
Dr. Rob van Eijk leads the Future of Privacy Forum's European operations as Managing Director. Previously, he spent a decade at the Dutch Data Protection Authority as Senior Supervision Officer and Lead Technologist. With a Ph.D. from Leiden Law School focused on online advertising and privacy, plus degrees in Electrical Engineering and Computer Science, he brings deep technical expertise to privacy policy. He recently served as a guest professor at Leiden University, teaching Explainable AI.
Elementy, w których Rob van Eijk uczestniczy
wtorek 5 kwiecień, 2022
środa 6 kwiecień, 2022
Session in English interpreted into Italian / Sessione in inglese con la traduzione in italiano
środa 19 kwiecień, 2023
czwartek 20 kwiecień, 2023
poniedziałek 12 maj, 2025
Generative AI development and deployment is exploding, but the recent EDPB Opinion 28/2024 and early enforcement actions (notably the fine against OpenAI by the Garante in Italy) signal that compliance with the GDPR must be taken seriously from the outset. Against this backdrop, our panel will explore how to build trust and avoid pitfalls when developing and deploying LLMs in Europe. We’ll examine the evolving legal landscape—and whether it leaves enough room for meaningful innovation....
czwartek 15 maj, 2025
If you are interested in how to turn the principle of privacy into marketing practices that not only comply with the law but also resonate with the audience, then this session is for you. The panel will explore how to build privacy-first marketing strategies that respect consumer data while still driving engagement and delivering results. Key questions
This session will cover the legal implications and real-world use cases of anonymization, pseudonymization, and synthetic data. From enabling secure data sharing for research and ensuring compliance in clinical trials, the panel will dive into how some techniques can help meet privacy requirements while still fostering scientific progress. Key questions
piątek 16 maj, 2025
This session will explore cutting-edge approaches to responsibly sharing personal data for AI development. Topics include federated learning, synthetic data generation, and Privacy Enhancing Technologies (PETs), focusing on how these methods support data privacy, facilitate cross-border collaboration, and help meet regulatory requirements in healthcare research, and other sensitive sectors. The session will include practical insights from the specialists in PET domain, based on their experien...