Zoheir Sabeur

Professor Zoheir Sabeur

  • Professor of Data Science and Artificial Intelligence
  • Poole House P322, Talbot Campus, Fern Barrow, Poole, BH12 5BB
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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)...

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Research

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...

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Journal Articles

  • Albiges, T., Sabeur, Z. and Arbab-Zavar, B., 2025. Features and eigenspectral densities analyses for machine learning and classification of severities in chronic obstructive pulmonary diseases. Intelligence-Based Medicine, 11.
  • Bruno, A., Chetouani, A., Sabeur, Z., Tliba, M., Maltezos, E. and Emeterio, M.G.S., 2024. Special issue: Multimedia data analysis for smart city environment safety: Editorial article: Embarking on a safer tomorrow through advanced multimedia analysis. Multimedia Tools and Applications, 83 (22), 61491-61492.
  • Albiges, T., Sabeur, Z. and Arbab-Zavar, B., 2024. Complex audio signal data compression and reconstruction: A benchmark data pre-processing approach for machine classification of chronic respiratory diseases. Digital Health, 10.
  • Albiges, T., Sabeur, Z. and Arbab-Zavar, B., 2023. Compressed Sensing Data with Performing Audio Signal Reconstruction for the Intelligent Classification of Chronic Respiratory Diseases. Sensors, 23 (3).
  • Rawson, A., Brito, M. and Sabeur, Z., 2022. Spatial Modeling of Maritime Risk Using Machine Learning. Risk Analysis, 42 (10), 2291-2311.
  • Rawson, A., Sabeur, Z. and Brito, M., 2022. Intelligent geospatial maritime risk analytics using the Discrete Global Grid System. Big Earth Data, 6 (3), 294-322.
  • Gibb, R.G., Purss, M.B.J., Sabeur, Z., Strobl, P. and Qu, T., 2022. Global Reference Grids for Big Earth Data. Big Earth Data, 6 (3), 251-255.
  • Rawson, A., Brito, M., Sabeur, Z. and Tran-Thanh, L., 2021. From conventional to machine learning methods for maritime risk assessment. TransNav, 15 (4), 757-764.
  • Rawson, A., Brito, M., Sabeur, Z. and Tran-Thanh, L., 2021. A machine learning approach for monitoring ship safety in extreme weather events. Safety Science, 141.
  • Arbab-Zavar, B. and Sabeur, Z.A., 2020. Multi-scale crowd feature detection using vision sensing and statistical mechanics principles. Machine Vision and Applications, 31 (4).
  • Purss, M.B.J., Peterson, P.R., Strobl, P., Dow, C., Sabeur, Z.A., Gibb, R.G. and Ben, J., 2019. DataCubes: A discrete global grid systems perspective. Cartographica, 53 (4), 63-71.
  • Granell, C., Sabeur, Z. et al., 2016. Future Internet technologies for environmental applications. Environmental Modelling and Software, 78, 1-15.
  • Zlatev, Z., Veres, G. and Sabeur, Z., 2013. Agile data fusion and knowledge base architecture for critical decision support. International Journal of Decision Support System Technology, 5 (2), 1-20.
  • Middleto, S.E., Sabeur, Z.A., Löwe, P., Hammitzsch, M., Tavakoli, S. and Poslad, S., 2013. Multi-disciplinary approaches to intelligently sharing large-volumes of real-time sensor data during natural disasters. Data Science Journal, 12.
  • Havlik, D., Schade, S., Sabeur, Z.A., Mazzetti, P., Watson, K., Berre, A.J. and Mon, J.L., 2011. From sensor to observation web with environmental enablers in the future internet. Sensors, 11 (4), 3874-3907.
  • Sabeur, Z.A. and Tyler, A.O., 2004. Validation and application of the PROTEUS model for the physical dispersion, geochemistry and biological impacts of produced waters. Environmental Modelling and Software, 19 (7-8), 717-726.
  • Tyler, A.O., Sabeur, Z.A. and Hockley, M.C., 2002. Modelling the behaviour and environmental impact of cuttings piles during decommissioning. Underwater Technology, 25 (2), 39-50.
  • Sabeur, Z.A., Tyler, A.O. and Hockley, M.C., 2000. Development of particle based modelling concepts for the simulation of jet and plume-like discharges in the marine environment. Water Studies, 7, 337-345.
  • Smith, J.P., Tyler, A.O. and Sabeur, Z.A., 1998. Ecotoxicological assessment of produced waters in indonesia. Environmental Toxicology and Water Quality, 13 (4), 323-336.
  • Sabeur, Z., 1993. Asymptotic Decay of Liquid Structure: Oscillatory Liquid-Vapour Density Profiles and the Fisher-Widom Line. Molecular Physics: An International Journal at the Interface Between Chemistry and Physics, 80, 755.
  • Sabeur, Z. and Henderson, J.R., 1992. Liquid‐state integral equations at high density: On the mathematical origin of infinite‐range oscillatory solutions. Chemical Physics, 97, 6750-6758.
  • Sabeur, Z., Barbour, I. and Davies, C., 1988. Lattice QCD at finite density. Physics Letters B: Nuclear Physics and Particle Physics, 215 (3), 567-572.

