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.