IDAI Pump Prime Funding
At the beginning of 2024 the Institute for Data and AI (IDAI) announced our first pump-prime funding call to support the development of innovative and high-impact research ideas.
This funding provides priming funds to support University of Birmingham researchers to develop interdisciplinary data science and AI ideas, projects and initiatives, both intra-Birmingham and through collaboration with leading national and international institutions. The funding aims to support work that will lead to the future external funding of innovative, high-impact research and long-term research collaborations. This funding is awarded through a process of pseudonymised panel review, followed by a lottery selection process – all applications put forward for the lottery had equal chance of being awarded.
Over 30 proposals for innovative and high-impact pump-prime research projects were received in first call. We delighted to announce the first cohort of 7 projects, which were awarded funding via lottery selection.
The 2024/2025 call is now open.
For all enquiries, please contact, Jessica Mylchreest, Head of Institute Operations, j.mylchreest@bham.ac.uk
Awarded Projects
Process Parameter Optimisation for Predictive Manufacturing and Design
Process Parameter Optimisation for Predictive Manufacturing and Design
Process Parameter Optimisation for Predictive Manufacturing and Design via Multi-Agent Reinforcement Learning
Dr Leonardo Stella, Lecturer, School of Computer Science
Prof Moataz Attallah, Professor of Advanced Materials Processing, School of Metallurgy and Materials
Understanding Follow-Up of Pulmonary Nodules at University Hospitals Birmingham
Understanding Follow-Up of Pulmonary Nodules at University Hospitals Birmingham
Understanding Follow-Up of Pulmonary Nodules at University Hospitals Birmingham to Improve Lung Cancer Survivability
Dr Michael Newnham, Associate Professor & Respiratory Consultant, Institute of Applied Health
Dr Justin Aunger, Research Fellow, Institute of Applied Health
Dr Karin Slater, Assistant Professor of Biomedical Semantics, Institute of Cancer and Genomic Sciences
Usability of AI-Enabled Analysis for Tissue-Based Pathological Scoring of H&E Images
Usability of AI-Enabled Analysis for Tissue-Based Pathological Scoring of H&E Images
Usability of AI-Enabled Analysis for Tissue-Based Pathological Scoring of H&E Images from Sjogren Syndrome Patient Biopsies: A Tool to Optimize Clinical Trials
Dr Saba Nayar, Research Fellow, Institute Inflammation and Ageing
Prof Fabian Spill, Professor of Applied Mathematics, School of Mathematics
Mr Sebastian Gilbert, PhD Student, School of Mathematics
A Public Database of Single-Molecule Tracking Data
A Public Database of Single-Molecule Tracking Data
Prof Dylan Owen, Professor of Immunology and Immunotherapy, Institute of Immunology and Immunotherapy
Bridging Human Brain Electrophysiology and Artificial Neural Network
Bridging Human Brain Electrophysiology and Artificial Neural Network
Bridging Human Brain Electrophysiology and Artificial Neural Network to Understand How Visual Representations Emerge
Dr Jianbo Jiao, Assistant Professor in Computer Science, School of Computer Science
Prof Ole Jensen, Professor in Translational Neuroscience, School of Psychology
Birmingham Digital Twin Scale-Up
Birmingham Digital Twin Scale-Up
Prof Martin Freer, Director of the Birmingham Energy Institute, School of Physics and Astronomy
Holistic Approaches to Biodiversity Monitoring Using AI
Holistic Approaches to Biodiversity Monitoring Using AI
Dr Jiarui Zhou, Assistant Professor in Environmental Bioinformatics, School of Biosciences
Prof Luisa Orsini, Professor of Evolutionary Systems Biology and Environmental Omics, School of Biosciences