Interviewing and Recruiting
- F. Boenisch, C Mühl, R. Rinberg, J. Ihrig, A. Dziedzic. Individualized PATE: Differentially Private Machine Learning with Individual Privacy Guarantees. Accepted to PoPETs 2023.
- R. Rinberg, N. Agarwal: “Privacy when Everyone is Watching: An SOK on Anonymity on the Blockchain”., 2022
- NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation, 2022.
- A. Tamaskar, R. Rinberg, S. Chakraborty, B. Mishra: “Creolizing the Web”. 2021.
Projects and Preprints
- I lead a group of cross-university graduate students who meet and discuss privacy and security from technical, legal, and policy perspectives. We are called Technically Private (though informally sometimes go by Privacy Peeps). Please reach out if you are interested in joining.
The Silver Screen