Distinguished Colloquium

The new series of departmental colloquia will be of interest to all academic staff, postdoctoral researchers and PhD students. Contact Karl-Mikael Perfekt for further information.

9 November 2018

16:00 - 17:00 (M113)

Speaker:  Carola-Bibiane Schönlieb (Cambridge)

Title:        Deep and shallow learning approaches for regularised inversion in imaging

Abstract: In this talk we discuss the idea of data-driven regularisers for inverse imaging problems, investigating two parametrisation: total variation type regularisers and deep neural networks. This talk is based on joint works with J. C. De Los Reyes, L. Calatroni, C. Chung, T. Valkonen, S. Lunz and O. Oektem.

Carola-Bibiane works in image processing and PDE. She won the Whitehead prize in 2016 "for her spectacular contributions to the mathematics of image analysis", and the Philip Leverhulme Prize in 2017.

 

3 March 2017

13:00 - 14:00 (M113)

Speaker:   Daniel Lawson (University of Bristol)

Theme:    Genetics for Mathematicians

Title:        The mathematics behind fine-scale personal ancestry inference,
        and what it can tell
 us      

AbstractPersonal Genomics is a booming industry and allows people to go on a discovery process for their own history. The methods behind it allow for a discovery process for whole a population and can inform fields such as history[1], archaeology[2] and sociology. In this talk we discuss the underlying genetics models and how they are related to (but more complex than) the well studied problem of clustering a graph.

We will compare two recent advances that allow extremely accurate personal ancestry inference. The first, recently released by Ancestry DNA [3] uses hundreds of thousands of samples with known location and uses graph heuristics to achieve geographical localisation. The second, developed by ourselves [4], uses careful algorithms on fewer samples to achieve similar clustering. This is based on the "Stochastic Block Model" which is a generative description of a graph. A number of approaches to inference are avaiable, including Markov-Chain Monte Carlo and algorithmic approaches such as maximising modularity. We will discuss their relative merits, as well as extensions to the model to allow nodes to be mixtures of the blocks, called the mixed membership model. This has great importance in genetics because it describes admixture, i.e. what proportion of a genome is from different regions.

Scaling these models, and the improvements in accuracy that scale provides, is invaluable in genetics, and we will describe some of the very exciting consequences of having this methodology available, which range from the practical (personal genomics) to the bizarre (what we can learn about 1700s social class from the amorous congress of Captain Cook's crew in the Society Islands).

[1] Leslie et al 2015, Nature 519:309-314

[2] Pagani & Lawson et al 2016 Nature 538:238-242

[3] Han et al 2017 Nat Comms 8:14238

[4] Lawson et al 2012, PLoS Genet. 8:e1002453

   

21 February 2017

13:00 - 14:00 (RH Theatre, JJ Thomson Building)

Speaker:  Lara Alcock (Loughborough)

Title:       Tilting the Classroom: Engaging Students in Large Lectures

Abstract:  There is much discussion currently about flipping the classroom or otherwise making dramatic adjustments to teaching. But for most lecturers, especially those with large classes, this is not practical. My view is that lectures are not inherently bad, and that that there are numerous ways to make them more engaging without dramatic changes.

This talk will be about 18 approaches that I use - these work well together, but each can be implemented independently so they can be tried out according to personal taste. There will be lots of examples and some light-touch discussion of how this approach relates to evidence from psychological research on learning.

The talk will be followed by coffee and cake in the Common Room where you'll have the opportunity to chat with Lara. 

Things to do now

Contact us

  • Email:
    maths@reading.ac.uk

  • Telephone:
    +44 (0) 118 378 8996

  • Department of Mathematics and Statistics, Whiteknights, PO Box 220, Reading RG6 6AX, UK

Page navigation

See also

 

Search Form

A-Z lists