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Artificial intelligence in the biosciences network

We are a BBSRC-funded network to support and enhance engagement between the Bioscience and AI communities in the UK.  The network will support community events, funding of pilot projects and creation of resources for supporting use of AI in the biosciences.

Artificial Intelligence (AI) systems are used in wide-ranging applications, from self-driving cars to language translation. Recent AI applications to the biosciences have been promising (e.g. deep learning systems for the prediction of protein structure), but efforts have been sparse and uncoordinated, and limited to groups/companies with specific expertise. Our vision is to bring together AI and core bioscience researchers to unravel biological fundamentals and tackle impeding societal challenges.

Although we are a community network, we have a Management Group to guide and help shape the network.  An external steering group will follow soon.

Management Group

Georgios Leontidis

Georgios Leontidis

Industry lead, social media

Georgios is a Professor of Machine Learning and the Director of the Interdisciplinary Centre for Data and AI at the University of Aberdeen. Georgios’ expertise spans foundations of deep learning, in particular self-supervised learning, domain adaptation, capsule neural networks and multimodal transformer systems, as well as interdisciplinary applications primarily in Agri-Food and Energy.
He is currently involved in 10 projects funded by EPSRC, BBSRC, ESRC-SGSSS, Scottish Funding Council, EU, Net Zero Technology Centre, Siemens Energy and Angus Growers. Georgios is a member of the leadership group of the Scottish AI Alliance and a Turing Academic Liaison.

Lucia Marucci

Lucia Marucci

Year 1 co-lead

Dr Lucia Marucci is a Fellow of the Engineering and Physical Sciences Research Council (EPSRC), and co-director of the Bristol Centre for Engineering Biology (BrisEngBio) and the Bristol BioDesign Institute (BBI). She holds a PhD in Automatic Engineering, and she was a European Molecular Biology (EMBO) fellow and a Medical Research Council (MRC) new investigator. Her interdisciplinary group works at the interface of systems and synthetic biology with control engineering and computer science, and is focused on the development of rational and automated strategies to precisely understand and design complex cellular phenotypes.

Reyer Zwiggelaar

Reyer Zwiggelaar

Co-Director, Ethics/RRI co-lead

Reyer is the Head of the Graduate School at the Aberystwyth University and has a chair in Computer Science. Reyer has 20+ years collaborative research experience with clinical/biology experts covering the development of machine learning and medical/biological image/data analysis techniques. More recently, he has also been working at the interface with digital repositories and represents Aberystwyth University at Supercomputing Wales. Current funding includes UKRI Centre for Doctoral Training in Artificial Intelligence, Machine Learning and Advanced Computing (EP/S023992/1), Miscanthus AI- Plant Selection and Breeding for Net Zero (EP/Y005430/1).

Dipali Singh

Dipali Singh

EDI co-lead

Dipali is a research scientist at the Quadram Institute and an affiliate researcher at the Oxford Brookes University. Dipali’s expertise lies in mathematical modelling of metabolism in particular the development and applications of genome-scale metabolic models. Her research focuses on systems biology approaches to investigate metabolic adaptation of microbes and microbial communities to bridge the gap between genotype and phenotype. The practical implications of her work extend to metabolite-based biomarkers and therapies, precision nutrition, and the enhancement of food safety. She is currently funded by the BBSRC Institute Strategic Programme (BB/R012504/1 and BBS/E/F/000PR10349).

Robert Knight

Robert Knight

EDI co-lead, Year 1 co-lead

Robert is a Reader at the Centre for Craniofacial and Regenerative Biology, King’s College London. Robert has been using molecular genetics and cell biology to probe organ development and repair in vertebrates for over 20 years, principally focusing on neuromuscular and musculoskeletal tissues. Combining advanced microscopy methods with computational and statistical approaches he aims to create explainable models for cell behaviour with funding from the Leverhulme Trust, Dunhill Medical Trust and Royal Society.
He sits on the steering group for the King’s AI Institute and is a member of the UKRI Interdisciplinary Assessment College.

Patrick Cai

Patrick Cai

Ethics/RRI co-lead

Patrick is a Professor in Synthetic Genomics at the University of Manchester and a world-leading expert in synthetic chromosomes, with a highly interdisciplinary research group. Patrick founded Edinburgh Genome Foundry and is the international coordinator for the (Sc2.0) Consortium. He regularly provides advice and consultancies to the Cabinet office, the Foreign Office and the Prime Minister’s Council for Science and Technologies. He holds prestigious visiting professorships with MIT (US), MRC LMB at Cambridge (UK), Hong Kong University and Chinese Academy of Sciences (China) and his current funding includes EPSRC fellowship and ERC Consolidator Award.

Maria Temenou

Maria Temenou

Network Manager

Maria (Mary) Temenou, the Network Manager of the AIBIO-UK project, holds two Master degrees from the University of Nottingham. Her previous roles involved organising large events and this has equipped her with skills essential for network management. Mary oversees project activities, collaborates with partners, manages funding calls, distributes awards, and engages the public. She plays a pivotal role in supporting the management team to ensure the project’s success.

Andrew French

Andrew French

Director, Year 1 co-lead

Andrew is a Professor Computer Science at the University of Nottingham, where he leads the Computer Vision Laboratory.  Along with several researchers in the lab, he focuses on developing AI approaches to understanding and interpreting biological images, including cells, plants and agricultural images. He holds an interdisciplinary position at Nottingham in the Schools of Computer Science and Biosciences. He has 20 years of experience developing novel AI approaches to computer vision in biological images, and has extensive experience developing data science learning resources for biologists.

Charlie Harrison

Charlie Harrison

Research Software Engineer

Charlie has worked with startups, governments, charities, universities and multinational corporations as a data scientist, technical consultant and researcher. He has a PhD in bioinformatics and was previously the Technical Lead on the GSMA’s AI for Impact project.