Taylor
imon j e taylor is a professor of computer science specialising in modelling & simulation and digital infrastructures. he has made many contributions to manufacturing, health care and international development. he has worked with international consortia (in particular unict, wacren and the ubuntunet alliance) to contribute to the development of national research and education networks in africa that has impacted over 3 million students and 300 universities. he has also worked with international consortia (in particular saker solutions, the university of westminster, sztaki and cloudsme ug) to develop high performance simulation systems that are being used by over 30 european smes and large-scale enterprises such as the ford motor company and sellafield plc. he continues to work closely with industry - his work has led to over £30m of savings and new products in industry. he also contributes to the development of open science principles and practice for africa and for modelling & simulation as a field. he has led modules in distributed computing in the department of computer science for many years with high module evaluations scores and is an enthusiastic teacher. he has also led the development of several postgraduate degrees. he has supervised over 20 doctoral students, has examined more than 25 doctoral students from across the world and has managed over 15 research fellows. professor taylor co-founded and is a former editor-in-chief of the journal of simulation and the uk operational research society simulation workshop series. he chaired acm sigsim between 2005-2008 and since then has been an active member of the acm sigsim steering committee. he is also the general chair for the 2025 winter simulation conference. he has chaired international standardisation groups under the simulation interoperability standards organization and has conducted several organisational review panels (e.g., dstl) and simulation audits. he is currently the executive chair for the annual simulation exploration experience ( and a member of the computer simulation archive steering committee ( he has also chaired several conferences and is the general chair for the ieee/acm 2025 winter simulation conference. interested in the history of computer simulation? visit the computer simulation archive hosted by ncsu and hear talks from some of the pioneers in computer simulation. i am strongly interested in modelling & simulation and digital infrastructures, particularly in the development of high performance simulation infrastructures and services in industry and health care. these are extremely important as it allows users to perform more simulation experimentation and to get deeper insight into their problems. this has openned up a new area of study that is allowing us to develop novel ai-based optimisation techniques for modelling & simulation that leverage our high performance simulation infrastructures that we have already deployed in industry (e.g., ford, saker solutions and sellafield). in parallel with these interests i have been able to work towards the development of digital infrastructures and services in africa. this has contributed to the rapid development of african national research and education networks and the foundation for african open science. this work continues and we are working with african stakeholders to further develop african open science and data science approaches across the continent. in turn these experiences have enabled me to contribute to open science techniques for modelling & simulation, as well as open science at brunel. modelling & simulation digital infrastructures and services cloud computing international development open science i teach a variety of subjects from modelling & simulation to distributed computing at undergraduate, postgraduate and national levels (e.g. natcor). i also support student projects and (unpaid) internships in these areas.
![Professor Simon Taylor]()
Professor Simon Taylor
imon J E Taylor is a Professor of Computer Science specialising in Modelling & Simulation and Digital Infrastructures. He has made many contributions to manufacturing, health care and international development. He has worked with international consortia (in particular UNICT, WACREN and the UBUNTUNET ALLIANCE) to contribute to the development of National Research and Education Networks in Africa that has impacted over 3 million students and 300 universities. He has also worked with international consortia (in particular Saker Solutions, the University of Westminster, SZTAKI and CloudSME UG) to develop high performance simulation systems that are being used by over 30 European SMEs and large-scale enterprises such as the Ford Motor Company and Sellafield PLC. He continues to work closely with industry - his work has led to over £30M of savings and new products in industry. He also contributes to the development of Open Science principles and practice for Africa and for Modelling & Simulation as a field. He has led modules in distributed computing in the Department of Computer Science for many years with high module evaluations scores