Chapters

  • Sabeur, Z. and Arbab-Zavar, B., 2021. Crowd Behaviour Understanding Using Computer Vision and Statistical Mechanics Principles. Modeling and Simulation in Science, Engineering and Technology. 49-71.
  • Rawson, A., Sabeur, Z. and Correndo, G., 2020. Spatial challenges of maritime risk analysis using big data. Proceedings in Marine Technology and Ocean Engineering. 275-282.
  • Sabeur, Z., 2009. Data Fusion and Modelling. In: Klopfer, M., ed. SANY An Open Service Architecture for Sensor Networks. SANY Consortium, 1-165.
  • Annoni, A., Bernard, L., Douglas, J., Greenwood, J., Laiz, I., Lloyd, M., Sabeur, Z., Sassen, A.-M., Serrano, J.-J. and Usländer, T., 2005. Orchestra: Developing a unified open architecture for risk management applications. Geo-information for Disaster Management. 1-17.

Conferences

  • Christian, A., Davis, Z., Walewska, R., Buchan, S., Sabeur, Z. and McCarthy, H., 2024. Data Analytics of Treatment effects on Immune Response Pathways within the Tumour Microenvironment of Waldenström Macroglobulinaemia. In: Cambridge lymphoma biology international symposium 2024 17-18 September 2024 Cambridge.
  • Christian, A., Davis, Z., Walewska, R., Buchan, S., Sabeur, Z. and McCarthy, H., 2024. Data Analytics of Treatment effects on Immune Response Pathways within the Tumour Microenvironment of Waldenström Macroglobulinaemia. In: International Workshop on Waldenstrom's macroglobulinaemia 17-19 October 2024 Prague.
  • Sabeur, Z., Bruno, A., Johnstone, L., Ferjani, M., Benaouda, D., Cetinkaya, D., Arbab-Zavar, B., Sallal, M. and Hardiman, B., 2022. Digital Twins for the Intelligent Detection of Malicious Activities in Urban Spaces. In: 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022) 24-28 July 2022 New York, USA. Cognitive Computing and Internet of Things, vol. 67 published by AHFE Open Access.
  • Sabeur, Z., Bruno, A., Johnstone, L., Ferjani, M., Benaouda, D., Arbab-Zavar, B., Cetinkaya, D. and Sallal, M., 2022. Cyber-Physical Behaviour Detection and Understanding using Artificial Intelligence. In: 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022) 24-28 July 2022 New York, USA. Cognitive Computing and Internet of Things, vol. 67 published by AHFE Open Access.
  • Bruno, A., Ferjani, M., Sabeur, Z., Arbab-Zavar, B., Cetinkaya, D., Johnstone, L., Sallal, M. and Benaouda, D., 2022. High-Level Feature Extraction for Crowd Behaviour Analysis: A Computer Vision Approach. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13374 LNCS, 59-70.
  • Sabeur, Z., Angelopoulos, C.M., Collick, L., Chechina, N., Cetinkaya, D. and Bruno, A., 2021. Advanced Cyber and Physical Situation Awareness in Urban Smart Spaces. Lecture Notes in Networks and Systems, 259, 428-441.
  • Rawson, A., Sabeur, Z. and Brito, M., 2021. GEOSPATIAL DATA ANALYSIS FOR GLOBAL MARITIME RISK ASSESSMENT USING THE DISCRETE GLOBAL GRID SYSTEM. International Geoscience and Remote Sensing Symposium (IGARSS), 3904-3907.
  • Rawson, A., Sabeur, Z. and Correndo, G., 2020. Spatial challenges of maritime risk analysis using big data. Developments in the Collision and Grounding of Ships and Offshore Structures - Proceedings of the 8th International Conference on Collision and Grounding of Ships and Offshore Structures, ICCGS 2019, 275-282.
  • Sabeur, Z., Zlatev, Z., Melas, P., Veres, G., Arbab-Zavar, B., Middleton, L. and Museux, N., 2017. Large scale surveillance, detection and alerts information management system for critical infrastructure. IFIP Advances in Information and Communication Technology, 507, 237-246.
  • Sabeur, Z.A., Correndo, G., Veres, G., Arbab-Zavar, B., Lorenzo, J., Habib, T., Haugommard, A., Martin, F., Zigna, J.M. and Weller, G., 2017. EO big data connectors and analytics for understanding the effects of climate change on migratory trends of marine wildlife. IFIP Advances in Information and Communication Technology, 507, 85-94.
  • Sabeur, Z.A., Melas, P., Meacham, K., Corbally, R., D’Ayala, D. and Adey, B., 2017. An integrated decision-support information system on the impact of extreme natural hazards on critical infrastructure. IFIP Advances in Information and Communication Technology, 507, 302-314.
  • Mayon, R., Sabeur, Z., Tan, M. and Djidjeli, K., 2016. Analysis of fluid flow impact oscillatory pressures with air entrapment at structures. Proceedings of the Coastal Engineering Conference, 35.
