09-19, 14:40–15:15 (Europe/Amsterdam), Mondriaan
Are you ready to push the boundaries of what’s possible with Python? Roseman Labs has developed a groundbreaking Python package—crandas—that puts cutting-edge cryptography right at your fingertips. If you’re familiar with pandas and sci-kit learn, crandas will feel like a natural extension, empowering you to unlock the full potential of sensitive data, gain deeper insights, and make predictions without compromising privacy.
In this session, Niek, the CTO of Roseman Labs, will guide you through the fascinating world of Multi-Party Computation (MPC). You’ll learn step-by-step how to work with data you can’t even see via our encryption engine, involving key players in the process and leveraging encrypted computing for data safety. This talk will feature a real-world case study that earned Roseman Labs a prestigious privacy award last year.
If you're a Python engineer with experience in pandas or simply eager to elevate your expertise with data privacy techniques, this session is for you. We’ll tackle essential privacy and compliance challenges, helping you hit the ground running—even with large datasets and complex calculations. Whether you're looking to integrate secure machine learning models like logistic regression or just curious to see crandas in action, be sure to join us at our stand for a live demo and hands-on experience.
Don’t miss this opportunity to upgrade how you work with sensitive data!
Niek is a founder of Roseman Labs, a company created to commercially realise privacy-preserving and/or confidential computations by means of secure multiparty computation (MPC).
Niek enjoys working on topics in computer science, mathematics and electrical engineering that combine theoretical (mathematical) foundations with practical relevance and feasibility. His work includes further developing such theoretical foundations, as well as bringing such foundations into practice, by means of, for example, writing a software implementation.
In his research at TU Eindhoven, he focused on MPC including its applications to privacy-preserving data mining & machine learning. At ABN AMRO, he has worked on machine learning techniques for detecting transaction fraud. At EPFL Switzerland, he has worked on security and control aspects of smart electricity grids. Niek holds a PhD in Mathematics ('12) from Leiden University, on the topic of quantum cryptography; this research was carried out in CWI's cryptology group. He obtained his MSc (cum laude) and BSc degree in Electrical Engineering from University of Twente. His master's thesis was in Communication and Information Theory. His research interests include cryptology, privacy-preserving machine learning, information theory, Bayesian statistics, and signal processing.