and is an enthusiastic teacher. He has also led the development of several postgraduate degrees. He has supervised over 20 doctoral students, has examined more than 25 doctoral students from across the world and has managed over 15 research fellows. Professor Taylor co-founded and is a former Editor-in-Chief of the Journal of Simulation and the UK Operational Research Society Simulation Workshop Series. He chaired ACM SIGSIM between 2005-2008 and since then has been an active member of the ACM SIGSIM Steering Committee. He is also the General Chair for the 2025 Winter Simulation Conference. He has chaired international standardisation groups under the Simulation Interoperability Standards Organization and has conducted several organisational review panels (e.g., DSTL) and simulation audits. He is currently the executive chair for the annual Simulation Exploration Experience ( and a member of the Computer Simulation Archive steering committee ( He has also chaired several conferences and is the General Chair for the IEEE/ACM 2025 Winter Simulation Conference. Interested in the history of computer simulation? Visit the Computer Simulation Archive hosted by NCSU and hear talks from some of the pioneers in computer simulation. I am strongly interested in Modelling & Simulation and Digital Infrastructures, particularly in the development of high performance simulation infrastructures and services in industry and health care. These are extremely important as it allows users to perform more simulation experimentation and to get deeper insight into their problems. This has openned up a new area of study that is allowing us to develop novel AI-based optimisation techniques for Modelling & Simulation that leverage our high performance simulation infrastructures that we have already deployed in industry (e.g., Ford, Saker Solutions and Sellafield). In parallel with these interests I have been able to work towards the development of digital infrastructures and services in Africa. This has contributed to the rapid development of African National Research and Education Networks and the foundation for African Open Science. This work continues and we are working with African stakeholders to further develop African Open Science and Data Science approaches across the continent. In turn these experiences have enabled me to contribute to Open Science techniques for Modelling & Simulation, as well as Open Science at Brunel. Modelling & Simulation Digital Infrastructures and Services Cloud Computing International Development Open Science I teach a variety of subjects from Modelling & Simulation to Distributed Computing at Undergraduate, Postgraduate and National levels (e.g. NATCOR). I also support student projects and (unpaid) internships in these areas.
Groen
i am a lecturer in simulation and modelling at brunel university. i'm also an emeritus fellow for the epsrc-funded 2020 science network, a fellow of the software sustainability institute, and a visiting lecturer at the centre for computational science at university college london. i completed an msc in grid computing at the university of amsterdam (uva) in 2006, and a phd in computational astrophysics both at the uva and leiden university in november 2010. after my phd i worked as a post-doctoral researcher on eu projects about distributed multiscale computing (mapper) and high-performance computing towards the exascale (cresta). i received a 1-year position as a fellow of 2020 science in january 2015, and funded myself for two months through an epsrc ecse to work on new approaches for domain decomposition. i joined brunel university in september 2015 to become a lecturer and i currently collaborate in the eu compat project about multiscale computing towards the exascale. i have published >20 peer-reviewed journal papers in venues such as ieee computer, ieee cise, journal of computational science, phil. trans. r. soc. a., physics review e., the astrophysical journal and elife. in addition, i was second author of the first ever feature article in advanced materials, which was on multiscale modelling of clay-polymer nanocomposites and received news coverage from the daily telegraph and the bbc. i currently run science hackathons to efficiently establish new interdisciplinary collaborations. i am an interdisciplinary researcher who focuses primarily on multiscale modelling and high-performance computing, but takes along some of the major challenges that surround these topics. these include performance modelling and optimization, distributed computing, new approaches for code coupling, and techniques to make intensive computational research easier and more efficient. in terms of applications, i currently model bloodflow in cerebral arteries (using lattice-boltzmann), and self-assembly processes in layered materials (using molecular dynamics methods). i have worked with a number of other models before (e.g., dark matter simulations to resolve structure formation in the universe), and i am likely to pick up new applications as i proceed with my career. 2015/2016 – service oriented architectures (msc module) 2015/2016 – data visualization (msc module)
