[Turing-Southampton] REMINDER: Turing Fellow Research Project Presentations | Still time to register

[Susan Davies]

***apologies if you receive this more than once***

As part of the Turing Fellow Research Projects event series taking place across the Institute's university partner network, I'm pleased to share details of the final two presentations being hosted by our Southampton Fellows in collaboration with The University of Manchester.

Details and registration links for the events are below.



Wednesday 3 November, 13:15-14:30

Register here<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fus02web.zoom.us%2Fwebinar%2Fregister%2FWN_XeILjhwERlGOKKaHc9TI_w&data=04%7C01%7Csdd1%40soton.ac.uk%7C8410aab42fc34f9140c108d9989b4123%7C4a5378f929f44d3ebe89669d03ada9d8%7C0%7C0%7C637708614860188613%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=6lKYZr6Rrfht6xQ3pZO8IZIlumKrTwMtWH2Iz6hPj5Q%3D&reserved=0>



Data science approaches to applied mathematical modelling

Marika Taylor<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.turing.ac.uk%2Fpeople%2Fresearchers%2Fmarika-taylor&data=04%7C01%7Csdd1%40soton.ac.uk%7C8410aab42fc34f9140c108d9989b4123%7C4a5378f929f44d3ebe89669d03ada9d8%7C0%7C0%7C637708614860198605%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=QuSFHhRjZB4qhesDvghbZ0AQm5qjkg37%2BC%2F0M4CYXIM%3D&reserved=0>

In this talk Marika Taylor will describe new relationships between tessellations and codes used for quantum error correction, focussing on tessellations of negatively curved (hyperbolic) spaces. The motivations for constructing such codes will be explored - these range from fundamental physics to understanding the geometry underlying quantum machine learning.



Jazz as Social Machine

Thomas Irvine<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.turing.ac.uk%2Fpeople%2Fresearchers%2Fthomas-irvine&data=04%7C01%7Csdd1%40soton.ac.uk%7C8410aab42fc34f9140c108d9989b4123%7C4a5378f929f44d3ebe89669d03ada9d8%7C0%7C0%7C637708614860198605%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=cpYochVqWa%2BEcIWqc%2Bbpp8heaupc6yjGJeitNAgDKfg%3D&reserved=0>

Making jazz with machine learning agents turns out to be complicated. Using insights from Web Science, Science and Technology Studies and musicological jazz studies, I survey the techniques currently in use, and explore what it is about jazz's data that makes machine learning jazz more of a "social" problem than other challenges in the growing field of Music Information Retrieval.



Tuesday 23 November, 14:00-15:30

Joint with The University of Manchester

Register here<https://teams.microsoft.com/registration/-XhTSvQpPk2-iWadA62p2A,1bh6qC4isUeT-gmiMP7McA,tfrNasdn50-4SBzv6YT4tw,bim-TalsAUSNJvHouy6iYg,zLVSjJcH4Eqt2ilJ3rgl2g,u3tnKBmtu0auqx8zwV8YFQ?mode=read&tenantId=4a5378f9-29f4-4d3e-be89-669d03ada9d8>



A Multidisciplinary Study of Predictive Artificial Intelligence Technologies in the Criminal Justice System

Pamela Ugwudike<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.turing.ac.uk%2Fpeople%2Fresearchers%2Fpamela-ugwudike&data=04%7C01%7Csdd1%40soton.ac.uk%7C8410aab42fc34f9140c108d9989b4123%7C4a5378f929f44d3ebe89669d03ada9d8%7C0%7C0%7C637708614860208600%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=pjuk0qoASi62CrrDMXMKHBvMF8GmmpJihS%2BT5I6wYdM%3D&reserved=0>
The project explored a classic predictive policing algorithm to investigate conduits of bias. Whilst many studies on real data have shown that predictive policing algorithms can create biased feedback loops, few studies have systematically explored whether this is the result of legacy data, or the algorithmic model itself. To advance the empirical literature, this project designed a framework for testing predictive models for biases. With the framework, the project created and tested: (1) a computational model that replicates the published version of a predictive policing algorithm, and (2) statistically representative, biased and unbiased synthetic crime datasets, which were used to run large-scale tests of the computational model. The study found evidence of self-reinforcing properties



