Aadarsh Kushwaha

Key Skills

Software

Label Studio

Top Subject Matter

No subject matter listed

Top Data Types

Text

Top Task Types

Entity (NER) Classification

Relationship

Evaluation/Rating

Freelancer Overview

I am a detail-oriented engineering student with hands-on experience in data analysis and simulation, including projects involving CFD, FEA, and thermodynamic modeling using tools like ANSYS, MATLAB, and Python. My work has required careful data preparation, annotation, and validation to ensure accurate results, and I am comfortable handling complex datasets and extracting meaningful patterns. I have a strong foundation in technical documentation, reproducible code, and teamwork, and I am eager to apply my analytical skills to data labeling and AI training data roles, especially in domains related to computer vision, engineering, or scientific data.

Labeling Experience

Medical Named Entity Recognition for Clinical Document Analysis

Label StudioTextEntity Ner ClassificationRelationship

I contributed to a large-scale data labeling project focused on improving information extraction from clinical documents, such as patient notes and medical research articles. My main tasks included annotating and classifying medical entities such as diseases, procedures, medications, anatomy, and patient attributes. In addition, I reviewed relationships between these entities (e.g., medication prescribed for a specific condition) and performed quality assurance to ensure accuracy and consistency across annotations. This work helped train advanced medical NLP models, supporting applications such as automated clinical record search, decision support, and research data mining.

I contributed to a large-scale data labeling project focused on improving information extraction from clinical documents, such as patient notes and medical research articles. My main tasks included annotating and classifying medical entities such as diseases, procedures, medications, anatomy, and patient attributes. In addition, I reviewed relationships between these entities (e.g., medication prescribed for a specific condition) and performed quality assurance to ensure accuracy and consistency across annotations. This work helped train advanced medical NLP models, supporting applications such as automated clinical record search, decision support, and research data mining.

2023 - 2023

Education

Work History