Summer School on Security and Privacy in the Age of AI

Azqa Nadeem is an Assistant Professor at the University of Twente in the Semantics, Cybersecurity, and Services (SCS) group. Her research focuses on developing explainable machine learning solutions for cybersecurity tasks such as incident response, malware analysis, and intrusion detection. Before joining UT, she held research positions at Eurecom, RIT, EPFL, and CERN. She obtained her PhD in 2024 at TU Delft, where she developed explainable sequential machine learning toolchains for automating cyber threat intelligence. Azqa’s mission is to go beyond prediction probabilities and extract semantically meaningful insights from ML models to create AI-assisted practitioners.

Adriana Sejfia is an Assistant Professor in Software Engineering at the University of Edinburgh. She completed her PhD at the University of Southern California in 2023. Adriana’s research interests lie in the field of software engineering, with a focus on security-related tasks. Specifically, she researches ways to deliver actionable security insights to developers. To thatend, she makes use of program analysis and machine learning. Currently, Adriana is focusing on improving automated software vulnerability detectors.

Fabio Roli is Full Professor of Computer Engineering at the Universities of Genova and Cagliari, Italy. He is Director of the sAIfer Lab, a joint lab between the Universities of Genova and Cagliari on Safety and Security of AI. Fabio does research on adversarial machine learning systems for security applications. He has been appointed Fellow of the IEEE, Fellow of the International Association for Pattern Recognition, and Fellow of the Asia-Pacific Artificial Intelligence Association.

Maura Pintor is an Assistant Professor at the PRA Lab, in the Department of Electrical and Electronic Engineering of the University of Cagliari, Italy. She received her PhD in Electronic and Computer Engineering from the University of Cagliari in 2022. She has provided several contributions in the area of adversarial machine learning, including efficient methods for ML testing and debugging frameworks for achieving trustworthy security evaluations of machine learning models. She is also the main organizer of the MLSec seminar series, aimed at inviting distinguished speakers to disseminate scientific results and applications to a worldwide audience.

Christian Wressnegger is a Tenure-Track Assistant Professor of Computer Science at Karlsruhe Institute of Technology (KIT) heading the “Artificial Intelligence and Security” research group. His research revolves around combining machine learning (or AI in the broader scope) and computer security. He develops methods in the area of system security and application security, for instance, approaches for attack detection or vulnerability discovery in software. Moreover, he researches the robustness of machine learning against attacks striving for “secure AI.” In this context, he is particularly interested in the security of XAI.

Dr. Fabio Pierazzi is a Senior Lecturer (Associate Professor) and Deputy Head of the Cybersecurity group at the Department of Informatics at King’s College London. His research interests are at the intersection of systems security and machine learning, with a particular emphasis on settings in which attackers adapt quickly to new defenses (i.e., high non-stationary, adaptive attackers).

Andrew Paverd is a Principal Research Manager in the Microsoft Security Response Center (MSRC), where he leads the strategic research initiative on AI Security & Privacy. In collaboration with researchers from across Microsoft, he has been working on tools and techniques to measure and mitigate privacy risks in machine learning. His research interests also include web and systems security. Prior to joining Microsoft, he was a Fulbright Cyber Security Scholar at the University of California, Irvine, and a Research Fellow in the Secure Systems Group at Aalto University. He received his DPhil from the University of Oxford in 2016.

Peggy Valcke is full professor of law & technology at KU Leuven and vice dean for research at the Leuven Faculty of Law & Criminology. She is executive committee member at CiTiP and Leuven.AI, and principal investigator in the Security & Privacy Department of imec (previously iMinds). She has taken up positions as visiting and part-time professor at Tilburg University, Bocconi University Milan, the European University Institute in Florence, and Central European University in Budapest. In January 2024, she joined the executive board of the Belgian Institute for Postal Services and Telecommunications (BIPT – IBPT).

Peggy’s current research focus lies with the rise of artificial intelligence technologies, and in particular algorithmic decision-making, in law enforcement, transport, media services, the judiciary, etc., and the ethical-legal implications thereof, especially in relation to human rights and the allocation of responsibilities / legal liabilities.

Sofie Royer is a research expert at CiTiP (KU Leuven), and a guest professor at UAntwerpen and ULiège. After a brief interlude as a lawyer, she has been a research and teaching assistant at the Institute of Criminal Law (KU Leuven) and meanwhile a visiting researcher at the Max Planck Institute for Foreign and International Criminal Law in Freiburg (Germany). Her PhD thesis (2020) on criminal seizure in a digitizing world was published as a book. Sofie’s main research focus lies with the impact of new technologies on criminal law, criminal procedure, and human rights. She is involved in various national and international research projects and coordinates important policy studies. Sofie is a regular speaker at and organizer of conferences and seminars. She is often interviewed by journalists on topics of criminal law and digitization and she contributes to making the law more accessible to a broad audience by means of podcasts.

Giovanni Cherubin is a Senior Researcher at Microsoft Research (Cambridge) working with the Microsoft Response Centre (MSRC). Before joining Microsoft, he held research positions at the Alan Turing Institute and EPFL, and he obtained a PhD in Machine Learning and Cyber Security from Royal Holloway University of London. His research focuses on privacy and security properties of machine learning models, and on the theoretical/empirical study of their information leakage. He also works on reliable machine learning tools, such as distribution-free uncertainty estimation for machine learning (e.g., Conformal Prediction). Some of his work on security and machine learning has been recognised with best student paper awards (SLDS15, PETS17), distinguished paper (USENIX22), and with a USENIX Internet Defense Prize (2022).

Marc Juarez is a Lecturer in Cyber Security and Privacy at the University of Edinburgh’s School of Informatics. Prior to his current appointment, he was a Postdoctoral Scholar in the Computer Science Department of the University of Southern California. His research focuses on investigating the privacy risks that arise from the application of machine learning techniques. More specifically, Marc’s work involves designing and evaluating countermeasures against machine learning-based attacks to privacy-aware Internet protocols, studying the privacy of deployed machine learning models, and developing private mechanisms to measure fairness properties of such models.

Lorenzo Cavallaro is a Full Professor of Computer Science at University College London (UCL), where he leads the Systems Security Research Lab. He grew up on pizza, spaghetti, and Phrack, and soon developed a passion for underground and academic research. Lorenzo’s research vision is to enhance the effectiveness of machine learning for systems security in adversarial settings. He works with his team to investigate the interplay between program analysis abstractions, representations, and ML models, and their crucial role in creating Trustworthy AI for Systems Security. Despite his love for food, Lorenzo finds his Flow in science, music, and family.