  • Veres, G.V. and Sabeur, Z.A., 2015. Data analytics for drilling operational states classifications. 23rd European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN 2015 - Proceedings, 409-414.
  • Sabeur, Z., Doulamis, N., Middleton, L., Arbab-Zavar, B., Correndo, G. and Amditis, A., 2015. Multi-modal computer vision for the detection of multi-scale crowd physical motions and behavior in confined spaces. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9474, 162-173.
  • Correndo, G., Arbab-Zavar, B., Zlatev, Z. and Sabeur, Z.A., 2015. Context ontology modelling for improving situation awareness and crowd evacuation from confined spaces. IFIP Advances in Information and Communication Technology, 448, 407-416.
  • Melas, P., Correndo, G., Middleton, L. and Sabeur, Z.A., 2015. Advanced data analytics and visualisation for the management of human perception of safety and security in urban spaces. IFIP Advances in Information and Communication Technology, 448, 445-454.
  • Veres, G.V. and Sabeur, Z.A., 2013. Automated operational states detection for drilling systems control in critical conditions. ESANN 2013 proceedings, 21st European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, 53-58.
  • Bonatsos, A., Middleton, L., Melas, P. and Sabeur, Z., 2013. Crime Open Data Aggregation and Management for the Design of Safer Spaces in Urban Environments. IFIP Advances in Information and Communication Technology, 413, 311-320.
  • Sabeur, Z., Arbab-Zavar, B., Wächter, J., Hammitzsch, M., Löwe, P., Lendholdt, M., Armigliato, A., Pagnoni, G., Tinti, S. and Omira, R., 2013. Modeling and detection of hydrodynamic trends for advancing early-tsunami warnings. Proceedings of the International Offshore and Polar Engineering Conference, 40-47.
  • Löwe, P., Wächter, J., Hammitzsch, M., Lendholt, M., Häner, R., Mobgraber, J. and Sabeur, Z., 2013. The evolution of disaster Early Warning systems in the TRIDEC project. Proceedings of the International Offshore and Polar Engineering Conference, 48-52.
  • Modafferi, S., Chakravarthy, A. and Sabeur, Z., 2013. Multi-level data fusion of environmental data in future internet applications. 21st Italian Symposium on Advanced Database Systems, SEBD 2013, 297-304.
  • Usländer, T., Berre, A.J., Granell, C., Havlik, D., Lorenzo, J., Sabeur, Z. and Modafferi, S., 2013. The Future Internet Enablement of the Environment Information Space. IFIP Advances in Information and Communication Technology, 413, 109-120.
  • Middleton, S.E. and Sabeur, Z.A., 2011. Knowledge-based service architecture for multi-risk environmental decision support applications. IFIP Advances in Information and Communication Technology, 359 AICT, 101-109.
  • Mörzinger, R., Sabeur, Z. et al., 2010. Tools for semi-automatic monitoring of industrial workflows. ARTEMIS'10 - Proceedings of the 1st ACM Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Streams, Co-located with ACM Multimedia 2010, 81-86.
  • Annoni, A., Bernard, L., Douglas, J., Greenwood, J., Laiz, I., Lloyd, M., Sabeur, Z., Sassen, A.M., Serrano, J.J. and Usländer, T., 2005. Orchestra: Developing a unified open architecture for risk management applications. , 1-17.
  • Sabeur, Z.A., Allsop, N.W.H., Beale, R.G. and Dennis, J.M., 1997. Wave dynamics at coastal structures: Development of a numerical model for free surface flow. Proceedings of the Coastal Engineering Conference, 1, 389-402.
  • Rymell, M.C., Sabeur, Z.A., Williams, M.O., Borwell, D.M. and Tyler, A.O., 1997. Development and application of environmental models in the assessment of exploratory drilling in a sensitive coastal region, Isle of Man, UK. Society of Petroleum Engineers - SPE/UKOOA European Environment Conference 1997, EEC 1997, 257-263.
  • Rymell, M.C., Sabeur, Z.A., Williams, M.O., Borwell, D.M. and Tyler, A.O., 1997. Development and application of environmental models in the assessment of exploratory drilling in a sensitive coastal region, Isle of Man, UK. SPE/UKOOA European Environmental Conference, Proceedings, 257-265.
  • Sabeur, Z.A., 1996. A parallel computation of the navier-stokes equation for the simulation of free surface flows with the volume of fluid method. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 1041, 483-492.

