UCL Community-based Initiative Scheme 2022

Data and its analysis can enable cross-disciplinary research between silos, create new disciplines and generate impact on society. This scheme provided opportunties for early career researchers to develop their leadership skills delivering activities which enable researchers to develop their skills using research software and data.

UCL Bioimage Analysis workshop 2022

Alessandro Felder (ARC) and Giulia Paci (LMBC) The UCL Bioimage Analysis Interest Group organises activities to foster connection, exchange knowledge and promote good practiceacross UCL’s biologicaland medical image analysis community. TheInterest Group is an informal and welcoming community, connecting image analysis aficionados from a variety of backgrounds and levels of seniority. Each month we host two speakers for informal talks(typically early career researchers), where people can share and discuss their image analysis tools and pipelines. The community also interacts through a Slack channel. With the funding from this call, we will organize a two-day UCL Bioimage Analysis workshop in summer 2022.The first day (to be heldin a hybrid format) will include akeynote by an image analysis expert,a showcase of workby UCL collaborative teams who were awarded CZI grants in 2021 to develop image analysistoolsand flashtalks by members of the community. We willconclude the first day with a face-to-face social eventand deliberation/pitchingof ideas for day 2.The second day will be inspired by the successful UCL Festival of Code Hackday in 2021, where newly formed teams will collaborate on an image analysis problem of their choice. Overall, the UCL Bioimage Analysis workshop will provide an opportunity to widen engagementacross UCL andfoster further networking among community members. It will also offer an entry point to custom image analysis pipelines (e.g. in Python) for life science researchers and promote the adoption of good coding practices

UCL R Project Showcase 2022

Ellen Webborn (UCL Energy Institute); Scott Orr (Institute of Sustainable Heritage)

The UCL R Project Showcase 2022 will bring R users together from across UCL for a free half-day hybrid (online and in-person) event in June 2022. It will showcase the work of Master’s and PhD students and Early-Career Researchers (ECRs) through short talks on projects using R to the attendees and a panel of judges for a chance to win a £50 prize. A keynote speaker from industry or government will demonstrate the role of R in their work and inspire the UCL community to further develop their R skills for their own work.

This event builds on the success of our previous R Project Showcase (June 2021) sponsored by eResearch. Whereas last year’s event had to be online, this year we hope to bring people together in person for a hybrid event. We hope that this will establish the showcase as an annual event we can run every year, to bring people together from across the university and inspire new R users.

The UCL R user group is a friendly community of students and staff who use R within their research and studies, or are interested in how they might do so. We hold a monthly meeting to exchange experiences, meet fellow R users, ask questions and find new inspiration for our R projects. This is currently the only R-specific programming group within UCL. Last year’s event was very well attended and we got very positive feedback from attendees and presenters. We hope that holding it again we can improve on the experience we were able to provide last year and strengthen the R community at UCL.

UCL Code Clubs 2022

Tereza Masonou (ICH) and Rini Veeravalli (IHI)

The UCL Code Clubs are collaborative initiatives run by early career researchers aiming to teachand promote good coding practice within research communities, based at Institute of HealthInformatics (IHI) and Institute of Child Health (ICH). Since 2019, we have successfully runcommunity-driven events across the two institutes, including workshops, troubleshooting sessions,coding challenges, IHI summer work experience 2021, and the IHI Code Club Hackathon 2020+1.With the support of the eResearch Domain and Researcher-Led Initiative awards, our team hasprovided various learning opportunities to the wider UCL research communities, and promotedboth inter- and intra-departmental collaborations. With funding from this current call, we aim tocontinue fostering collaborations and upskilling our members through informative and interactiveexperiences, starting with a Speed Code Matching social and continuing the year with regularpeer-programming sessions. These activities aim to bring our members closer together and tostrengthen their coding skills by working through specific computing tasks relevant to their work ina safe and friendly environment. We will also continue our dedicated workshop series invitingexperienced speakers from both internal and external UCL. Our aims this year are to facilitate members in solving work-related computing tasks, encourage peer learning between members,widen our membership across UCL and beyond, as well as finding successors to ensure thecontinuity of our communities in future.

UCL/NHNN Course: understanding artificial intelligence and machine learning

Hani J Marcus (WEISS, UCL and Department of Neurosurgery, NHNN) and Anand Pandit (High-dimensional Neurology, Institute of Neurology and Department of Neurosurgery, NHNN)

Machine learning and artificial intelligence are playing a growing role in the delivery of all aspects of healthcare, and clinical neurosciences are no exception. An understanding of the concepts underlying these technologies is necessary for medical students and those engaged in clinical neuroscience practice (neurosurgeons, neuroradiologists, neurologistsand neurophysiologists) to play a role in theirappraisal and implementation. However, courses in artificial intelligence and machine learning for healthcare are often targeted towards those from computer science/engineering backgrounds or go into much greater depth than necessary for those hoping to get a grasp of the basic concepts.Over the course of two days, our course will provideparticipants with a conceptual and intuitive understanding of commonly used machine learning tools in medical research. Seminars on the key models used in healthcare will be delivered by world-leading speakers. Participants will also have a chance to reinforce their learning through journal article discussions and interactive exerciseswhich are specifically dedicated toward algorithms used in clinical neuroscience literature. Finally, signposting to resources for future learning will be provided to ensureparticipants have an understanding of the next steps they can take in their learning. Pre-and post-course surveys will be used to improve future courses and to assess the effectiveness and feasibility of the course. The results will be written up for a publication in a peer-reviewed journal and for presentation at a national/international meeting.

UCL-NHNN Clinical Neurosciences Datathon

Anand Pandit (High-dimensional Neurology, Institute of Neurology and Department of Neurosurgery, NHNN) and Ahmed Toma (Department of Brain Repair and Rehabilitation / NHNN)

This joint UCL-NHNN Neurosurgery Datathon represents a novel, unique cross-disciplinary hackathon event designed to use data science and machine learning tools to answer important clinical neuroscience questions. Forging collaborations between medical, neuroscience and psychology students, computer scientists and trainee surgeons, this weekend event aims to analyse clinical and imaging data with the objective of determining factors which are associated with raised intracranial pressure: an impending sign portendingirreversible neurological injury and who require urgent treatment.Using the ‘datathon’ model, the cross-collaboration will involve several opportunities for skill sharing, including but notlimited to: digital literature critical appraisal, computational neuroimaging methods, analysis of multivariate data sets and data visualisation. With the overall datathon goal of generating pilot results for conference presentation and publication, this event would be the first of its kind in the clinical neuroscience community world-wide.