Topology and neural networks generalisations

Jacek Brodzki<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.turing.ac.uk%2Fpeople%2Fresearchers%2Fjacek-brodzki&data=04%7C01%7Csdd1%40soton.ac.uk%7C8410aab42fc34f9140c108d9989b4123%7C4a5378f929f44d3ebe89669d03ada9d8%7C0%7C0%7C637708614860208600%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=VSBFUJDcvpcIJmaJujXVtU60AxvqyQF7ksxeWlILFyk%3D&reserved=0>

Neural networks are at the centre of many remarkable applications of AI. These powerful classification tools are great when they work well, but have demonstrated weaknesses where they fail at surprisingly easy tasks. This talk will summarise the results of our pilot project devoted to the study of the geometry of the decision boundaries of neural networks as a predictor for their performance.



Anonymisation and Provenance: Expression Data Environments With PROV

Adriane Chapman<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.turing.ac.uk%2Fpeople%2Fresearchers%2Fadriane-chapman&data=04%7C01%7Csdd1%40soton.ac.uk%7C8410aab42fc34f9140c108d9989b4123%7C4a5378f929f44d3ebe89669d03ada9d8%7C0%7C0%7C637708614860218593%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=2N1KdQNNkqERNv3f5KDgQlMqEissg48p6lC4IWAgTDY%3D&reserved=0> and Mark Elliot<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.research.manchester.ac.uk%2Fportal%2Fmark.elliot.html&data=04%7C01%7Csdd1%40soton.ac.uk%7C8410aab42fc34f9140c108d9989b4123%7C4a5378f929f44d3ebe89669d03ada9d8%7C0%7C0%7C637708614860218593%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=f3afeq42EtdBiXtCvCCFT076XjvjyUusyT31EhAt12Q%3D&reserved=0>, The University of Manchester
The Anonymisation Decision-Making Framework (ADF) is a comprehensive practice designed for assessing and controlling the risks of sharing and disseminating data. This project examines how to use provenance to support anonymization decision-making. To enable this, we analyze the mapping of concepts between ADF and prov. We have operationalized provenance into the framework, and analyse the suitability via real use cases. We have created prototype tool support from simulators to reasoners.

Background
In 2018 over 300 Turing Fellows were appointed at the Institute following an open call. Some of these received additional funding to deliver research projects that have had substantial impact in the areas of data science and artificial intelligence. The Institute and its university partners are delighted to host the events which will showcase the breadth of research and demonstrate the impact of these research projects. Events will be added to the website over the coming weeks, visit regularly for more information.

Details of all university partner presentations and how to register can be found here<https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.turing.ac.uk%2Fpresenting-turing-fellow-research-projects&data=04%7C01%7Csdd1%40soton.ac.uk%7C8410aab42fc34f9140c108d9989b4123%7C4a5378f929f44d3ebe89669d03ada9d8%7C0%7C0%7C637708614860228590%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C1000&sdata=HGfzER3TPSz5bBTnQvJoFT2aMFYJIQXnqNJ8F95FzNQ%3D&reserved=0> - we look forward to seeing you there.

Please feel free to disseminate more widely.

Best wishes

Susan
_________________________________
Susan Davies
Coordination Manager, Web Science Institute<https://www.southampton.ac.uk/wsi/index.page?>
University Liaison Manager, The Alan Turing Institute<https://www.southampton.ac.uk/wsi/alan-turing-institute/alan-turing-institute.page>
Web Science Institute
University of Southampton
Southampton SO17 1BJ
M 07768 266464
https://www.southampton.ac.uk/wsi<https://www.southampton.ac.uk/wsi/index.page>

My working days are Monday to Thursday.




-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mailman.ecs.soton.ac.uk/pipermail/turing-southampton/attachments/20211101/e9886e67/attachment-0001.html