This series covers the Strachey Lectures, a series of termly computer science lectures named after Christopher Strachey, the first Professor of Computation at the University of Oxford.
Hosted by the Department of Computer Science, University of Oxford, the Strachey Lectures began in 1995 and have included many distinguished speakers over the years. The Strachey Lectures are generously supported by OxFORD Asset Management.
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.
15 May 2025
Will Computers prove theorems?
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.
15 May 2025
Formalizing the Future: Lean’s Impact on Mathematics, Programming, and AI
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.
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