Alec Sargood

PhD Researcher @ UCL. Generative Models, Inference-Time Steering and Computer Vision.

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Hawkes Institute, UCL
London, UK
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I am an applied mathematician and PhD researcher in Computer Science at University College London (UCL), based in the Hawkes Institute. I am also a research intern at InstaDeep, working on the guidance and steering of generative models.

My research focuses on the theory and development of generative models, particularly diffusion and flow models, including few-step approaches. I am especially interested in how we can control and adapt pretrained models at inference time, using guidance, rewards and feedback to steer generation and shape output distributions. My work spans mathematical analysis and practical methods, with applications in image synthesis, medical imaging, inverse problems, and AI4Science.

Open to collaboration: I am always keen to discuss ideas and collaborations in generative modelling, inference-time steering and image generation. Feel free to get in touch!

Prior to my PhD, I completed an MRes at the University of Cambridge, an MSc in Mathematical Modelling and Scientific Computing at the University of Oxford, and a BSc in Mathematics at the University of Exeter.

news

Oct 01, 2026 Part of my research work at InstaDeep Steered Not Stirred: Effective Reward Tilting using Surrogate Reward Mixing has been accepted at NeurIPS 2026 STODY workshop. Explore the project page.
Mar 24, 2026 I’m excited to share that I’ll be starting a 6-month PhD Research Internship at InstaDeep in London! I will be joining the team to focus on the guidance and steering of generative models!
Feb 20, 2026 Thrilled to share that our paper GenTract: Generative Global Tractography has been accepted at CVPR 2026 as a highlight paper.

recent publications

2026

  1. Steered Not Stirred: Effective Reward Tilting using Surrogate Reward Mixing
    Alec Sargood, Olivia Gallup, Georg Maierhofer, Noam Ghenassia, Paul Duckworth, Krisztina Sinkovics, and Avishek Joey Bose
    arXiv preprint, 2026
  2. GenTract: Generative Global Tractography
    A. Sargood, L. Puglisi, E. Thompson, M. Musolesi, and D. C. Alexander
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026
    Highlight Award
  3. CoCoLIT: ControlNet-Conditioned Latent Image Translation for MRI to Amyloid PET Synthesis
    A. Sargood*, L. Puglisi*, J. H. Cole, N. P. Oxtoby, D. Ravi, and D. C. Alexander
    In Proceedings of the AAAI Conference on Artificial Intelligence, 2026
    * denotes joint first authorship (equal contribution).