![Dr Derek Groen]()
Dr Derek Groen
I am a Lecturer in Simulation and Modelling at Brunel University. I'm also an Emeritus Fellow for the EPSRC-funded 2020 Science Network, a Fellow of the Software Sustainability Institute, and a Visiting Lecturer at the Centre for Computational Science at University College London. I completed an MSc in Grid Computing at the University of Amsterdam (UvA) in 2006, and a PhD in Computational Astrophysics both at the UvA and Leiden University in November 2010. After my PhD I worked as a post-doctoral researcher on EU projects about distributed multiscale computing (MAPPER) and high-performance computing towards the Exascale (CRESTA). I received a 1-year position as a Fellow of 2020 Science in January 2015, and funded myself for two months through an EPSRC eCSE to work on new approaches for domain decomposition. I joined Brunel University in September 2015 to become a Lecturer and I currently collaborate in the EU ComPat project about multiscale computing towards the Exascale. I have published >20 peer-reviewed journal papers in venues such as IEEE Computer, IEEE CiSE, Journal of Computational Science, Phil. Trans. R. Soc. A., Physics Review E., the Astrophysical Journal and eLife. In addition, I was second author of the first ever feature article in Advanced Materials, which was on multiscale modelling of clay-polymer nanocomposites and received news coverage from the Daily Telegraph and the BBC. I currently run Science Hackathons to efficiently establish new interdisciplinary collaborations. I am an interdisciplinary researcher who focuses primarily on multiscale modelling and high-performance computing, but takes along some of the major challenges that surround these topics. These include performance modelling and optimization, distributed computing, new approaches for code coupling, and techniques to make intensive computational research easier and more efficient. In terms of applications, I currently model bloodflow in cerebral arteries (using lattice-Boltzmann), and self-assembly processes in layered materials (using molecular dynamics methods). I have worked with a number of other models before (e.g., dark matter simulations to resolve structure formation in the universe), and I am likely to pick up new applications as I proceed with my career. 2015/2016 – Service Oriented Architectures (Msc module) 2015/2016 – Data Visualization (Msc module)
Ghinea
i am a professor in the department of computer science at ÃÛÌÒ´«Ã½. i obtained my bsc. degree with computer science and mathematics majors from the university of the witwatersrand, south africa. i later went on to obtain bsc. (hons.) and msc. degrees, both in computer science, from the same university. i was awarded my phd – quality of perception: an essential facet of multimedia communications - from the university of reading, uk, in 2000. in it, i proposed the quality of perception metric, a precursor of the quality of experience (qoe) concept now widely known. however, whilst qoe is still a concept, qop is a concrete metric. thus, recognising the infotainment duality of multimedia, qop not only characterises the subjective enjoyment associated with experiencing multimedia presentations, but also how such presentations aid a person\'s ability to assimilate informational content. my research activities lie at the confluence of computer science, media and psychology. in particular, my work focuses on the area of perceptual multimedia quality and how one builds end-to-end communication systems incorporating user perceptual requirements. i have applied my expertise in areas such as eye-tracking, telemedicine, multi-modal interaction, and ubiquitous and mobile computing. i am particularly interested in building human-centred e-systems, particularly integrating human perceptual requirements. my work has been funded by both national and international funding bodies – all of it being collaborative work with other teams and stakeholders i have been privileged to be involved with. i have also been honoured to supervise 33 phd students to completion and to have published over 350 high-quality research articles with them and other research collaborators. currently, my research pursuits are centered on extending the notion of multimedia with that of mulsemedia – a term which i have put forward to denote multiple sensorial media, ie. media applications that go beyond engaging the by now traditional auditory and visual senses, engaging three of our other human in a realistic manner akin to our experiences of everyday life. • multimedia and multimodal interactive environments• mulsemedia applications and environments• adaptive, cross-layer communication systems• human-centred e-systems• mobile and pervasive computing• communications security • multimedia and multimodal interactive environments • mulsemedia applications and environments • adaptive, cross-layer communication systems • human-centred e-systems • mobile and pervasive computing • communications security i currently lead the level 7 postgraduate module research project management.