Others

  • Correndo, G. and Sabeur, Z.A., 2015. Open data sources for the development of mobile applications and forecast of microbial contamination in bathing waters. Published.

PhD Students

  • Sebastian Nickel, 2024. Advanced cluster and feature omics data mining for chronic respiratory diseases, (In progress)
  • Mihye Lee, 2027. Understanding and monitoring infective endocarditis to improve clinical outcomes of Infective endocarditic patients, (In progress)
  • Amy Christian, 2028. Machine Learning with Advanced Immunogenetic Analytics for the Clinical Care of Waldenström Macroglobulinaemia, (In progress)
  • Robert Mayon, 2017. Computational Free Surface Flows and Impact on Porous Structures, (Completed)
  • Andrew Rawson, 2021. Big data analytics for safer ships navigation in arctic harsh environment(s), (Completed)
  • Tim Albiges, 2024. Artificial Intelligence and Signal Analysis for COPD Classification: Detecting and Understanding of Respiratory Disease Severities, (Completed)

Profile of Teaching PG

  • Data Science and Artificial Intelligence - MSc - Programme Leader
  • Digital Health and Artificial Intelligence - MSc - Programme Leader
  • Artificial Intelligence - Unit code: 249813_FST_COM_L7_2122 - Unit Leader

Profile of Teaching UG

  • Cyber Situational Awareness - 65018_FST_COM_L6 - Unit Leader
  • Tools and Technologies for Data Science - 68392_FST_COM_L5 - Unit Leader

Invited Lectures

  • AI for exploitation of Earth Observations, Farnborough International Conference Centre, 20 Mar 2025 more
  • AI Methods for Respiratory Diseases Detection, UK Department of Health and Social Care, 14 Aug 2024 more
  • Big Data Technologies, Data Science and AI, Bournemouth University - CHSDC, 18 May 2023 more
  • Artificial Intelligence for Safer Urban Space, AI3 Science Discovery Network, 08 Dec 2021 more
  • European Big Data Value Forum Seminars, Siemens Conference Center Vienna, Austria, 14 Nov 2018 more
  • Institute of Engineering and Technology Lecture, IET, Isle of Wight, 25 Jan 2018 more
  • BMT Data Conference 2017, BMT Group Limited, Goodrich House Teddington, UK, 03 Oct 2017 more
  • ECS Data Science Seminar Series, University of Southampton, ECS, 13 Jul 2016 more
  • Implications of DIRECTIVE 2013/30/EU on O&G, European Parliament - Brussels, 16 Oct 2013 more

