Multi-scale and Multi-modality Digital Health Collaboration Workshop
Join us for a one-day event sponsored by The Alan Turing Institute to encourage interdisciplinary collaboration in digital health:
Date and Time
Tuesday 18 July 2023, 9:30 - 18:00 BST
Registration
Registration is now open via Eventbrite.
Location
Clark Kennedy Lecture Theatre, Queen Mary BioEnterprises Innovation Centre, 42 New Rd, London E1 2AX
Agenda
| 09:45 | Welcome Breakfast & Registration |
| 10:00 |
Speakers Topic 1: Physics based-models and machine learning Chair: Caroline Roney Yi Sui (QMUL): Real-time mechanical characterisation of microcapsules and biological cells Gary Zhang (UCL): Model-based quantitative MRI meets machine learning Marta Varela (ICL): Physics-Informed Neural Networks: Marrying Maths and Data for Personalised Healthcare Chris Harbron (Roche): Turing-Roche Strategic Partnership: A Multi-Scale, Multi-Modal, Multiple Topics, Multi-Organisation Partnership |
| 11:00 | Break |
| 11:30 |
Speakers Topic 2: Different data modalities: from cellular basic science to organ-scale clinical Chair: Giorgia Bosi Steve Niederer (ICL): Cardiac Digital Twins Sophia Bano (UCL): Surgical AI for Next Generation Interventions Mine Orlu (UCL): Machine learning for formulating next generation of therapeutics Manish Patel (Jiva.ai): Multimodal AI solutions in healthcare and bridging the gaps in scale |
| 12:30 | Networking Lunch |
| 13:30 |
Speaker Topic 3: Digital health in practice Chair: Greg Slabaugh Aldo Faisal (ICL): Behavioural Transcriptomics Karla Sanchez (Cambridge Design Partnership): Digital Health Adoption: An Industry Perspective Pat Healey (QMUL): Social Health Patrik Bachtiger (ICL): Towards a Tricorder |
| 14:30 |
Sandpit Session: (email: c.roney@qmul.ac.uk to pitch!) Chair: Guang Yang Tina Chowdhury & Zara Arain (QMUL): Air pollution effects on preterm birth Jiahao Huang (ICL): Deep Learning-based MRI Reconstruction. Lei Li (Oxford): Towards Enabling Cardiac Digital Twins of Myocardial Infarction Using Deep Computational Models for Inverse Inference Julia Camps (Oxford): Digital twin generation Xiaodan Xing (ICL): How to evaluate the quality of synthetic images effectively Jenny Wang (Oxford): In silico trials in ventricles Albert Dasi (Oxford): Atrial in silico trials Alexander Zolotarev (QMUL): Atrial Fibrosis Distribution Generation based on the Diffusion Model Youssef Abdalla (UCL): Predicting 3D printability using Machine Learning |
| 15:30 | Break |
| 16:00 |
Career session: Digital health and AI opportunities Panellists include: Courtney Bishop (GE HealthCare), Patrik Bachtiger (ICL), Mike Barnes (QMUL), Guang Yang (ICL), Karla Sanchez (Cambridge Design Partnership). |
| 17:00 | Refreshments and Networking |
About this event
This one-date workshop is funded by The Alan Turing Institute and jointly hosted by Queen Mary University London, UCL, and Imperial College London.
The event will take place on the Whitechapel Campus at Queen Mary University London: Clark Kennedy Lecture Theatre, QMUL Innovation Building
The workshop will be composed of talks, a sandpit event, and a careers focused panel discussion, with further details noted in the agenda , above.
The objective is to bring together researchers from academia and industry working with different data modalities and spatio-temporal scales, in different environments including basic science, clinical, engineering, and digital health industry. We hope to initiate new collaborations, exchange ideas and research techniques.
Digital health is a rapidly growing field. To personalize treatment approaches through digital health, we need to utilize all available data to provide mechanistic understanding and inform therapies at the patient-specific and population level. These data are collected using different modalities, at widely different spatio-temporal scales, creating large challenges and opportunities in Digital Health. This event aims to bring together researchers working with data across different scales and modalities, from basic scientists and clinicians, through to industry, using different types of computational techniques, from physics-based models to machine learning and digital health in industry. We will motivate exciting areas of development through a series of talks and posters, and then have sandpit sessions with a series of short pitches, with the aim of initiating new collaborations.
Support towards the costs associated with attending the event (i.e. travel, accommodation, childcare) can be applied for. Priority for support will be given to our speakers, early career researchers and PhD students, and those who are geographically located outside of London.
This event has been organised in association with the Digital Environment Research Institute (DERI) at Queen Mary University London.