![Professor George Ghinea]()
Professor George Ghinea
I am a Professor in the Department of Computer Science at ÃÛÌÒ´«Ã½. I obtained my BSc. Degree with Computer Science and Mathematics majors from the University of the Witwatersrand, South Africa. I later went on to obtain BSc. (Hons.) and MSc. Degrees, both in Computer Science, from the same university. I was awarded my PhD – Quality of Perception: An Essential Facet of Multimedia Communications - from the University of Reading, UK, in 2000. In it, I proposed the Quality of Perception metric, a precursor of the Quality of Experience (QoE) concept now widely known. However, whilst QoE is still a concept, QoP is a concrete metric. Thus, recognising the infotainment duality of multimedia, QoP not only characterises the subjective enjoyment associated with experiencing multimedia presentations, but also how such presentations aid a person\'s ability to assimilate informational content. My research activities lie at the confluence of Computer Science, Media and Psychology. In particular, my work focuses on the area of perceptual multimedia quality and how one builds end-to-end communication systems incorporating user perceptual requirements. I have applied my expertise in areas such as eye-tracking, telemedicine, multi-modal interaction, and ubiquitous and mobile computing. I am particularly interested in building human-centred e-systems, particularly integrating human perceptual requirements. My work has been funded by both national and international funding bodies – all of it being collaborative work with other teams and stakeholders I have been privileged to be involved with. I have also been honoured to supervise 33 PhD students to completion and to have published over 350 high-quality research articles with them and other research collaborators. Currently, my research pursuits are centered on extending the notion of multimedia with that of mulsemedia – a term which I have put forward to denote multiple sensorial media, ie. media applications that go beyond engaging the by now traditional auditory and visual senses, engaging three of our other human in a realistic manner akin to our experiences of everyday life. • Multimedia and multimodal interactive environments• Mulsemedia applications and environments• Adaptive, cross-layer communication systems• Human-centred e-systems• Mobile and pervasive computing• Communications security • Multimedia and multimodal interactive environments • Mulsemedia applications and environments • Adaptive, cross-layer communication systems • Human-centred e-systems • Mobile and pervasive computing • Communications security I currently lead the level 7 postgraduate module Research Project Management.
Suleimenova
i am a lecturer in the department of computer science at ÃÛÌÒ´«Ã½. i am a member the modelling & simulation group and the computer science for social good research groups. my​​ research concentrates on agent-based modelling, forced displacement prediction, and verification, validation and uncertainty quantification (vvuq) of multiscale applications deployed on emerging exascale platforms. i worked as a research fellow in multiscale migration prediction for the horizon 2020 projects, namely verified exascale computing for multiscale applications (vecma), hpc and big data technologies for global systems (hidalgo) and it tools and methods for managing migration flows (itflows). currently, i am a knowledge exchange coordinator for the software environment for actionable and vvuq-evaluated applications (seavea), which aims to develop an exascale-ready toolkit for vvuq techniques in application to various domains. i am interested in predicting and forecasting forced displacement movements using an agent-based modelling. modelling and simulation, agent-based modelling, forced displacement prediction, verification, validation and uncertainty quantification currently, i am the module leader for a second-year cs2007 icts in society module. it is a core module for the business computing degree. moreover, i am a tutor for first-year undergraduate students (cs1701 group project lectures and tutorials module). i also supervise the cs3072-cs3605 final year projects and msc dissertations (cs5500) in computer science.
![Dr Diana Suleimenova]()
Dr Diana Suleimenova
I am a Lecturer in the Department of Computer Science at ÃÛÌÒ´«Ã½. I am a member the Modelling & Simulation Group and the Computer Science for Social Good research groups. My​​ research concentrates on agent-based modelling, forced displacement prediction, and verification, validation and uncertainty quantification (VVUQ) of multiscale applications deployed on emerging exascale platforms. I worked as a Research Fellow in Multiscale Migration Prediction for the Horizon 2020 projects, namely Verified Exascale Computing for Multiscale Applications (VECMA), HPC and Big Data Technologies for Global Systems (HiDALGO) and IT tools and methods for managing migration FLOWS (ITFLOWS). Currently, I am a Knowledge Exchange coordinator for the Software Environment for Actionable and VVUQ-evaluated Applications (SEAVEA), which aims to develop an exascale-ready toolkit for VVUQ techniques in application to various domains. I am interested in predicting and forecasting forced displacement movements using an agent-based modelling. Modelling and Simulation, Agent-based Modelling, Forced Displacement Prediction, Verification, Validation and Uncertainty Quantification Currently, I am the module leader for a second-year CS2007 ICTs in Society module. It is a core module for the Business Computing degree. Moreover, I am a tutor for first-year undergraduate students (CS1701 Group Project Lectures and Tutorials module). I also supervise the CS3072-CS3605 Final year projects and MSc dissertations (CS5500) in Computer Science.
