Steering Group

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AIBIO-UK Steering Group

AIBIO-UK is a BBSRC funded network for promoting the application of AI in the biosciences within the UK. The network is run by a Management Group who were nominated from colleagues in a wider community interest group who responded to a BBSRC call for interest in working on AI in the biosciences in 2022. Oversight and feedback for the management group is provided by the Steering Group, who are nominated from a variety of institutions, organisations and positions, so as to provide a comprehensive and expert opinion.

The steering group will undertake the following tasks:

Meet annually to examine progress of the management group against grant objectives and achievements of the network.
Provide critical feedback to the management committee on their actions and activities e.g. success of pilot grant funding schemes, engagement with industry etc.
Consult with the management group and advise on long term strategy for expanding and enhancing the network

Academia

Felix Shaw

Earlham Institute

Felix is the lead developer of the COPO (Collaborative Open Omics) data and metadata brokering platform for life sciences data, developed at the Earlham Institute. He holds a PhD in Computer Science, and specialises in metadata standards, open science, web technologies and signal processing. As of 2025 he is developing new standards around single cell RNASeq, spatial transcriptomics, and the application of machine learning techniques to organise and catalog scientific literature.

Mark Brewer

BioSS

Mark is Director of Biomathematics and Statistics Scotland (BioSS), a small research institute with headquarters in Edinburgh, which specialises in the development and application of the quantitative methods needed to enhance scientific knowledge and impact. Mark co-led a Specialist Advisory Group on the use of AI in the Scottish Government ENRA (Environment, Natural Resources and Agriculture) Division with Professor Georgios Leontidis. Mark’s research interests are in Bayesian modelling with applications mainly in environment and ecology; he has also been a statistical consultant for much of his career, with application in many different fields in the biological and environmental sciences, following his PhD in Edinburgh and a period as a lecturer at the University of Exeter.

Darren Wilkinson

Durham University

Darren is a Professor in Statistics within the Department of Mathematical Sciences at Durham University. A Bayesian statistician by training, he is an interdisciplinary researcher with a long track record of work in statistical bioinformatics and computational systems biology. Having originally trained at Durham, gaining his PhD in 1995, he spent 25 years at Newcastle University, where he held a BBSRC Fellowship, and led a number of biomathematical modelling work-packages on several large UKRI-funded programme grants. He was also a Turing Fellow, and co-director the EPSRC CDT in Cloud Computing for Big Data, building on his interests in modelling large and complex data sets in molecular biology and genomics. He continues to be motivated by the application of advanced statistical and machine learning algorithms and associated computational frameworks to challenging inferential problems in life science research and currently serves on the UKRI cross-council Strategic Advisory Team for AI.

Melanie Vollmar

EMBL-EBI

Melanie Vollmar is an ARISE Fellow at EMBL-EBI leading a text mining and NLP project for protein structure annotation enrichment. Previously she held Postdoc positions at the Structural Genomics Consortium within the University of Oxford, at the University of Manchester and at Diamond Light Source. She has a degree in biochemistry from the University of Regensburg and a PhD in structural biology from the University of Duesseldorf. Melanie is also a co-editor for Acta Crystallographica Section D: Structural Biology focusing on submissions concerned with AI, computing and statistics. Throughout her career she gained and combined experience in wet lab applications, computational biology, software development, machine learning and AI.

Elizabeth Sklar

University of Lincoln

Elizabeth Sklar is Director of the Lincoln Institute for Agri-food Technology (LIAT) and Professor in Agri-Robotics at the University of Lincoln. Previously she was Head of the Centre for Robotics Research (CoRe) in the Department of Informatics/Engineering at King’s College London and earlier at the City University of New York and Columbia University (US). Her research investigates intelligent methodologies for human-robot teaming and data-backed decision making. She has published over 200 peer-reviewed papers, was a founder of the international educational initiative RoboCupJunior and serves on the editorial board of Current Robotics Reports. She has received over £38M in grants as PI or Co-I, from funders including UKRI research councils, Innovate UK, US National Science Foundation and a US-UK Fulbright fellowship. She was the Research Director of the Lincoln Agri-Robotics (LAR) grant, funded by Research England, and is currently Deputy Director of the UKRI AI CDT in Sustainable Understandable agri-food Systems Transformed by Artificial INtelligence (SUSTAIN).

UKRI

Tochukwu Ajare

Senior Portfolio Manager for AI and Robotics, EPSRC

Tochi is an Engineering and Physical Sciences Research Council (EPSRC) Senior Portfolio Manager in the AI and Robotic Team, responsible for the management of the Turing AI Fellowships. Tochi joined EPSRC in 2020 and has managed a number of portfolios including Sustainable Manufacturing, Engineering Design and Digital Manufacturing portfolios.

Yan Yip

AI and Digital Health Program Manager, MRC

Yan is a Medical Research Council Programme Manager in the Data Science Team (Artificial Intelligence and Digital Health). Prior to joining MRC in 2020, she was a post-doctoral researcher at King’s College London working on cytoskeleton dynamics and cell membrane biology, and completed her PhD at The University of Melbourne, Australia.

Daniela Hensen

Senior Portfolio Manager for AI, BBSRC

Daniela is responsible for the strategy development in artificial intelligence (AI) as it relates to the biosciences, supporting the development of new AI approaches as well as application or adaptation of existing AI approaches that can lead to high-quality and transformative research outcomes. Her activities also extend across UK Research and Innovation more broadly in recognition of the genuine cross-cutting nature of AI. Daniela has worked in BBSRC since 2014, initially looking after the peer review process before moving into a strategy-focused position. Before focussing on artificial intelligence in 2020, she was responsible for other underpinning technologies including bioimaging, data-intensive bioscience and biodata resources.

Industry

George Amarantidis Koronaios

Mathworks

Dr. George Amarantidis works as a technical specialist at MathWorks, where he collaborates with academic institutions to enhance research, teaching, and innovation using MATLAB and Simulink. Prior to MathWorks, he developed software solutions for real-world engineering challenges in biomedical & semiconductor applications. Dr. Amarantidis specializes in Applied AI, signal processing, control systems, system identification and predictive maintenance. He has a Ph.D. in Control Systems from the University of Birmingham and an M.Eng. in Electrical and Electronic Engineering from Loughborough University.

Denis Battistella

NVidia