Hamza Harkous is a Research Scientist in the Applied Privacy Research group at Google, Zürich. His research lies at the intersection of natural language processing and data privacy. He currently leads an initiative to transform the data curation and model building process for large language models, driving advancements in privacy, safety, and security across Google’s products. He previously architected the machine learning models behind Google’s “Checks”, the privacy compliance service.
Prior to his tenure at Google, he worked at Amazon Alexa on natural language understanding and generation. He holds a Master’s degree in Communication Systems and a PhD in Computer Science from the Swiss Federal Institute of Technology in Lausanne (EPFL), where he also served as a postdoctoral researcher. During that time, he researched and developed tools for improving users’ comprehension of privacy practices and for automatically analyzing privacy policies. He received his B.E. in computer and communications engineering from the American University of Beirut, Lebanon.
He is the recipient of the 2019 Caspar Bowden Award for Outstanding Research in Privacy Enhancing Technologies as well as the 2017 Thesis Excellence Award from the Information Security Society in Switzerland.