Privacy-Preserving Machine Learning is an important and exciting research subject that investigates how to benefit from machine learning techniques while preserving the privacy of training data and learned models.

At the PPML School 2022 lecturers with both a theoretical and applied background will cover a broad spectrum of subjects such as Multiparty Computation, Fully Homomorphic Encryption, Differential Privacy, Federated Learning as well as practical attacks. Current confirmed speakers are:

• Emiliano De Cristofaro (UCL)
• Rafael Dowsley (Monash University – tentative)
• Divya Gupta (Microsoft Research)
• Peter Kairouz (Google)
• Yuriy Polyakov (Duality)
• Yang Zhang (CISPA)

The school is aimed at PhD and Master students in the areas of Security as well as Machine Learning, but we also encourage researchers as well as other people with an interest in the area to attend.

Registration for the school is now open for a fee of 500 DKK (approximately 70 USD or 67 EUR). Students can obtain 3 ECTS for attending the school.

The event is organized by Bernardo David, Associate Professor at ITU Copenhagen and Carsten Baum, Assistant Professor at Aarhus University and will take place from August 1st until August 4th on the campus of ITU Copenhagen. We are currently investigating a remote participation option, but this is so far not decided.

More information will be provided soon. We will provide information about potential stipends at a later point of time.

Registration deadline is on June 30th!

The event is supported by the International Association for Cryptologic Research, the Danish Data Science Academy, the Pioneer Centre for Artificial Intelligence as well as the Digital Research Centre Denmark (DIREC).