I am the Responsible AI Engineering lead @ 
Technologies.
AI and ML are at HERE’s core, with their adoption spanning from data ingestion pipelines to user-facing products like WeGo.
This widespread adoption brings complex challenges in AI governance, which I tackle every day.
My mission is to ensure the responsible use of AI across HERE’s products and processes. I provide technical guidelines to development teams, build tools that enable safe and scalable AI adoption, and design compliance frameworks and policies. These efforts led HERE to become the first company in the industry to achieve ISO 42001 certification for AI management.
Contact:
Previously worked as Privacy Architect @ Technologies, focusing on location privacy and anonymization.
HERE’s business is about the creation of data-driven location-based services from a variety of location data. In my research I develop privacy-enhancing algorithms that reduce the privacy risk for the data producer, i.e. the end user, associated with the publication of location-data and with location-based services.
My work tackles two problems: The first problem is the measurement of privacy risk associated with different use cases, which involve different kinds of location data and location-based services, the second problem is the development and validation of privacy-enhancing algorithms for specific use cases.
In 2018, I completed a doctorate @ 
under the supervision of Prof. Dirk Helbing
In my research, I look at the interaction between intelligent entities, be they humans beings, animals or smart devices, and I study them from two perspectives:
First, I study the effect of individual learning on the patterns of interaction, hence on the population-level behavior, and vice-versa. Second, I apply this knowledge to design new patterns of interactions and communication protocols that improve social aspects, such as privacy, discrimination and inequality.
I take a multi-disciplinary approach at the intersection between the social sciences and computer science. My methodology is based on three pillars: computer simulations, machine learning and data analysis.
If you want to know more about my research, visit the Research page