Anagnostou
dr anastasia anagnostou is a senior lecturer in the department of computer science at ÃÛÌÒ´«Ã½ and the co-lead of the modelling & simulation group (msg). she is also member of the intelligent data analytics (ida) group. she holds a phd in distributed modelling & simulation, an msc in telemedicine and e-health systems and a bsc(hons) in electronic engineering. her research interests lie in the areas of advanced computing infrastructures for modelling and simulation, open science for simulation, hybrid distributed simulation and modelling and simulation for healthcare and industrial applications. since 2011, she has been involved in several interdisciplinary research projects with stakeholders from industry and academia across manufacturing, healthcare, defence and food supply chains. she has also worked in africa helping to develop digital infrastructures and collaborative services enabling open science. she is co-chair for the or society’s simulation workshop (sw21) and member of organising committees for international conferences sponsored by the ieee and acm/sigsim. she has been awarded horizon 2020 funding for a 9.5 million euro project (brunel contribution €370k) entitled “demonstration of intelligent decision support for pandemic crisis prediction and management within and across european borders” (stamina). modelling and simulation, distributed simulation, cloud computing, open science, e-infrastructures, healthcare systems, internet of things cs2005 networks and operating systems (module leader) cs2001 level 2 group project cs2555 work placement cs3004 network computing cs3072-3605 computer science/business computing final-year projects cs5601 enterprise modelling (module reviewer) i also taught: introduction to programming, business analysis and process modelling, systems project management, erp systems theory and practise, erp systems deployment and configuration and sap erp integration of business processes certification course (terp-10).
![Dr Anastasia Anagnostou]()
Dr Anastasia Anagnostou
Dr Anastasia Anagnostou is a Senior Lecturer in the Department of Computer Science at ÃÛÌÒ´«Ã½ and the co-lead of the Modelling & Simulation Group (MSG). She is also member of the Intelligent Data Analytics (IDA) Group. She holds a PhD in Distributed Modelling & Simulation, an MSc in Telemedicine and e-Health Systems and a BSc(Hons) in Electronic Engineering. Her research interests lie in the areas of Advanced Computing Infrastructures for Modelling and Simulation, Open Science for Simulation, Hybrid Distributed Simulation and Modelling and Simulation for Healthcare and Industrial Applications. Since 2011, she has been involved in several interdisciplinary research projects with stakeholders from industry and academia across manufacturing, healthcare, defence and food supply chains. She has also worked in Africa helping to develop digital infrastructures and collaborative services enabling open science. She is co-chair for the OR Society’s Simulation Workshop (SW21) and member of organising committees for international conferences sponsored by the IEEE and ACM/SIGSIM. She has been awarded Horizon 2020 funding for a 9.5 million Euro project (Brunel contribution €370K) entitled “Demonstration of intelligent decision support for pandemic crisis prediction and management within and across European borders” (STAMINA). Modelling and Simulation, Distributed Simulation, Cloud Computing, Open Science, e-Infrastructures, Healthcare Systems, Internet of Things CS2005 Networks and Operating Systems (Module Leader) CS2001 Level 2 Group Project CS2555 Work Placement CS3004 Network Computing CS3072-3605 Computer Science/Business Computing Final-Year Projects CS5601 Enterprise Modelling (Module reviewer) I also taught: Introduction to Programming, Business Analysis and Process Modelling, Systems Project Management, ERP Systems Theory and Practise, ERP Systems Deployment and Configuration and SAP ERP Integration of Business Processes Certification Course (TERP-10).
