiDAR-based point cloud annotation, accurately labeling vehicles, pedestrians, lanes, and road infrastructure using Imerit Point Cloud Tool.Handled end-to-end data quality assurance, performing detailed SQC-based quality checks to ensure high accuracy, consistency, and compliance with strict project guidelines. Collaborated closely with annotation and review teams to maintain production standards and meet client expectations.Processed 1.5–2 lakh frames per month across 2D and 3D datasets, consistently achieving 97–98% accuracy, contributing high-quality annotated data for reliable model training and performance improvement.

Worked on Advanced Driver Assistance Systems (ADAS) projects involving 2D and 3D object annotation for autonomous driving applications. Specialized in LiDAR-based point cloud annotation, accurately labeling vehicles, pedestrians, lanes, and road infrastructure using Imerit Point Cloud Tool.Handled end-to-end data quality assurance, performing detailed SQC-based quality checks to ensure high accuracy, consistency, and compliance with strict project guidelines. Collaborated closely with annotation and review teams to maintain production standards and meet client expectations.Processed 1.5–2 lakh frames per month across 2D and 3D datasets, consistently achieving 97–98% accuracy, contributing high-quality annotated data for reliable model training and performance improvement.

2024 - 2025

Education

Work History