## Z

:::{profile} Zeena Shawa
---
roles: |
    PhD student (2021-Present);
    Book Dash Participant (June 2024);
    Turing-Roche Community Scholar (October 2023-2024)
github: Zeena-Shawa
bio: |
    Zeena Shawa is PhD student in the i4Health Medical Imaging CDT programme at University College London.
    She is part of the Progression of Neurodegenerative Diseases (POND) Group in the Centre for Medical Image Computing (CMIC), supervised by Dr. Neil Oxtoby and Dr. Rimona Weil.
    Her PhD project aims at understanding Parkinson’s disease progression using machine learning approaches developed within POND, with a focus on medical imaging data.
    The insights obtained from this can aid in understanding disease mechanisms, identifying biomarkers associated with disease progression and thus potentially providing targets for therapeutic development.

    Zeena was an Enrichment Student at the Alan Turing Institute, where she first engaged with the Turing-Roche Partnership and started looking at imputing missing data.
    She was also part of the 2023/2024 Turing-Roche Partnership Community Scholar Scheme.
highlights: |
    The main aim of my Turing-Roche Community Scholar project, was to create the {ref}`pd-missing-data` Chapter in the Turing Way handbook, consolidating what I learned during the [Turing Enrichment Scheme](https://www.turing.ac.uk/work-turing/studentships/enrichment) (and more) with current research of the [Turing-Roche Partnership](https://www.turing.ac.uk/research/research-projects/alan-turing-institute-roche-strategic-partnership).
    Imputing and data missingness is an important aspect of a lot of research, due to missing data being a common problem, especially in large cross-cohort multimodal datasets.

    A main highlight of this project was completing the chapter and then doing a live merge in a Collaboration Cafe, which also happened to be a Book Dash Q&A session.
    It was also great to have the Chapter reviewed by [Vicky Hellon](https://github.com/vhellon).
---
:::

:::{profile} Zoë Turner
---
roles: |
    Fellow in NHS-R Community and Community Leader
github: Lextuga007
bio: |
    I’m a Senior Data Scientist at the Midlands Decision Support Network which is part of the NHS Midlands & Lancashire Commissioning Strategy Unit.
    I've been an analyst in the NHS and public sector for over 10 years and have been an active member and now proud Fellow of the NHS-R Community helping to run its activities since 2023.
    I also have a particular interest in Ethics, having studied Philosophy, and some of my thoughts on this, along with technical blogs, can be found on my [blog site](https://philosopher-analyst.netlify.app/).
highlights: |
    I started the Quarto book [NHS-R Community Way](https://nhsrway.nhsrcommunity.com/) closely following The Turing Way but used the format to document the NHS-R Community.
    I wanted to put into the open all the detail that makes a community run where every person can be responsible and contribute, just like The Turing Way.
    I promote The Turing Way because so much of the contributed work in it is as appropriate to analysis in the public sector as it is to research and I was consequently delighted to host a lightning talk from Sophia Batchelor at the 2024 RPySoc conference on The Turing Way.
quote: |
    The Turing Way has been both inspirational and a support working in an open way and documenting everything.
    It's not just a repository of knowledge but a shining example of how a cultural shift to community ownership can transform how we get that knowledge out into the public domain where anyone can benefit from it.
    I've learned so much about how to engage a community from The Turing Way and particularly have appreciated how GitHub issues have been used to get community input on all manner of subjects including the experiences of others in how to host events and what software has worked and why.
    These discussions are so often hidden and people never get a chance to contribute or miss the time it is discussed so it was enlightning to see this approach from The Turing Way and one that I've since copied in the NHS-R Community.
---
:::