Mintram
dr katie mintram is an associate lecturer in the department of computer science at ÃÛÌÒ´«Ã½ and is a member of the modelling and simulation group. with a background in environmental biology, katie's research is centred around simulating the emergent behaviours of complex systems. she has developed simulation models to aid decision making in the fields of ecotoxicology, epidemiology, public health, supply chain resilience, microbiology, climate change biology and fisheries science. katie completed her bsc at the university of plymouth in 2014 with an industrial placement year at astrazeneca, where she developed in vitro alternatives to animal testing. she completed her phd in agent-based simulation at the university of exeter in 2019 within the college of life and environmental sciences. her phd and subsequent postdoctoral research centred around the development and application of agent-based models for realistic predictions of chemical exposure effects on fish populations. katie joined brunel in 2021 as a research fellow working in the stamina project, a horizon2020 funded project which developed a toolset for pandemic crisis prediction and management across europe. prior to joining brunel, katie also spent a year as an animal welfare consultant in the ngo sector, and is a fellow of the higher education academy. agent-based modelling ecological modelling (fisheries, bioenergetics, ecotoxicology, genetic resistance) healthcare (epidemiological modelling) utilising data science and machine learning tools for big data analysis and visualisations
![Dr Kate Mintram]()
Dr Kate Mintram
Dr Katie Mintram is an Associate Lecturer in the Department of Computer Science at ÃÛÌÒ´«Ã½ and is a member of the Modelling and Simulation group. With a background in Environmental Biology, Katie's research is centred around simulating the emergent behaviours of complex systems. She has developed simulation models to aid decision making in the fields of ecotoxicology, epidemiology, public health, supply chain resilience, microbiology, climate change biology and fisheries science. Katie completed her BSc at the University of Plymouth in 2014 with an industrial placement year at AstraZeneca, where she developed in vitro alternatives to animal testing. She completed her PhD in agent-based simulation at the University of Exeter in 2019 within the College of Life and Environmental Sciences. Her PhD and subsequent postdoctoral research centred around the development and application of agent-based models for realistic predictions of chemical exposure effects on fish populations. Katie joined Brunel in 2021 as a Research Fellow working in the STAMINA project, a Horizon2020 funded project which developed a toolset for pandemic crisis prediction and management across Europe. Prior to joining Brunel, Katie also spent a year as an animal welfare consultant in the NGO sector, and is a Fellow of the Higher Education Academy. Agent-based modelling Ecological modelling (fisheries, bioenergetics, ecotoxicology, genetic resistance) Healthcare (epidemiological modelling) Utilising data science and machine learning tools for big data analysis and visualisations
Abubakar
diligent and strategic software engineer with 20+ years of experience in the it industry. strong background in developing, implementing, and applying information and data system management practices. shaped through operative and technical roles within various-sized businesses & agencies. adept at monitoring systems, implementing technological solutions, and improving processes. academically founded in management information systems. cloud computing, distributed simulation, and agent-based modelling. cloud-based distributed modelling and simulation i built and demonstrated a cloud-based distributed simulation system that represents a world first in the area. distributed simulation involves linking together many simulations in real-time (e.g., simulations of hospitals across london) as though they are a single simulation (e.g., a comprehensive simulation of hospitals across london). the problem is that the simulations and the computers they run on are difficult to access. cloud computing offers a great alternative as these simulations can be run “in the cloud” and accessed by everyone who has permission. the computers they run on are hired just for the runs and there makes it incredibly cheap. the problem is that no one had figured out how to do this, and there are very few publications in the area (despite great demand). the research proposed a development framework to guide experienced and non-technical analysts in implementing cloud-based distributed simulation (cbds) and a scalable distributed simulation cloud architecture for experimentation (dice). experimental results demonstrated its feasibility and how to use cloud to perform high-performance simulation. a world first basically. modules cybersecurity network and operating systems network computing business analysis and process modelling
![Dr Nura Abubakar]()
Dr Nura Abubakar
Associate Lecturer (Education)
