Professor Zoheir Sabeur
- Professor of Data Science and Artificial Intelligence
- Poole House P322, Talbot Campus, Fern Barrow, Poole, BH12 5BB
Biography
Zoheir Sabeur is Professor of Data Science and Artificial Intelligence at Bournemouth University (2019-present), and Head of the Processes and Behaviour Understanding (PRO_BU) Research Group.
He is also Visiting Professor of Data Science at Colorado School of Mines, Golden, Colorado, USA (2017-present). Zoheir was Science Director at the School of Electronics and Computer Science, IT Innovation Centre, University of Southampton (2009-2019). He led his Data Science Research Group over the years in more than 30 large projects as Principal Investigator (PI). The research was funded with grants totalling £8.5M, by the European Commission (H2020, FP7, FP6, FP5), Innovate UK, DSTL, NERC, EPSRC and Industries. Prior to Southampton, Zoheir worked as Director and Head of Research in Marine Informatics, at BMT Group Limited (1996-2009), At BMT, Zoheir led as PI large Joint Industries research initiatives such as MIMIC, UKOOA I, II and III which were funded by O&G industries, NERC and EPSRC (Grants totalling £3.5M)... In these, he led his research team in the development of advanced information systems, including the PROTEUS, ISAAC, STM and LTM systems, for O&G UK and the Department of Trade and Industry for assessing the short term and long term environmental impact of offshore industrial explorations, operations; and also decommissioning.
Prior to working with BMT Group Ltd, Zoheir held several academic appointments in Computational Sciences, including Senior Research Fellow in Computational Fluid Dynamics at Oxford Brookes University (1993-1996), SERC Research Fellow in Computational Molecular Physics at University of Leeds (1991-1993); and Triatomic Molecular Laser Physics at the University of Strathclyde (1990-1991). He also worked as a Research Scientist in the Intensive Computing Lattice QCD Theoretical Physics Group at the University of Wuppertal, Germany (1987). Zoheir graduated with a PhD and MSc in Theoretical Physics from the University of Glasgow (1985-1990). His PhD was on: "Lattice QCD at High Density with Dynamical Fermions"., while earlier research work in his MSc was on: "The Study of the Fermion Matrix Spectral Density in Lattice QCD. This was his earliest involvement in "Data Science" using supercomputing vector machines for investigating on the origins of hadron matter phase transitions, specifically with the mechanism of chiral symmetry breaking and quarks confinements.
In the last 15 years, Zoheir long research career moved towards fundamentals of Data Science and Artificial Intelligence with knowledge extraction for human, natural (or industrial), processes and behaviour understanding. These are being investigated in context of various domains which include: Humans chronic diseases intelligent analytics for diagnostics and prognostics in healthcare; Advanced situational awareness using computer vision, sensors data fusion and knowledge reasoning in Cyber-physical security; Natural species migratory patterns and behaviour detection and understanding due to climate change using Earth Observations ; and more.
Zoheir has published over 200 papers in scientific journals, conference proceedings and books. He is peer reviewer, member of international scientific committees and editing boards of various science and engineering conferences and journals. He is also an active peer reviewer of research programmes for the UKRI, EPSRC, MRC, Dutch Research Council and European Commission. Zoheir chaired the OGC Digital Global Grid System Specification and Domain Working Groups, and co-chaired the AI and Data Science Task Group at the BDVA. He is Fellow of the British Computer Society; Fellow of IMaREST, Chartered Physicist, Chartered Engineer and Member of the Institute of Physics. He is Programme Leader for the MSc Data Science and AI, and MSc Digital health and AI at Bournemouth University. He is also external reviewer for programmes of MSc Data Science and AI for many UK Universities and others around the world.
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My long research career over the years moved towards fundamentals of Data Science and Artificial Intelligence for science discoveries. My interest is mainly on knowledge extraction for understanding human, natural (or industrial), processes and behaviour. Behaviour here, means "observables" dynamics, conditions or mechanisms that evolve in systems or sub-systems. Be it a physical system, a human system or indeed an organ to the simplest organism. The aim is to observe such systems using multi-modal observation methods which generate rich big data for further analyses and learning using AI. Some processes and behaviour may yet to be discovered. Also, our observation missions may be constrained by the Uncertainty Principle. Although known in quantum physics it is not clear to us when observing "other intelligent" systems!
My research activities are being applied in context of various domains of interest. These include: Chronic diseases understanding from omics to phenotypic levels; Intentional behaviour detection of natural intelligent systems including humans; Intelligent behaviour and responses in a changing recipient environment...and more.
Our aim here is to empower ourselves with AI fundamentals for accelerating our ways of understanding dynamic systems, with their underlying driving processes and mechanisms.
A more recent activity which we are currently conducting in our research team is the intelligent detection of severities of respiratory diseases such as COPD and Asthma. This is done through investigating patterns of lung auscultation signals... These are distinctly analysed when transformed into their feature space and used for machine classifications. Good classification performances on severities are obtained as a result.
In a similar way, we are exploring the evolution of other diseases such as cancers using machine learning and detection of gene mutations as the disease evolves. AI is indeed speeding up our understanding of such systems and processes, while our ultimate goal is to further our discoveries and lead to the foundation of generalised theories that are supported by mathematically validated formalisms.
I am happy to discuss potential research collaboration or partnership, including the development of new ideas and initiatives for research funding under UKRI, Horizon Europe, and others.
I am also keen for more postgraduate students to join our Research Group for pursuing their PhD investigations with us.
Stay in touch!
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