Dr Haleh Asgarinia (H.)

Haleh Asgarinia is a researcher in the Health, Ethics, and Society Department at Maastricht University in the Netherlands. Before joining MU, she obtained her PhD in Ethics and Philosophy of Technology from the University of Twente, specializing in AI Ethics. Haleh has a background in philosophy of science and technology and computer engineering, specializing in software engineering, having studied them in her master’s and bachelor’s degrees, respectively.

Her PhD research primarily focused on the impacts of Machine Learning (inference as a process associated with ML) on various aspects of privacy, including the definition of privacy, the social value of privacy, and the group right to privacy. She also evaluated the effectiveness of the GDPR in addressing related concerns and proposed design requirements to incorporate the social value of privacy into the design of systems. 

Haleh’s PhD research was conducted within the European Commission’s Horizon 2020 project, PROTECT - Protecting Personal Data Amidst Big Data Innovation, funded by the EU’s Marie-Sklodowska-Curie ITN grant. Her work in PROTECT emphasized analyzing data-related regulations from an ethical perspective and developing an interoperable privacy paradigm that fosters trust and transparency in data governance.

Haleh is currently involved in the DACIL Project (Developing a Digital COPD Companion for Improving Lifestyle), where her research focuses on respecting patients' right to privacy and minimizing privacy risks. She is investigating how to collect patient data for model training while safeguarding the privacy of data sources and targets. Based on her PhD research and certification as a Certified Information Privacy Professional/Europe (CIPP/E), she continues to address privacy and data protection from ethical and legal perspectives.

Expertises

- AI Ethics: Focused on privacy, data protection, trust, and autonomy
- Privacy-by-Design: Embedding the (social) value of privacy into the design of systems
- GDPR Compliance: Navigating data protection regulations in AI systems