Diligent and strategic Software Engineer with 20+ years of experience in the IT industry. Strong background in developing, implementing, and applying information and data system management practices. Shaped through operative and technical roles within various-sized businesses & agencies. Adept at monitoring systems, implementing technological solutions, and improving processes. Academically founded in Management Information Systems. Cloud Computing, Distributed Simulation, and Agent-Based Modelling. Cloud-Based Distributed Modelling and Simulation I built and demonstrated a cloud-based distributed simulation system that represents a world first in the area. Distributed simulation involves linking together many simulations in real-time (e.g., simulations of hospitals across London) as though they are a single simulation (e.g., a comprehensive simulation of hospitals across London). The problem is that the simulations and the computers they run on are difficult to access. Cloud computing offers a great alternative as these simulations can be run “in the Cloud” and accessed by everyone who has permission. The computers they run on are hired just for the runs and there makes it incredibly cheap. The problem is that no one had figured out how to do this, and there are very few publications in the area (despite great demand). The research proposed a development framework to guide experienced and non-technical analysts in implementing cloud-based distributed simulation (CBDS) and a scalable Distributed simulation Cloud Architecture for Experimentation (DICE). Experimental results demonstrated its feasibility and how to use Cloud to perform high-performance simulation. A world first basically. Modules Cybersecurity Network and Operating Systems Network Computing Business Analysis and Process Modelling
Jahani
working as a research fellow in coupled agent-based modelling at computer science department, ÃÛÌÒ´«Ã½, uk. before joining ÃÛÌÒ´«Ã½, he was the deputy of technical and information services and assistant professor at faculty of information technology, mehralborz university (mau), iran. machine learning knowledge management supply chain analytics agent-based modelling multi-agent systems
![Dr Alireza Jahani]()
Dr Alireza Jahani
Working as a Research Fellow in Coupled Agent-based Modelling at Computer Science Department, ÃÛÌÒ´«Ã½, UK. Before joining ÃÛÌÒ´«Ã½, He was the Deputy of Technical and Information Services and Assistant Professor at Faculty of Information Technology, Mehralborz University (MAU), Iran. Machine Learning Knowledge Management Supply Chain Analytics Agent-Based Modelling Multi-Agent Systems
Xue
dr. yani xue received the m.sc. degree in web technology from university of southampton, southampton, uk, in 2015, and the ph.d. degree in computer science from ÃÛÌÒ´«Ã½, london, uk, in 2021. she is currently a lecturer in the department of computer science, ÃÛÌÒ´«Ã½, uk. multi-/many-objective optimization (optimization problems with many conflictingobjectives, optimization problems expensive to evaluate, optimization problems underuncertainty) evolutionary computation (design of evolutionary algorithms) intelligent data analytics (artificial intelligence, high performance data analytics) engineering applications (search-based software engineering) modelling and simulation (agent-based modelling, forced displacement prediction) modules supported include: cs1702 introductory programming cs2002 software development and management
![Dr Yani Xue]()
Dr Yani Xue
Dr. Yani Xue received the M.Sc. degree in Web Technology from University of Southampton, Southampton, UK, in 2015, and the Ph.D. degree in Computer Science from ÃÛÌÒ´«Ã½, London, UK, in 2021. She is currently a Lecturer in the Department of Computer Science, ÃÛÌÒ´«Ã½, UK. Multi-/Many-Objective Optimization (Optimization problems with many conflictingobjectives, Optimization problems expensive to evaluate, Optimization problems underuncertainty) Evolutionary Computation (Design of evolutionary algorithms) Intelligent Data Analytics (Artificial intelligence, High performance data analytics) Engineering Applications (Search-based software engineering) Modelling and Simulation (Agent-based modelling, Forced displacement prediction) Modules supported include: CS1702 Introductory Programming CS2002 Software Development and Management
Ghorbani
