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Prof. Lorenzo Cavallaro on "Trustworthy AI... for Systems Security"
20 January 2026, 11:00 am–1:00 pm
Can Machine Learning truly help us build secure systems?
Event Information
Open to
- All | UCL staff | UCL students | UCL alumni
Availability
- Yes
Organiser
-
Vijay Patel
Location
-
40566-72 Gower StreetLondonWC1E 6EAUnited Kingdom
Trustworthy AI... for Systems Security
You're warmly invited to a talk by Professor Lorenzo Cavallaro on "Trustworthy AI... for Systems Security". Join the CDT Cybersecurity community for this insightful session and discussion. Join the CDT Cybersecurity community for this insightful session and discussion.
No day goes by without reading about machine learning (ML) success stories in every walk of life. Systems security is no exception, where ML’s tantalizing performance may leave us wondering whether any problems remain unsolved. Yet ML has no clairvoyant abilities, and once the magic wears off, we are left in uncharted territory. Can it truly help us build secure systems? In this talk, I will argue that performance alone is not enough. I will highlight the consequences of adversarial attacks and distribution shifts in realistic settings, and discuss how semantics may provide a path forward. My goal is to foster a deeper understanding of machine learning’s role in systems security and its potential for future advancements.
You will need to register via Eventbrite - https://www.eventbrite.com/e/trustworthy-ai-for-systems-security-by-prof...
There will be lunch and a networking session at the end of the talk.
About the Speaker
Prof. Lorenzo Cavallaro
Lorenzo Cavallaro grew up on pizza, spaghetti, and Phrack, and soon developed a passion for underground and academic research. He is a Full Professor of Computer Science at University College London (UCL), where he leads the Systems Security Research Lab — https://s2lab.cs.ucl.ac.uk. Lorenzo’s research vision is to enhance the effectiveness of machine learning for systems security in adversarial settings. To this end, he and his team investigate the interplay among program analysis abstractions, engineered and learned representations, and grounded models, and their crucial role in creating Trustworthy AI for Systems Security. Lorenzo publishes at and sits on the Program Committee of leading conferences in computer security and ML, received the Distinguished Paper Award at USENIX Security 2022, ICML 2024 Spotlight Paper, and DLSP 2025 Best Paper Award (co-located with IEEE S&P)/ He is also Associate Editor of ACM TOPS and IEEE TDSC. In addition to his love for food, Lorenzo finds his Flow in science, music, and family.