For employers

Hire this AI Trainer

Sign in or create an account to invite AI Trainers to your job.

LoginCreate account
Invite to Job
N
Neşet Koçkar

Neşet Koçkar

Scientific Data Annotation Expert | Medical Imaging & Physics

Turkey flagAnkara, Turkey
$22.00/hrIntermediateOther

Key Skills

Software

Other

Top Subject Matter

Medical Imaging
Physics & Mathematics
Materials Science

Top Data Types

DocumentDocument
ImageImage
TextText

Top Task Types

SegmentationSegmentation
ClassificationClassification
Fine-tuningFine-tuning

Freelancer Overview

I am a dedicated mathematical physicist and independent researcher with hands-on experience in complex data annotation, preprocessing, and machine learning workflows. My academic background requires extreme precision and analytical rigor, which I directly apply to data labeling and AI training tasks. I have successfully curated and structured diverse datasets, ranging from processing large-scale materials science data (perovskite and chalcogen) for predictive modeling to extracting and formatting time-series data via APIs for algorithmic analysis. My standout expertise lies in medical image annotation, where I utilize 3D Slicer to accurately segment 3D DICOM data and establish reliable ground-truth datasets for anomaly detection models. Proficient in Python, Pandas, and NumPy, I bridge the gap between raw, unstructured data and high-quality, training-ready inputs. My deep understanding of the underlying machine learning architectures—such as GNNs, XGBoost, and Grad-CAM—ensures that the data I prepare perfectly aligns with the model's specific learning objectives, setting me apart in quality-focused execution.

IntermediateEnglishRussianTurkish

Labeling Experience

Data Curation for Materials Science AI

DocumentClassification
I curated and cleaned materials science datasets for use in AI model training. My data preparation focused on predictive modeling for crystal stability and superconductivity. I resolved inconsistencies to provide robust and accurate academic datasets. • Processed and standardized materials data formats. • Enabled Graph Neural Network and tree-based AI model training. • Focused on perovskite and chalcogen datasets for scientific use. • Ensured accuracy for materials science research.

I curated and cleaned materials science datasets for use in AI model training. My data preparation focused on predictive modeling for crystal stability and superconductivity. I resolved inconsistencies to provide robust and accurate academic datasets. • Processed and standardized materials data formats. • Enabled Graph Neural Network and tree-based AI model training. • Focused on perovskite and chalcogen datasets for scientific use. • Ensured accuracy for materials science research.

2026 - 2026

Medical Image Annotation and 3D Segmentation

Segmentation
I annotated and precisely segmented 3D medical images for ground-truth dataset creation in anatomical anomaly detection. My work ensured high quality and accuracy of processed DICOM data for medical machine learning pipelines. I also applied Grad-CAM techniques to visually support model validation and feature alignment. • Created detailed 3D medical image segmentations using 3D Slicer. • Structured complex DICOM data for machine learning. • Ensured data reliability for training anatomical models. • Used Grad-CAM to validate annotation focus areas.

I annotated and precisely segmented 3D medical images for ground-truth dataset creation in anatomical anomaly detection. My work ensured high quality and accuracy of processed DICOM data for medical machine learning pipelines. I also applied Grad-CAM techniques to visually support model validation and feature alignment. • Created detailed 3D medical image segmentations using 3D Slicer. • Structured complex DICOM data for machine learning. • Ensured data reliability for training anatomical models. • Used Grad-CAM to validate annotation focus areas.

2026 - 2026

Time-Series Data Extraction & Processing

TextClassification
I extracted, labeled, and preprocessed time-series financial data for predictive analytic modeling. I applied Fast Fourier Transform (FFT) to enhance feature engineering. My work prepared structured data for algorithmic analysis and machine learning. • Collected and labeled financial time-series data using APIs. • Applied data preprocessing and transformation techniques. • Enhanced datasets for predictive modeling applications. • Supported feature engineering with FFT methods.

I extracted, labeled, and preprocessed time-series financial data for predictive analytic modeling. I applied Fast Fourier Transform (FFT) to enhance feature engineering. My work prepared structured data for algorithmic analysis and machine learning. • Collected and labeled financial time-series data using APIs. • Applied data preprocessing and transformation techniques. • Enhanced datasets for predictive modeling applications. • Supported feature engineering with FFT methods.

2025 - 2025

Education

K

Kemer Fatma Turgut Sen Anatolian High School

High School Diploma, General High School Education

High School Diploma
2018 - 2022
A

Ankara University

Bachelor of Science, Physics

Bachelor of Science
2022

Work History

A

Ankara University

Independent Researcher

Ankara
2025 - Present
A

Ankara University

Nuclear Reactor Core Design Team Member

Ankara
2024 - 2025