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Abhishek Prakash

Abhishek Prakash

AI Engineer with patented biometric system and real world ml deployments and data annotator

India flagKanpur, India
$30.00/hrIntermediateOtherRoboflowLabel Studio

Key Skills

Software

Other
RoboflowRoboflow
Label StudioLabel Studio
SuperAnnotateSuperAnnotate

Top Subject Matter

Biometric Authentication
Palm Vein Recognition
Agricultural Image Analysis

Top Data Types

ImageImage
TextText
Computer Code ProgrammingComputer Code Programming

Top Task Types

SegmentationSegmentation
ClassificationClassification
Bounding BoxBounding Box
Object DetectionObject Detection
Text GenerationText Generation
Text SummarizationText Summarization
Data CollectionData Collection

Freelancer Overview

Research Associate – Palm Vein Biometrics Data Annotation. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include OpenCV and Other. Education includes Bachelor of Technology and Master of Technology, Indian Institute of Technology Kanpur (2021) and Senior Secondary Certificate, Sunbeam Suncity School Varanasi (2020). AI-training focus includes data types such as Image and labeling workflows including Segmentation and Classification.

IntermediateEnglishHindiBhojpuri

Labeling Experience

Wheat Grain Dataset Image Annotator – Automated Analysis Project

ImageClassification
Engineered data annotation pipelines for AI-powered wheat grain analysis, focusing on labeling images for healthy seeds, bad seeds, and impurities with YOLOv11. Coordinated dataset curation, image annotation, and verification to reduce manual inspection load and enable high-accuracy model training. Executed segmentation and scoring of dense grain regions using SAM-enabled Cellpose for deeper analysis. • Labeled over 7,000 wheat grain images for seed classification tasks. • Utilized Cellpose to annotate and segment more than 3,000 wheat grain samples. • Generated labels for both object classes and region segmentations for multi-task training. • Leveraged OpenCV and custom pipelines for efficient annotation and quality control.

Engineered data annotation pipelines for AI-powered wheat grain analysis, focusing on labeling images for healthy seeds, bad seeds, and impurities with YOLOv11. Coordinated dataset curation, image annotation, and verification to reduce manual inspection load and enable high-accuracy model training. Executed segmentation and scoring of dense grain regions using SAM-enabled Cellpose for deeper analysis. • Labeled over 7,000 wheat grain images for seed classification tasks. • Utilized Cellpose to annotate and segment more than 3,000 wheat grain samples. • Generated labels for both object classes and region segmentations for multi-task training. • Leveraged OpenCV and custom pipelines for efficient annotation and quality control.

2025 - 2025

Research Associate – Palm Vein Biometrics Data Annotation

ImageSegmentation
Led the development of an AI pipeline using YOLOv11, UNet++, and Sobel for palm detection, segmentation, and ROI extraction as part of a patented non-contact palm vein authentication system. Built and trained a Siamese network with advanced loss functions to create robust multimodal palm embeddings, leveraging labeled image data for supervised learning. Oversaw end-to-end data collection, annotation, and evaluation to ensure model accuracy and reliability. • Curated and annotated palm images for detection and segmentation tasks. • Labeled regions of interest and vein patterns to train and evaluate the segmentation and embedding pipeline. • Evaluated segmentation outcomes using accuracy metrics and refined annotations for performance improvements. • Used OpenCV as well as proprietary tools during the annotation and modeling process.

Led the development of an AI pipeline using YOLOv11, UNet++, and Sobel for palm detection, segmentation, and ROI extraction as part of a patented non-contact palm vein authentication system. Built and trained a Siamese network with advanced loss functions to create robust multimodal palm embeddings, leveraging labeled image data for supervised learning. Oversaw end-to-end data collection, annotation, and evaluation to ensure model accuracy and reliability. • Curated and annotated palm images for detection and segmentation tasks. • Labeled regions of interest and vein patterns to train and evaluate the segmentation and embedding pipeline. • Evaluated segmentation outcomes using accuracy metrics and refined annotations for performance improvements. • Used OpenCV as well as proprietary tools during the annotation and modeling process.

2025 - 2025

Image Dataset Annotator – ML Winter Project

OtherImageSegmentation
Focused on the creation of image datasets and training pipelines for restoration tasks such as deblurring, denoising, and low-light enhancement using U-Net and MAGNet models. Handled annotation and segmentation of image data from popular datasets like DIV2K, GoPro, and LOL to enable reliable model benchmarking and evaluation. Optimized data and annotation flows to support advanced training and high-quality restoration results. • Prepared and segmented images for various restoration challenges. • Utilized PSNR and SSIM evaluation criteria to verify annotation quality and restoration output. • Integrated open-source datasets and internal pipelines for annotation tasks. • Engaged with Google Developer Student Club tools and Python-based software for annotation and validation.

Focused on the creation of image datasets and training pipelines for restoration tasks such as deblurring, denoising, and low-light enhancement using U-Net and MAGNet models. Handled annotation and segmentation of image data from popular datasets like DIV2K, GoPro, and LOL to enable reliable model benchmarking and evaluation. Optimized data and annotation flows to support advanced training and high-quality restoration results. • Prepared and segmented images for various restoration challenges. • Utilized PSNR and SSIM evaluation criteria to verify annotation quality and restoration output. • Integrated open-source datasets and internal pipelines for annotation tasks. • Engaged with Google Developer Student Club tools and Python-based software for annotation and validation.

2023 - 2024

Education

I

Indian Institute of Technology Kanpur

Bachelor of Technology and Master of Technology, Electrical Engineering

Bachelor of Technology and Master of Technology
2021 - 2026
S

Sunbeam Suncity School Varanasi

Senior Secondary Certificate, Science

Senior Secondary Certificate
2019 - 2020

Work History

S

Stanford University

Senior Student Research Associate

Stanford
2025 - 2025
I

Indian Institute of Technology Kanpur

Manager, Community Welfare Cell

Kanpur
2023 - 2024