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Overview

This conference will address cross-sector collaborations by bringing together past and current Royal Society Industry FellowsEntrepreneurs in Residence and their collaborators.

Participants will have the opportunity to discuss issues and successes and hear about the wider work of the Society.

Organisers

Schedule


Chair

Opening remarks

Speakers

The clue is in the titles - Why Hardware is hard and why deep tech is deeply problematic

Abstract

Mark will give an overview of the offer and journey of a Deep Tech start-up, and what he would have done differently based on experience to date.

Speakers

The key stages of company creation

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Overview of our annual spinout data report and upcoming entrepreneur handbook

Speakers


Chair

What did a Royal Society Industry Fellowship ever do for me?

Speakers

Intro to my Industry Fellowship

Speakers

Entrepreneur in Residence Case studies

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Context-Aware Facial Inpainting with GANs

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Using Boron Doped Diamond for Wastewater Treatment and Disinfection

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Transforming Radiology: High Flux Field Emission for 3D Medical Imaging

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Functional Aluminium Matrix Nanocomposites

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Development of a New Blood Circulatory System Simulator

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Capillary refill time and SpO2 measurement using optical wireless pulse oximeter sensor

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Entrepreneur in Residence activity case studies

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EiR pitches

Abstract

An opportunity for EiRs to pitch collaborative projects and discuss challenges with the group.

Chair

Testing Autonomous Vehicle Perception Safety on Hardware Accelerators

Speakers

Using Light to enable Flight

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Active Controls for Sustainable Aviation

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Speakers

Thermal Metrology in Steelmaking

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Building Faster Interpreters to Reduce Cost and Energy Use of Massive Ecommerce Systems

Speakers

AI-guided solutions for early dementia prediction

Abstract

Alzheimer’s disease (AD) is characterised by a dynamic process of neurocognitive changes from normal cognition to mild cognitive impairment (MCI) and progression to dementia. However, not all individuals with MCI develop dementia. Predicting whether individuals with (MCI) or without symptoms (pre-symptomatic) will decline or remain stable is impeded by patient heterogeneity due to comorbidities that may lead to MCI diagnosis without progression to AD. Despite the importance of early diagnosis of AD for prognosis and personalised interventions, we still lack robust tools for predicting individual progression to dementia. Here, we propose a novel trajectory modelling approach that mines multimodal data patients to derive individualised prognostic scores of cognitive decline due to AD before symptoms occur. Our approach has strong potential to facilitate effective stratification of individuals based on prognostic disease trajectories, reducing patient misclassification with important implications for clinical practice and discovery of personalised interventions.

Speakers

15:15-15:45
How is the Royal Society approaching innovation policy and what are your thoughts?

Speakers

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