Computing Science and Mathematics Seminars,
Autumn 2022

Unless otherwise state, seminars will take place in Room 4B96, Cottrell Building, University of Stirling from 15.00 to 16.00 on Friday afternoons, followed by informal discussions.

If you would like to give or suggest a seminar talk, or if you need more information,  
please contact the seminar organiser .

Autumn 2022

Date Speaker Title/Abstract
9:30 -- 17:00
INTO lecture theatre
21 September
LMS Women in Mathematics Day

28 September
Note different day!
Vincenzo Vespri, University of Florence, Italy Financial markets, how is the best way to simulate them?

The probability distribution underlying the performance of the financial markets is not a Guassian one. This implies that mathematical methods for describing market trends either do not always describe financial phenomena well or are too complicated to be implemented. One procedure is to study the probability distribution empirically, simulate it and obtain projections of future behaviors using the Montercarlo method. In this talk, we will talk about the advantages and disadvantages of this very practical approach.

Speaker bio: Vincenzo Vespri is Full Professor in Mathematics at the University of Florence, previously professor at the University of L’Aquila, Pavia, Milano and Tor Vergata-Rome, as well as visiting professor in various universities in US, Europe, Australia, and South America. His work concerns the existence and the regularity of solution to nonlinear equations arising from Mathematical Physics and the application of Functional Analysis to evolution equations. In the last years the research interests were directed also to Mathematical Models and to applications to Finance, Industrial Mathematics and Blockchains (Cryptography). His research has been published in more than 130 scientific papers.
7 October

14 October

21 October
Gavin Abernethy, University of Stirling Stability in ecological meta-community models

How can mathematical models represent the interaction of species populations in a spatially-explicit environment, and simulate the assembly of these meta-communities through the interaction between ecological and evolutionary processes? This talk will discuss a variety of model types for ecological communities and populations in space, and in particular describe an eco-evolutionary model that simulates their formation from an initial species. We will investigate the stability of the resulting network of populations against perturbations such as invasion or extinction of species, or alterations to the spatial network by patch removal, and how thus consider how these models can be applied to questions of biodiversity conservation.

Speaker bio: Dr Gavin Abernethy is a lecturer in mathematics at the University of Stirling, recently joined from Sheffield Hallam University where he was a lecturer in engineering mathematics for the four years since receiving his PhD from the Ulster University. His research interests include applied dynamical systems theory, complex networks, and simulating population dynamics on networks with applications to ecology and epidemiology. He originally studied mathematics at the University of St Andrews, and is glad to be back in beautiful Scotland!
28 October
No seminar - reading week

4 November

11 November
Wen-shin Lee, University of Stirling From computer algebra to signal processing: sparse interpolation, rational approximation, exponential analysis and tensor decomposition

A mathematical model is called sparse if it can be represented by only a few non-zero terms. The aim of sparse interpolation is to determine such a model from a small amount of data samples. Sparse techniques solve the problem statement from a number of samples proportional to the number of terms in the representation rather than the number of available data points or available generating elements. Sparse representations reduce the complexity in several ways: data collection, algorithmic complexity, model complexity.

In this talk, we will introduce sparse polynomial interpolation and the connections between sparse interpolation, generalized eigenvalue computation, exponential analysis, rational approximation, and tensor decomposition.
Speaker bio: Wen-shin Lee earned her bachelor’s degree in mathematics from National Taiwan University and PhD in computational mathematics from North Carolina State University (USA). In 2018, she joined Stirling as a lecturer in mathematics. Prior to this, she was with the University Antwerp (Belgium), INRIA-French National Institute for Research in Computer Science and Control and the University of Waterloo (Canada). She has a research background in computer algebra and is specialised in symbolic-numeric computation. A focus of her current research is on exponential analysis and its applications in signal processing.
18 November

25 November

2 December
Jefersson dos Santos, University of Stirling Large-Scale Geographic Mapping in the Wild

Automatic geographic mapping using Remote Sensing Images (RSIs) as a data source is usually modelled as a supervised classification problem. In this context, semantic segmentation or pixel-wise classification is a computer vision task that has made great strides in recent years mainly due to the emergence of new approaches based on deep convolutional networks. Remote sensing applications have also benefited from these advances. Several studies have been noted for the high level of quality obtained in the creation of geographic maps in an automated way through the use of semantic segmentation techniques. An important issue, however, is that the advances shown are generally evaluated in relatively well-controlled environments. Several challenges emerge when these approaches are employed on more specific applications, such as class imbalance, underrepresentation of some classes, and presence of pixels of unknown classes during the prediction phase.

In this talk, we will discuss computational challenges and opportunities of research in remote sensing image-based geographic mapping for real-world applications with a focus on public health and environmental monitoring. We also intend to introduce some ideas, ongoing work, and collaboration possibilities.
Speaker bio: Jefersson A. dos Santos is currently a Lecturer in Computing Science at the University of Stirling. He used to hold a position as Associate Professor at the Universidade Federal de Minas Gerais, Brazil (2013 - 2022). He got a Ph.D in Computer Science at the University of Campinas (Unicamp), Brazil, and at the University of Cergy-Pontoise, France, in 2013. He is an IEEE Senior Member. He is currently an Associate Editor for the IEEE Geoscience and Remote Sensing Letters. He used to hold the prestigious CNPq Productivity Research Scholarship (2016 - 2022). In 2021, he was awarded a competitive research grant from the Serrapilheira Institute (Brazil). His research interests include remote sensing image processing, computer vision and machine learning.
9 December

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