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Claudio Angione

Claudio Angione

Reader, Computer Science, Teesside University
Dr Claudio Angione is a Reader in Computer Science at Teesside University, within the Department of Computer Science and Information Systems.

He currently also holds two Visiting Professor positions at the University of Bari, in Italy, and at KMUTT, in Thailand.

He joined the university in 2015 as a Senior Lecturer, after a PostDoc at the University of Cambridge, and a research intern position at Microsoft Research UK.

He holds a PhD in Computer Science from the University of Cambridge, UK, awarded in 2015 with a thesis titled "Computational methods for multi-omic models of cell metabolism and their importance for theoretical computer science".

He previously obtained a Degree in Mathematics from the University of Catania, Italy. He also obtained a Higher Education Diploma from the Institute for Advanced Studies of the University of Catania, Italy.

Dr Angione's research group works at the intersection of computer science, mathematics and biology. Research topics include machine/deep learning, biomedical modelling and optimisation, systems biology, genome-scale cell models, statistical big data analytics. He has published more than 50 peer-reviewed papers in leading international conferences and high impact journals. He has recently received several awards for his outstanding academic contributions in the community, including an award by the Italian Embassy for the best research project in the Physical and Engineering Sciences in 2016.

He regularly serves as a reviewer for BBSRC Responsive Mode and MRC Responsive Mode grants. He serves as a Program Committee member for top AI and Mathematical Modelling conferences, and as a reviewer for top Computational Biology journals, including Nature Protocols, Metabolic Engineering, Bioinformatics, Oncotarget, Briefings in Bioinformatics, PLOS Computational Biology, BMC Bioinformatics.

AI technique that predicts cell growth could someday diagnose cancer or develop new drugs

Dec 17, 2020 11:37 am UTC| Science

Machine learning technologies are everywhere. Theyre used by search engines, social media, and even in online banking. But one area that this technology is still emerging is medicine. Machine learning technologies could...

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