Grants

  • INSIGHT (National Institute of Health and Medical Research, 01 Apr 2024). In Progress
  • Immunogenetic Data Analytics - AI for Future Care of Waldenström Macroglobulinaemia (Bournemouth University - University Hospital Dorset, 15 Jan 2024). In Progress
  • S4AllCities: Smart Spaces Safety and Security for All Cities (European Commission (H2020) - Grant Number 883522, 01 Sep 2020). Completed
  • OADEM 2021 - Automatic Detection of Anomalies in CENSUS 2021 Data - Phase 3 (Office for National Statistics, 01 Feb 2019). Completed
  • Big Earth Observation (EO) Data – HD Digital Globe Image Recognition of Baleen Whales Habitats and Behaviour in a Changing Climate (HE Stimulus Fund, 01 Jan 2019). Completed
  • Big Medilytics - Improving healthcare in Europe through big data analytics - COPD UK pilot leader - Grant ID Number: 780495 (H2020 European Commission, 01 Jan 2018). Completed
  • OADEM 2021 - Automatic Detection of Anomalies in CENSUS 2021 Data - Phase 1 and Phase 2 (Office for National Statistics, 01 Dec 2017). Completed
  • SEDNA: Big Data Analytics for Safer Shipping in Arctic Environment (European Commission - H2020, 01 Sep 2017). Completed
  • Transforming Transport - Big Data Analytics for Assets Predictive Maintenance (European Commission, 01 Jan 2017). Completed
  • PROTECT-CDE - Computations and Specifications for the Design of Smart Defences for Wave Energy Harvesting (Higher Education Stimulus Fund, 01 Jan 2017). Completed
  • Big Data Analytics and Technologies (Office for National Statistics, 01 Dec 2016). Completed
  • EO4Wildlife - Earth Observation Big data Analytics for detecting migratory trends of marine species due to climate change (H2020 European Commission, 01 Jan 2016). Completed
  • Big Data Analytics: Insights into offshore resources and processes. (HE Stimulus Fund, 05 Jan 2015). Completed
  • The Dempster-Shafer Framework - Optimised Ocean Data Observation and Measurements with Autonomous Swarming Unmanned Surface Vessels (Natural Environment Research Council, 01 Jan 2015). Completed
  • ZoneSEC - Towards a EU Framework for the Security of Widezones (European Commission - FP7 Grant ID Number: 607292, 01 Oct 2014). Completed
  • AXON-III: ICT Health Platform Architecture Specification (Axon TeleHealthcare Limited, 03 Feb 2014). Completed
  • SMMI-RCSF: Intelligent Forecasting of risks of microbial contamination in coastal waters (HE Stimulus Fund, 06 Jan 2014). Completed
  • Future Cities Feasibility Study - Big Data Analytics (Innovate UK, 01 Nov 2013). Completed
  • INFRARISK - Novel Indicators for Identifying Critical infrastructure risks from natural hazards (EU-FP7, 01 Oct 2013). Completed
  • EVACUATE - Evacuation of large crowds from confined spaces to safety using Multi-modal Computer Vision and AI (EU - FP7, 01 Apr 2013). Completed
  • SWIM Roadmap: A review of Ontology management tools for water systems. (Innovate UK, 01 May 2012). Completed
  • AXON-II: ISO27001 Compliance (AXON TeleHealthcare Limited, 01 May 2012). Completed
  • IoT Enablement - Converged and Open Services for Transport and Logistics (British Telecommunications, 01 Mar 2012). Completed
  • Envirofi - The Environmental Observation Web and its Service Applications within the Future Internet (EU Commission - FP7, 01 Apr 2011). Completed
  • OGC SWE Implementations for Sensor Systems Applications (DSTL, 01 Feb 2011). Completed
  • Desurbs - Designing Safer Spaces (European Commission - FP7, 01 Jan 2011). Completed
  • TRIDEC - Complex, Critical and Collaborative Decision-support in evolving crises (European Commission - FP7, 01 Sep 2010). Completed
  • AXON-I Technical Specification for the t4NET Architecture (AXON TeleHealthcare Limited, 01 Jul 2010). Completed
  • Adaptive Long Term Modelling of Drill Cutting Piles (Shell UK, 06 Feb 2009). Completed
  • SCOVIS - Self-Configurable Cognitive Video Supervision (European Commission FP7, 03 Mar 2008). Completed
  • Bathing Water Quality Forecasting: Data Driven Predictors for the Management of South of England Bathing Zones (Environment Agency, 03 Dec 2007). Completed
  • SANY- Sensors Anywhere (European Commission FP6, 01 Sep 2006). Completed
  • ORCHESTRA - Open Architecture and Spatial Data Infrastructure for Risk Management (European Commission - FP6, 01 Sep 2004). Completed
  • ISAAC: Information System for Assessment of the fate of Acoustic Channels (British Gas, 01 Mar 2004). Completed
  • i-MARQ - Information system for Marine Aquatic Resource Quality (EU Commission FP5, 01 May 2002). Completed
  • UKOOA III - Platform Decommissioning in the North Sea (UKOOA, 01 Mar 2002). Completed
  • SEAM : Assessing Concepts and Tools for Safer, Efficient and Environmentally Aware and Friendly Maritime Transport (European Commission - FP5, 01 Mar 2001). Completed
  • BlueWater - Computerised video camera image analysis for monitoring pollution in water (European Commission - FP5, 01 Mar 2000). Completed
  • UKOOA II - Platform Decommissioning: Long Term Modelling Disturbances (UKOOA, 01 Mar 2000). Completed
  • UKOOA I - Platform Decommissioning: Short Term Modelling Disturbances (UK Offshore Oil Operators Alliance, 01 Jun 1998). Completed
  • MIMIC - Management of the Impact of Marine Industrial Chemicals (JIP: O&G-NERC-EPSRC, 02 Sep 1996). Completed

