Prasad Bn

Key Skills

Software

Other

SuperAnnotate

Top Subject Matter

Traffic Sign Detection (Automotive)

Autonomous Vehicle Perception/Tracking

Large Language Model (LLM) Evaluation

Top Data Types

Image

3D Sensor

Text

Audio

Video

Top Task Types

Bounding Box

Segmentation

Classification

Transcription

Tracking

Freelancer Overview

SR (Sign Detection) Project Data Annotation Specialist. Core strengths include Other and SuperAnnotate. Education includes Secondary School Leaving Certificate, Morarji Desai Model Residential School (2016) and Pre-University Education, Morarji Desai Residential PU Collage (2018). AI-training focus includes data types such as Image, 3D Sensor, and Text and labeling workflows including Bounding Box, Segmentation, and Evaluation.

Labeling Experience

Video Annotation and Tracking Specialist

SuperannotateVideoTracking

I performed detailed video annotation for object detection and tracking complex dynamics in sports, traffic, and agricultural research. My annotations enabled precise temporal data creation for automated analysis and prediction systems. Team collaboration and quality review were integral to my annotation workflow. • Used SuperAnnotate and Mindkosh for advanced video tracking projects. • Worked on sports, vehicle, and plant growth analysis. • Ensured consistent annotation across frames and sequences. • Conducted internal quality assurance for project outputs.

I performed detailed video annotation for object detection and tracking complex dynamics in sports, traffic, and agricultural research. My annotations enabled precise temporal data creation for automated analysis and prediction systems. Team collaboration and quality review were integral to my annotation workflow. • Used SuperAnnotate and Mindkosh for advanced video tracking projects. • Worked on sports, vehicle, and plant growth analysis. • Ensured consistent annotation across frames and sequences. • Conducted internal quality assurance for project outputs.

Not specified

Audio Annotation and Transcription Specialist

SuperannotateAudioTranscription

I executed high-accuracy audio transcription for multi-speaker conversations, optimizing structured datasets for machine learning. My work supported projects aiming at speech recognition and natural language processing improvements. Detailed annotation and verification ensured accuracy across varied audio scenarios. • Used SuperAnnotate and Mindkosh for audio transcription. • Focused on multi-speaker and noisy environment datasets. • Prioritized accuracy and quality in transcribed output. • Supported downstream speech and NLP modeling projects.

I executed high-accuracy audio transcription for multi-speaker conversations, optimizing structured datasets for machine learning. My work supported projects aiming at speech recognition and natural language processing improvements. Detailed annotation and verification ensured accuracy across varied audio scenarios. • Used SuperAnnotate and Mindkosh for audio transcription. • Focused on multi-speaker and noisy environment datasets. • Prioritized accuracy and quality in transcribed output. • Supported downstream speech and NLP modeling projects.

Not specified

2D Image Annotation Specialist

SuperannotateImageBounding Box

I performed bounding box, polygon, and polyline annotations on 2D images for various detection needs such as object identification and roof structure analysis. Projects included military vehicle detection and satellite imagery annotation for multiple domains. Consistently ensured accuracy and compliance with project specifications. • Used SuperAnnotate, CVAT, Mindkosh, and Roboflow for image annotation tasks. • Worked on military, satellite imagery, and roof detection cases. • Applied multiple annotation modes (box, polygon, polyline). • Maintained data quality and consistency across datasets.

I performed bounding box, polygon, and polyline annotations on 2D images for various detection needs such as object identification and roof structure analysis. Projects included military vehicle detection and satellite imagery annotation for multiple domains. Consistently ensured accuracy and compliance with project specifications. • Used SuperAnnotate, CVAT, Mindkosh, and Roboflow for image annotation tasks. • Worked on military, satellite imagery, and roof detection cases. • Applied multiple annotation modes (box, polygon, polyline). • Maintained data quality and consistency across datasets.

Not specified

Contextual Intelligence Data Annotator

SuperannotateImageClassification

I engineered real-time content analysis solutions for image and video data, enabling advanced targeting for advertising scenarios. My role focused on multi-modal moderation pipelines and context-aware annotation to optimize engagement metrics. Implemented metadata extraction for real-time content descriptions to enhance discoverability. • Used SuperAnnotate for image and video content analysis. • Developed automated moderation workflows. • Annotated content for targeted ad serving. • Extracted metadata to support content indexing.

I engineered real-time content analysis solutions for image and video data, enabling advanced targeting for advertising scenarios. My role focused on multi-modal moderation pipelines and context-aware annotation to optimize engagement metrics. Implemented metadata extraction for real-time content descriptions to enhance discoverability. • Used SuperAnnotate for image and video content analysis. • Developed automated moderation workflows. • Annotated content for targeted ad serving. • Extracted metadata to support content indexing.

Not specified

RUBY LLM Human-in-the-Loop Evaluator

SuperannotateText

I worked on a framework providing human-in-the-loop evaluation of large language model agents, focusing on factuality, prompt adherence, and output quality. My responsibilities included comparative rating, feedback generation, and aggregating data for model improvement. The role required detailed annotation and assessment to support iterative training processes. • Used SuperAnnotate for text data evaluation and rating. • Evaluated LLM output for quality and accuracy. • Generated feedback and comparative summaries. • Facilitated robust model evaluation workflows.

I worked on a framework providing human-in-the-loop evaluation of large language model agents, focusing on factuality, prompt adherence, and output quality. My responsibilities included comparative rating, feedback generation, and aggregating data for model improvement. The role required detailed annotation and assessment to support iterative training processes. • Used SuperAnnotate for text data evaluation and rating. • Evaluated LLM output for quality and accuracy. • Generated feedback and comparative summaries. • Facilitated robust model evaluation workflows.

Not specified

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Education

Work History