Ibrahim Baroud

Ibrahim Baroud is a researcher and doctoral student at the Quality and Usability Lab (Q&U Lab) of the Technical University of Berlin, focusing on privacy-preserving machine learning and data utility preservation. He holds a B.Sc. and M.Sc. in Computer Science from TU Berlin, with prior research experience at Charité - Universitätsmedizin Berlin and the German Research Center for Artificial Intelligence (DFKI). His work addresses the impact of de-identification techniques on clinical data utility and privacy robustness.

His research interests include AI-driven anonymization of personal patient data in clinical text and speech databases, combining machine learning with privacy-enhancing technologies. Current projects emphasize balancing data utility and privacy in healthcare contexts.

No scientific awards or publications are explicitly listed in the provided text.