Dunia Mahboobeh
Junior Research Scientist
Affiliation: NYU Abu Dhabi
Education: BSc Khalifa University, MSc Khalifa University
Research Websites: Center for Cyber Security
Research Areas: Machine learning security, Bias and fairness auditing in ML, AI sovereignty
Dunia J. Mahboobeh earned both a Bachelor of Science in Electrical Engineering and a Master of Science in Electrical and Computer Engineering, with a specialized concentration in Artificial Intelligence (AI), from Khalifa University in the United Arab Emirates. Grounded in a rigorous engineering background, her academic trajectory has consistently focused on building a deep foundation in general electrical and computer engineering principles before transitioning into specialized machine learning systems and artificial intelligence.
Currently, Mahboobeh serves as a Researcher at New York University Abu Dhabi (NYUAD) within the Center for Cyber Security (CCS). Her ongoing scholarly work concentrates primarily on the intersection of algorithmic bias, fairness, and security in machine learning systems. Specifically, her research addresses the critical challenge of creating reliable, trustworthy auditing schemes tailored to highly skewed and demographically biased datasets to prevent adversarial attacks that exploit these underlying data imbalances.
Expanding on her auditing research, Mahboobeh’s work also focuses on generative AI sovereignty across models. Her research seeks to trace and identify a model's origin and training provenance to reveal latent regional biases, evaluate cross-border performance discrepancies, and quantify how geographic data imbalances impact critical national strategic interests. Her contributions at NYUAD advance the broader field of trustworthy AI, ensuring that machine learning systems remain ethically equitable, secure against adversarial manipulation, and accountable to regional governance priorities.