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Mohit Gurav

Mohit Gurav

Customer Support Specialist - Financial Services

India flagkarwar, India
$10.00/hrEntry LevelInternal Proprietary Tooling

Key Skills

Software

Internal/Proprietary Tooling

Top Subject Matter

No subject matter listed

Top Data Types

ImageImage

Top Task Types

Bounding BoxBounding Box
MappingMapping

Freelancer Overview

I am a computer science engineering student with hands-on experience in data annotation and data analysis, skilled in Python, SQL, and MS Excel. My background includes working in BPO operations where I analyzed and managed client data, as well as contributing to IoT projects that required precise data handling and annotation for solution development. I have also built projects involving data visualization and online management systems, which strengthened my attention to detail and understanding of structured data. I am eager to apply my technical and analytical skills to support high-quality AI training data and data labeling initiatives.

Entry LevelHindiKannadaEnglish

Labeling Experience

qure.ai

Internal Proprietary ToolingImageBounding BoxMapping
This project involved large-scale medical image annotation to support the development of AI models for automated bone fracture detection. A total of 200,000 (2 lakh) healthcare imaging records were annotated with high precision, focusing on identifying the presence of bone fractures and accurately marking the exact fracture regions. The dataset consisted of radiological images usually X-rays covering multiple anatomical regions. Each image was reviewed by trained annotators as well as Orthopedists following strict medical annotation guidelines. Fractures were classified and localized using bounding boxes and/or polygon annotations to highlight the affected bone area. Special attention was given to annotation consistency, anatomical accuracy, and edge-case handling, including hairline fractures and complex fracture patterns.

This project involved large-scale medical image annotation to support the development of AI models for automated bone fracture detection. A total of 200,000 (2 lakh) healthcare imaging records were annotated with high precision, focusing on identifying the presence of bone fractures and accurately marking the exact fracture regions. The dataset consisted of radiological images usually X-rays covering multiple anatomical regions. Each image was reviewed by trained annotators as well as Orthopedists following strict medical annotation guidelines. Fractures were classified and localized using bounding boxes and/or polygon annotations to highlight the affected bone area. Special attention was given to annotation consistency, anatomical accuracy, and edge-case handling, including hairline fractures and complex fracture patterns.

2021 - 2022

Education

A

AMC Engineering College

Bachelor of Engineering, Computer Science and Engineering

Bachelor of Engineering
2019 - 2023
P

Premier P.O College

PUC, Science

PUC
2018 - 2019

Work History

S

Suma Soft

Customer Support Executive

Pune
2024 - 2025