Supporting organizations in evaluating, designing, and applying anonymization for safe data reuse.
Organizations want to use data. Privacy laws make it complex.
Organizations increasingly rely on data for research, AI, and innovation.
However, sharing or using data often involves significant privacy risks.
Simply removing names or direct identifiers is rarely sufficient.
Even datasets that appear anonymized may still allow individuals to be re-identified.
Understanding and mitigating these risks requires specialized expertise.
Assess probability of
re-identification in datasets.
Expert advisor for
Worked with
GDPR | HIPAA | AI Act | EHDS
• Strengths and weaknesses
• When to use which approach
• Limitations of tools
Interview European
Leadership University
Sentiment analyse
Python & Power BI
Independent expert in data anonymization and re-identification risk.
Specialized in evaluating privacy risks in datasets used for research, AI, and data sharing.
Focus on scientific analysis and
independent advice.
For privacy professionals, security experts, and anyone interested in learning more about anonymization.
23 September 2026
17.00 to 18.00 hr
Dataset intake and
context analysis
Identifification and
classifification of
identififiers
Re-identifification
risk modeling
Evaluation of possible
transformations to
ensure the data is
anonymous
Final risk assessment
and recommendations
Complete audit-proof
report
If you are planning to share, publish, or use personal data,
understanding the privacy risks is essential.
