Hamza Harkous

Hamza Harkous

I am a Staff Research Scientist at Google, Zürich. I currently work on techniques and systems for revamping synthetic data generation with large language models, taking agentic approaches focused on data diversity and complexity. Before that, I lead an effort to transform the data curation and model building process with LLMs, driving advancements in privacy, safety, security, and beyond across Google's products. I previously architected the machine learning models behind Google Checks, the privacy compliance service. I also built core models behind Hark, one of Google's internal systems for feedback analysis, through which all user feedback goes every day. Prior to Google, I worked at Amazon Alexa on natural language understanding and generation. I received my PhD in Computer Science from the Swiss Federal Institute of Technology in Lausanne (EPFL), where I also served as a postdoctoral researcher. During that time, I researched and developed tools for improving users’ comprehension of privacy practices and for automatically analyzing privacy policies. You can find more about my work on my personal homepage.
Authored Publications
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    Google
Website Data Transparency in the Browser
Sebastian Zimmeck
Daniel Goldelman
Owen Kaplan
Logan Brown
Justin Casler
Judeley Jean-Charles
Joe Champeau
24th Privacy Enhancing Technologies Symposium (PETS 2024), PETS (to appear)
On the Potential of Mediation Chatbots for Mitigating Multiparty Privacy Conflicts - A Wizard-of-Oz Study
Kavous Salehzadeh Niksirat
Diana Korka
Kévin Huguenin
Mauro Cherubini
The 26th ACM Conference On Computer-Supported Cooperative Work And Social Computing (CSCW) (2023) (to appear)
CookieEnforcer: Automated Cookie Notice Analysis and Enforcement
Rishabh Khandelwal
Asmit Nayak
Kassem Fawaz
32th USENIX Security Symposium (2023)
PriSEC: A Privacy Settings Enforcement Controller
Rishabh Khandelwal
Thomas Linden
Kassem Fawaz
30th USENIX Security Symposium (2021)
Have Your Text and Use It Too! End-to-End Neural Data-to-Text Generation with Semantic Fidelity
Isabel Groves
Amir Saffari
The 28th International Conference on Computational Linguistics (COLING 2020) (to appear)