Summer School on Security & Privacy in the Age of AI

About

The KU Leuven 'Summer School on Security and Privacy in the Age of AI' deep-dives into the intersection of Machine Learning and cybersecurity. You will discover how AI introduces both novel opportunities and threats for security and privacy. You will learn how to defend ML pipelines against adversarial threats, and discover cutting-edge strategies to secure applications in the age of data-driven intelligence.

The program is designed for a comprehensive learning experience, structured around four key pillars (I-IV) to enhance participant knowledge and engagement. Pillar I offers foundational knowledge through introductory sessions, ensuring that attendees have a solid grasp of essential concepts behind AI for Security and Privacy, and Security and Privacy of AI. Pillar II provides focused deep dives into selected topics which vary each year, providing expert-led insights on advanced subdomains. Pillar III fosters exchange and community building, featuring poster sessions, mentoring opportunities, and an extensive seminar on soft skills. Pillar IV bridges the gap between academic research and industry, addressing practical applications, industry challenges, and legal concerns.

This 4-day program is hosted by KU Leuven (Computer Science dept.), taught in English, and organized on-campus in Leuven, Belgium

Course leader

Vera Rimmer

Target group

PhD students and researchers

Course aim

This summer school gathers young researchers and seasoned experts to zoom into security and privacy aspects of the flourishing area of machine learning. On the one hand, we consider strengthening security and privacy solutions with advanced AI; on the other hand, we want to drive state-of-the-art ML to higher security and privacy levels.

The primary goal of the summer school is to propel progress towards pragmatic and sound research methodologies, while simultaneously guiding and supporting the next generation of researchers in their early stages. Additionally, the program aims to establish stronger ties between academia and industry, ultimately fostering a stronger, more interconnected research community

Fee info

The tuition fee includes all the classes and course materials, lunches, coffee breaks, and social dinner