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Freelancer Overview

I am a Ph.D. candidate specializing in data privacy and cybersecurity, with hands-on experience in data analysis, annotation, and the development of automated frameworks for privacy-preserving machine learning. My research has focused on the design and implementation of data anonymization methods, including Differential Privacy and K-Anonymity, where I built and open-sourced a framework that automates parameter tuning and optimizes data labeling processes across real-world datasets. I have practical skills in Python, PyTorch, and scikit-learn, and am experienced in network packet capture, protocol analysis, and the use of tools like Wireshark and SQL for structured data management. My background allows me to ensure high-quality, accurate training data for AI applications, with a strong emphasis on data integrity, privacy, and security.

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