Caner K.-Synthetic Medical Dataset (MedGym)
Check rate
Experience
Synthetic Medical Dataset (MedGym)
MedTank
- Generated synthetic datasets for CXR, mammography, and distal radius fracture detection using GANs and diffusion, creating >50k synthetic images for benchmarking.
- Ensured GDPR-compliant workflows and reproducibility, enabling dataset adoption for internal validation and academic collaboration.
- Project highlighted in MedTank’s internal R&D showcase as a flagship synthetic data initiative.
Explainable AI for GANs
Technical University of Munich
- Implemented Saliency Maps, LIME, Shapley, and DeepLift with Captum to improve GAN transparency, making black-box generative models interpretable for medical AI researchers.
- Results presented in a departmental seminar, influencing adoption of explainability tools in ongoing research projects.
Machine Learning Engineer
MEDTANK Corp
- Spearheaded development of GAN/diffusion pipelines on radiology datasets (>1M CXRs), boosting synthetic data diversity by 25% and reducing classifier overfitting in regulated medical imaging workflows.
- Optimized Stable Diffusion for chest X-rays, improving SSIM/PSNR by up to 12% and enabling clinically plausible outputs validated by radiologists.
- Designed preprocessing and 3D segmentation workflows (MONAI, SimpleITK), enabling automated anomaly detection and ROI extraction, later integrated into hospital PACS/RIS pipelines.
- Collaborated with cross-functional teams to ensure GDPR-compliant data handling and contributed to deployment of ML systems in production-grade healthcare environments.
Data Science Intern
Data Glacier
- Built machine learning pipelines for predictive analytics on structured healthcare datasets, achieving a 15% improvement in model accuracy compared to baseline.
- Applied feature engineering and data visualization (Pandas, Scikit-learn, Matplotlib) to uncover actionable insights for business stakeholders.
- Deployed a proof-of-concept model to AWS, demonstrating scalability and integration into existing workflows.
Freelance Web Developer
Asel Wire Industry
- Delivered responsive React.js web application with reusable UI components.
Avionics Test Engineer Intern
ASELSAN A.S
- Built distributed tool for automated documentation, improving team efficiency.
Industry experience
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Experienced in Healthcare, Education, Manufacturing, and Aerospace and Defense.
Business area experience
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Experienced in Product Development, Research and Development, Information Technology, Business Intelligence, and Quality Assurance.
Summary
M.Sc. Informatics candidate at TUM with 2+ years of hands-on experience in generative AI and medical imaging. Specialized in diffusion/GAN pipelines, GDPR-compliant data handling, and deployment of ML systems in regulated medical imaging workflows. Thesis research on integrating Roentgen and MRM for synthetic radiology image generation. Seeking full-time AI/ML Engineer roles starting Sept. 2025.
Skills
- Ml/Ai: Pytorch, Huggingface, Tensorflow, Scikit-Learn, Monai, 3d Slicer
- Devops/Tools: Mlflow, Docker, Fastapi, Aws, Git, Langchain, Langgraph, Pydantic
- Programming: Python, Julia, C++, C#, Sql
- Compliance: Gdpr-Compliant Data Handling, Medical Imaging Workflows, Hipaa Awareness
Languages
Education
Technical University of Munich
M.Sc. Informatics · Informatics · Munich, Germany
Ankara University
B.Sc. Computer Engineering · Computer Engineering · Ankara, Turkey
Statistics
Experience
Global experience
Expertise
Qualifications
Profile
Frequently asked questions
Have questions? Find more information here.
Caner is based in Munich, Germany.
Caner speaks the following languages: Turkish (Native), English (Advanced), German (Elementary).
Caner has at least 6 years of experience. During this time, Caner has worked in at least 6 different roles and for 6 different companies. The average length of individual experience is 1 year. Note that Caner may not have shared all experience and actually has more experience.
Based on recent experience, Caner would be well-suited for roles such as: Synthetic Medical Dataset (MedGym), Explainable AI for GANs, Machine Learning Engineer.
Caner's most recent position is Synthetic Medical Dataset (MedGym) at MedTank.
In recent years, Caner has worked for MedTank, Technical University of Munich, MEDTANK Corp, and Data Glacier.
Caner is most experienced in industries like Healthcare, Education, and Manufacturing. Caner also has some experience in Aerospace and Defense.
Caner is most experienced in business areas like Product Development, Research and Development, and Information Technology. Caner also has some experience in Business Intelligence and Quality Assurance.
Caner has recently worked in industries like Healthcare and Education.
Caner has recently worked in business areas like Product Development, Research and Development, and Business Intelligence.
Caner holds a Master in Informatics from Technical University of Munich and a Bachelor in Computer Engineering from Ankara University.
The availability of Caner needs to be confirmed.
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The median daily rate is the middle value of all daily rates — half of comparable freelancers charge less, half charge more. Unlike the average, it is barely affected by outliers.
Calculated based on our freelancers’ daily rates as of 7 Sep 2026. Actual rates may vary depending on seniority level, experience, skill specialization, project complexity, and engagement length.
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