as an associate lecturer with a multidisciplinary background in electronics engineering, microelectronics system design, experimental physics, and computer science, dr maziar ghorbani is committed to fostering academic excellence and nurturing the next generation of innovators. with a strong passion for interdisciplinary teaching and research, dr ghorbani specialises in modeling and simulations, large-scale high-performance distributed computing, machine learning and computer vision, as well as sensor instrumentation and iot. his dedication to student engagement and experiential learning drives the creation of cutting-edge projects designed to challenge and inspire future computer scientists. dr ghorbani is focused on exploring the limitless possibilities at the intersection of technology, science, and education. dr maziar ghorbani's research interests lie at the forefront of artificial intelligence (ai), with a specific focus on generative ai and its transformative potential across various industries. he is also keenly interested in game engines and rendering technologies, exploring how these tools can be applied to enhance simulations and visualisation. additionally, dr ghorbani has a deep interest in computer languages and programming, continually seeking to optimise computational efficiency and explore new paradigms in software development. dr maziar ghorbani’s research encompasses a broad range of cutting-edge areas in computer science and engineering. his work focuses on high-performance computing, where he explores innovative techniques and architectures for efficient distributed and parallel computing systems. he also specialises in large-scale simulations, particularly in agent-based and geospatial modelling, optimising these simulations to address complex systems. in the field of artificial intelligence, dr ghorbani integrates machine learning and computer vision techniques with sensor instrumentation and iot systems, advancing the capabilities of automated sensing, data processing, and intelligent decision-making. this interdisciplinary approach enhances real-time data analysis and system performance across various applications. dr ghorbani is also deeply engaged in ensuring the accuracy and reliability of simulations through verification, validation, and uncertainty quantification methods. his research includes advanced simulation visualisation, where he utilises real-time 3d tools to enhance understanding and interpretation of simulation outcomes. further, his expertise in high-level architecture (hla) and distributed systems contributes to the optimisation of collaborative space simulations, facilitating large-scale and complex multi-agent environments. dr ghorbani’s work on interactive systems extends to robotics, real-time visualisation, and human-computer interactions, fostering developments in both scientific research and practical applications.
![Dr Maziar Ghorbani]()
Dr Maziar Ghorbani
As an Associate Lecturer with a multidisciplinary background in Electronics Engineering, Microelectronics System Design, Experimental Physics, and Computer Science, Dr Maziar Ghorbani is committed to fostering academic excellence and nurturing the next generation of innovators. With a strong passion for interdisciplinary teaching and research, Dr Ghorbani specialises in Modeling and Simulations, Large-scale High-performance Distributed Computing, Machine Learning and Computer Vision, as well as Sensor Instrumentation and IoT. His dedication to student engagement and experiential learning drives the creation of cutting-edge projects designed to challenge and inspire future computer scientists. Dr Ghorbani is focused on exploring the limitless possibilities at the intersection of technology, science, and education. Dr Maziar Ghorbani's research interests lie at the forefront of artificial intelligence (AI), with a specific focus on generative AI and its transformative potential across various industries. He is also keenly interested in game engines and rendering technologies, exploring how these tools can be applied to enhance simulations and visualisation. Additionally, Dr Ghorbani has a deep interest in computer languages and programming, continually seeking to optimise computational efficiency and explore new paradigms in software development. Dr Maziar Ghorbani’s research encompasses a broad range of cutting-edge areas in computer science and engineering. His work focuses on high-performance computing, where he explores innovative techniques and architectures for efficient distributed and parallel computing systems. He also specialises in large-scale simulations, particularly in agent-based and geospatial modelling, optimising these simulations to address complex systems. In the field of artificial intelligence, Dr Ghorbani integrates machine learning and computer vision techniques with sensor instrumentation and IoT systems, advancing the capabilities of automated sensing, data processing, and intelligent decision-making. This interdisciplinary approach enhances real-time data analysis and system performance across various applications. Dr Ghorbani is also deeply engaged in ensuring the accuracy and reliability of simulations through verification, validation, and uncertainty quantification methods. His research includes advanced simulation visualisation, where he utilises real-time 3D tools to enhance understanding and interpretation of simulation outcomes. Further, his expertise in high-level architecture (HLA) and distributed systems contributes to the optimisation of collaborative space simulations, facilitating large-scale and complex multi-agent environments. Dr Ghorbani’s work on interactive systems extends to robotics, real-time visualisation, and human-computer interactions, fostering developments in both scientific research and practical applications.