Yuliya Sapega
A practical AI professional with 14+ years of expertise in Data Science, Analytics, Engineering, and AI, along with 5 years in leadership roles. Combines technical expertise with business acumen, gained from working with complex organizations such as IKEA, KLM, KPN, the City of Rotterdam, AON, and ING. Focusing on designing and integrating practical AI solutions that align with your organization’s objectives.
Session
Privacy-Enhancing Technologies (PETs) promise to bridge the gap between data utility and privacy — but how do they perform in practice? In this talk, we’ll share real-world insights from our hands-on experience testing and implementing leading PET solutions across various data science use cases.
We explored tools such as differential privacy libraries, homomorphic encryption frameworks, federated learning, multi-party computation, etc. Some lived up to their promise — others revealed critical limitations.
You’ll walk away with a clear understanding of which PET solutions work best for which types of data and analysis, what trade-offs to expect, and how to set realistic goals when integrating PETs into your workflows. This session is ideal for data professionals and decision-makers who are navigating privacy risks while still wanting to innovate responsibly.