External Responsibilities

  • European Big Data Value Association (BDVA), Co-Chair of Ai and Data Science Task Group (2019-)
  • University of Southampton - School of Electronics and Computer Science, External PhD supervisor (2018-)
  • Colorado School of Mines, Golden, USA, Visiting Professor of Data Science (2017-)
  • DGGS - OGC International, Chair of the DGGS SW and DW groups (2017-)

Internal Responsibilities

Qualifications

  • Advanced Leadership Processes in Executive Management (Ashridge Business School (UK), 2011)
  • Chartered Engineer (CEng) in Computing and Informatics (UK Enginerring Research Council, 1996)
  • Chartered Physicist (CPhys) in Physics (Institute of Physics, 1996)
  • PhD - with UK ORS Awards - in Theoretical Physics (University of Glasgow, 1990)
  • MSc in Theoretical Physics (University of Glasgow, 1986)
  • BSc First-Class Honours in Physics and Applied Mathematics (Universite d'Oran, 1984)
  • Baccalaureat (With Distinction) in Techniques Mathematiques (Lycee Technique d'Oran, 1980)

Honours

  • ORS Award - 1989 (Committee of Vice-Chancellors and Principals of the Universities of the United Kingdom, 1989)
  • ORS Award - 1988 (Committee of Vice-Chancellors and Principals of the Universities of the United Kingdom, 1988)
  • ORS Award - 1987 (Committee of Vice-Chancellors and Principals of the Universities of the United Kingdom, 1987)

Memberships

  • British Computer Society, Fellow (2019-),
  • Institute of Marine Enginering, Science and Technology, Fellow (2017-),
  • Institue of Physics, Member (1996-),

External Media and Press

Broadcast Interview

  • Heart Radio - News Bulletin interview, AI deployment for Investment in UK Healthcare - Professor Sabeur interview by Broadcaster Rachel Mather, Heart Radio. Following the press conference of PM Sir Keir Starmer, concerning investments on AI, Professor Sabeur noted that the deployment of AI for investment on future healthcare in the UK, is critical and paramount for improving the lives of millions of people. January 13th 2025, 4pm, 5pm, 6pm News bulletins., Rachel, M, 13 Jan 2025. http://my.tvey.es/Sf6g8
  • AI 4 Science Discovery, In this Humans of AI4SD interview Professor Zoheir Sabeur discusses the early days of data science and its importance to this century, how to understand, detect and track human behaviour to make urban spaces safer, the fascination of mathematical theories, and how data science came into its own during the pandemic. https://eprints.soton.ac.uk/469318/1/Humans_of_AI3SD_Interview_38_ZS.pdf, Pauli, M, 30 Nov 2021. https://eprints.soton.ac.uk/469318/1/Humans_of_AI3SD_Interview_38_ZS.pdf
  • Data Science, AI and One Health, Professor Zoheir Sabeur provides aspects of his long career in Data Science and AI and how they benefited into addressing solving real world problems, including understanding diseases in health, the COVID pandemic, climate change and coastal erosion and smart defences, to those coming towards us at the present time and the foreseeable future. (See interview in YouTube: https://www.youtube.com/watch?v=gX-DR2tSiCw), Deborah, T, 15 Aug 2021. https://www.youtube.com/watch?v=gX-DR2tSiCw