Sean Holden
Sean Holden is a Cambridge computer scientist whose research connects machine learning with automated theorem proving. He earned engineering degrees at East Anglia and Cambridge, did postdoctoral research in London and Cambridge, taught at UCL, and joined Cambridge's Department of Computer Science and Technology in 2002. His Connect++ prover supports machine-learning experiments in automated theorem proving; he presented a talk on SAT solvers in 2025 and coauthored a paper for the Vampire Workshop in 2026. As of October 2026, he is University Associate Professor of Computer Science at Cambridge and a Fellow and Director of Studies at Trinity College.
- Works
- 94
- Citations
- 1,582
- h-index
- 16
Publication numbers from OpenAlex, as of 27 October 2026.
Timeline
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1989
An engineering degree
He earns a BSc in Electronic Systems Engineering at the University of East Anglia in 1989.
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1994
A Cambridge engineering PhD
After joining Cambridge's Signal Processing and Communications Group, he completes a PhD in Engineering at Corpus Christi College in 1994.
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By 1995
Postdoctoral research in London and Cambridge
Before joining UCL in 1995, he conducts postdoctoral research at King's College London's Signals, Circuits and Systems Research Group and Cambridge's Speech, Vision and Robotics Group.
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1995–2002
Lecturing at UCL
He joins UCL's Department of Computer Science as a Lecturer in 1995 and sets up its advanced MSc in Intelligent Systems. He leaves in September 2002 as a Senior Lecturer.
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October 2002
Cambridge and Trinity roles
In October 2002, he joins Cambridge's Department of Computer Science and Technology as a Lecturer in Machine Learning. His roles include Senior Lecturer in Machine Learning and Fellow and Director of Studies in Computer Science at Trinity College.
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September 2023
The Connect++ theorem prover
In September 2023, he publishes a paper on Connect++, a C++ connection prover designed to support machine-learning experiments in automated theorem proving.
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August 2025
A SAT solver talk
In August 2025, he presents “Applying Machine Learning to Improve SAT Solvers: Some Highlights” at the Machine Learning for Solvers and Provers workshop. He works on machine learning for automated theorem proving and is responsible for the Connect++ connection prover.
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2026
A Vampire Workshop paper
In 2026, he coauthors “Reset Early, Reset Often, Eliminate Models” with Martin S. Fixman and Fredrik Rømming for the 9th Vampire Workshop.
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As of October 2026
Associate Professor at Cambridge
As of October 2026, he is University Associate Professor of Computer Science at Cambridge, a Fellow of Trinity College and its Director of Studies in Computer Science. His current research combines machine learning with automated theorem proving. His earlier publications cover Bayesian inference, drug design and organelle proteomics.
Career
- Since 2002Trinity College, University of CambridgeFellow
- NowUniversity of CambridgeUniversity Associate Professor of Computer Science
- NowTrinity College, University of CambridgeDirector of Studies in Computer Science
- Until 2002University College LondonSenior Lecturer
- From 2002University of CambridgeLecturer in Machine Learning
- From 1995University College LondonLecturer
- King's College LondonPostdoctoral Researcher in the Signals, Circuits and Systems Research Group
- University of CambridgePostdoctoral Researcher in the Speech, Vision and Robotics Group
- University of CambridgeSenior Lecturer in Machine Learning
Education
- 1994University of CambridgePhD in Engineering
- 1989University of East AngliaBSc in Electronic Systems Engineering
Colleagues
Sources and credits
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