Strachey Lectures

Trinity Term 2026 Strachey Lecture with Professor Srđan Čapkun, Hardening Digital Infrastructure: Resilient Positioning and Sovereign Smartphone Architectures. Recent global events have underscored how failures in isolation, redundancy, and control can jeopardiseessential digital functions. A critical challenge remains: how do we harden systems for higher resiliency, personal and societal control while maintaining compatibility with existing ecosystems? In this talk, I explore this in two example settings. First, I address the systemic vulnerabilities of current satellite positioning systems. By integrating novel protocols hardened at the physical layer, I demonstrate a path toward a robust, feature-rich, wide-area positioning infrastructure. Second, I introduce a novel security architecture that brings true digital sovereignty to the modern smartphone. This deployable design allows users to run 'several phones in one' (e.g. isolating private and business environments), ensuring that sensitive applications and critical I/O remain protected even if the underlying OS is compromised. Ultimately, these designs return control to users and organisations, fostering a more resilient and free environment for digital innovation.

Hilary Term 2026 Strachey Lecture with Professor Ion Stoica, An AI stack: from scaling AI workloads to evaluating LLMs Large language models (LLMs) have taken the world by storm, enabling new applications, intensifying GPU shortages, and raising concerns about the accuracy of their outputs. In this talk, I will present several projects I have worked on to address these challenges. Specifically, I will focus on Ray, a distributed framework for scaling AI workloads, vLLM and SGLang, two high-throughput inference engines for LLMs, and LMArena, a platform for accurate LLM benchmarking. I will conclude with key lessons learned and outline directions for future research.

MT25 Strachey Lecture - Professor Rafail Ostrovsky: Advances in Garbled Circuits Nearly 40 years ago, Andy Yao proposed the construction of “Garbled Circuits,” which had an enormous impact on the field of secure computation -- both in theory and in practice. In Garbled Circuits, two parties agree on a Boolean circuit that they want to evaluate, where both parties have partial, disjoint inputs to the circuit, and neither party is willing to disclose to the other party anything but the output. In this talk, I will survey the state of the art for garbling schemes, including computing with Garbled Random Access Memory, the so-called GRAM constructions that were invented by Lu and Ostrovsky in 2013, as well as more recent progress, including the GRAM paper by Heath, Kolesnikov and Ostrovsky, which received the best paper award in Eurocrypt 2022. I will also discuss Garbled Circuits in the malicious setting, where parties try to deviate arbitrarily from the prescribed protocol execution to gain additional information, and will review some of the latest advances in this area. The talk will be self-contained and accessible to the general audience.

Kevin Buzzard: Will Computers prove theorems? Will computers one day replace human mathematicians? Is this just around the corner, or decades away? Can neural networks spot patterns which humans have missed? Currently language models are great for brainstorming big ideas but are very poor when it comes to details. Can integrating a language model with a theorem prover like Lean solve these problems? Is the modern mathematical literature riddled with errors, and is it feasible to hope that a machine might find and even fix them? Is it possible to teach a computer the proof of Fermat's Last Theorem? And what do mathematicians make of all this? I'll talk about how modern developments in AI and theorem provers are beginning to affect mathematics.

Leo De Moura: Formalizing the Future: Lean’s Impact on Mathematics, Programming, and AI How can mathematicians, software developers, and AI systems work together with complete confidence in each other’s contributions? The open-source Lean proof assistant and programming language provides an answer, offering a rigorous framework where proofs and programs are machine-checkable, shared, and extended by a broad community of collaborators. By removing the traditional reliance on trust-based verification and manual oversight, Lean not only accelerates research and development but also redefines how we collaborate. In this talk, I will highlight how Lean is being used to tackle challenging problems in mathematics, software verification, and AI research that depends on formally sound reasoning. I will also introduce the Lean Focused Research Organization (FRO), a non-profit dedicated to expanding Lean’s capabilities and community. By showcasing real-world examples, ranging from advanced research projects to industry-driven applications, I illustrate how Lean empowers us to innovate in a more reliable, transparent, and truly collective manner.