Bath Numerical Analysis Seminar

Fridays at 12.15 at Wolfson 4W 1.7. All talks will be broadcast on Zoom.

Link to Zoom meeting

Everyone is welcome at these talks.

Date Speaker Title
6 Feb 2026 Pranav Singh (University of Bath)
13 Feb 2026 Mike Giles (University of Oxford)
20 Feb 2026 Malena Sabaté Landman (University of Bath)
27 Feb 2026 Lea Bogensperger (University of Zurich)
6 Mar 2026 Wenqi Zhu (University of Oxford)
13 Mar 2026 Georgios Exarchakis (University of Bath)
20 Mar 2026 Daniel Burrows (IMI and University of Bath)
Motion-enabled tomography via Gaussian Mixture Models

Recovering the physical properties of objects in motion is a fundamental challenge across various scientific and industrial applications. When motion is sufficient to provide a fully informative sinogram relative to a fixed source-receiver system, Computerised Tomography (CT) offers a powerful means for recovering object properties, enabling automation and access to otherwise hidden information. To address this, we propose a general time-varying parametric model for Gaussian Mixture Models (GMMs) that explicitly describes angular velocity, projectile motion, and morphology specific to each constituent Gaussian. Leveraging the closure of GMMs under the ray transform, we derive an exact forward model that allows for reconstruction by fitting directly to observed sinogram data. The utility of using GMMs as a basis for reconstruction comes from their ability to approximate complicated mathematical functions with a high degree of accuracy [Zickert, Öktem, Yarman, 2022] [Zickert, Yarman, 2021].

To implement this reconstruction, we utilize suitable loss functions and the automatic differentiation capabilities of PyTorch to efficiently compute parameter estimates that characterise the approximating GMMs. Alongside motion and tomography models applicable to Euclidean spaces of arbitrary dimension, we provide a fully operational gradient-based optimization algorithm tailored for two-dimensional scenarios. Our results demonstrate accurate and robust performance on challenging simulated datasets, providing a credible foundation for extending the algorithm to arbitrary dimensions.
27 Mar 2026 Kamran Arora (University of Bath)
17 Apr 2026 Amin Sabir (University of Bath)
24 Apr 2026 Mostafa Meliani (University of Bath)
24 Apr 2026 María Ignacia Fierro-Piccardo (University of Bath)
1 May 2026 Massimiliano Tamborrino (University of Warwick)
Subscribe to seminar calendar

You can subscribe to the NA calendar directly from your calendar client, including Outlook, Apple’s iCalendar or Google calendar. The web address of the calendar is this ICS link which you will need to copy.

To subscribe to a calendar in Outlook:

  1. In Calendar view, select “Add Calendar” (large green +)
  2. Select “From Internet”
  3. Copy paste the ICS link, click OK, and click Yes to subscribe.

To subscribe to a calendar in iCalendar, please follow these instructions. Copy paste the ICS link in “web address”.

To subscribe to a calendar in Google Calendar:

  1. Go to link.
  2. On the left side go to "Other Calendars" and click on the dropdown.
  3. Choose "Add by URL".
  4. Copy paste the ICS link in the URL of the calendar.
  5. Click on "Add Calendar" and wait for Google to import your events. This creates a calendar with a somewhat unreadable name.
  6. To give a readable name to the calendar, click on the three vertical dots sign next to the newly created calendar and select Settings.
  7. Choose a name for the calendar, eg. Numerical Analysis @ Bath, and click back button on top left.

How to get to Bath See here for instructions how to get to Bath. Please email James Foster (jmf68@bath.ac.uk) if you intend to come by car and require a parking permit for Bath University Campus for the day.
Tips for giving talks

Tips for new students on giving talks

Since the audience of the NA seminar contains both PhD students and staff with quite wide interests and backgrounds, the following are some guidelines/hints to make sure people don't give you evil looks at lunch afterwards.

Before too much time passes in your talk, ideally the audience should know the answers to the following 4 questions:

  • What is the problem you're considering?
  • Why do you find this interesting?
  • What has been done before on this problem/what's the background?
  • What is your approach/what are you going to talk about?

There are lots of different ways to communicate this information. One way, if you're doing a slide show, could be for the first 4 slides to cover these 4 questions; although in this case you may want to revisit these points later on in the talk (e.g. to give more detail).

Remember:

  • "vertebrate style" (structure hidden inside - like the skeleton of a vertebrate) = good for detective stories, bad for maths talks.
  • "crustacean style" (structure visible from outside - like the skeleton of a crustacean) = bad for detective stories, good for maths talks.

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