Agius
harry has research and teaching expertise in various aspects of digital media, games and creative computing. he is the section editor for track 4 (digital games, virtual reality, and augmented reality) of the multimedia tools and applications journal (springer). he was co-editor of the handbook of digital games (ieee/wiley, 2014). personalisation of digital media and digital games using creative computing techniques, particularly ai-based methods digital media and digital games harry has taught a wide variety of subjects in digital media, games and creative computing during his career. his current teaching responsibilities are in the areas of digital experiences, digital futures and emerging technologies, and responsive web development.
Dr Harry Agius
Harry has research and teaching expertise in various aspects of digital media, games and creative computing. He is the Section Editor for Track 4 (Digital Games, Virtual Reality, and Augmented Reality) of the Multimedia Tools and Applications journal (Springer). He was co-editor of the Handbook of Digital Games (IEEE/Wiley, 2014). Personalisation of digital media and digital games using creative computing techniques, particularly AI-based methods Digital media and digital games Harry has taught a wide variety of subjects in digital media, games and creative computing during his career. His current teaching responsibilities are in the areas of digital experiences, digital futures and emerging technologies, and responsive web development.
Angelides
marios c. angelides is a computer scientist, chartered engineer (ceng) and a chartered fellow of the british computer society (fbcs citp). he holds a bsc (first class honours) and a phd both in computing and both from the london school of economics (lse) where he also began his academic career more than three decades ago specializing in artificial intelligence (ai). a symbolic programming language he developed as a degree finalist for coding ai applications was commercialized and then turned into his first book. he continued working on ai throughout his career and for the last two decades, he has been researching the application of creative computing techniques, such as machine learning, serious gaming, and cognitive modelling, recently in developing smart iot apps. during this period, he published several books, including “multimedia information systems” (kluwer), “mpeg applications” (wiley), and “digital games” (ieee/wiley). in 2016, several years prior to joining the computer journal (oxford university press) editorial board, a paper of his that was published in the computer journal with a focus on “machine learning in multimedia” was the runner up winner of the annual oxford university press “2016 wilkes award”. in 2019 he was elected to the editorial board of the computer journal for which he is now serving as a deputy editor. in 2023 the computer journal celebrated its 65th anniversary with editorial perspectives on key articles by esteemed international authors from across the journal’s long history. the focus of marios' editorial perspective is on a visionary article on expert systems from 1980 by the late professor donald michie that truly resonates. creative computing (machine learning, serious gaming, and cognitive modelling) for developing smart iot apps
Professor Marios Angelides
Marios C. Angelides is a Computer Scientist, Chartered Engineer (CEng) and a Chartered Fellow of the British Computer Society (FBCS CITP). He holds a BSc (First Class Honours) and a PhD both in Computing and both from the London School of Economics (LSE) where he also began his academic career more than three decades ago specializing in Artificial Intelligence (AI). A symbolic programming language he developed as a degree finalist for coding AI applications was commercialized and then turned into his first book. He continued working on AI throughout his career and for the last two decades, he has been researching the application of creative computing techniques, such as machine learning, serious gaming, and cognitive modelling, recently in developing smart IoT apps. During this period, he published several books, including “Multimedia Information Systems” (Kluwer), “MPEG Applications” (Wiley), and “Digital Games” (IEEE/Wiley). In 2016, several years prior to joining The Computer Journal (Oxford University Press) editorial board, a paper of his that was published in The Computer Journal with a focus on “machine learning in multimedia” was the runner up winner of the annual Oxford University Press “2016 Wilkes Award”. In 2019 he was elected to the Editorial Board of The Computer Journal for which he is now serving as a Deputy Editor. In 2023 The Computer Journal celebrated its 65th anniversary with editorial perspectives on key articles by esteemed international authors from across the journal’s long history. The focus of Marios' editorial perspective is on a visionary article on Expert Systems from 1980 by the late Professor Donald Michie that truly resonates. Creative Computing (machine learning, serious gaming, and cognitive modelling) for developing smart IoT apps
Daylamani-Zad
damon is a senior lecturer in creative computing (ai and games). applications of ai in games and digital media machine learning & evolutionary algorithms (neural networks, genetic algorithm, swarm intelligence) games, serious games and gamification accessibility design in games and digital media extended reality (xr) and immersive technologies: ar, vr and mr computer generated music damon's main research activities are within the creative computing, games and digital media domain, and are specifically focused on applications of artificial intelligence in games and digital media including collaborative content modelling, serious gaming, immersive technologies in cultural heritage, immersive technologies in training and education, gamification for accessibility design and user modelling and personalisation. he has worked on using machine learning for automated music generation, strategy planning, user modelling and game personalisation, use of artificial intelligence (swarm intelligence) in strategic and serious games, use of gamification for accessibility design and serious games for reading interventions in dyslexia. he has been involved in various projects funded by the epsrc, ahrc, nih, the bikeability trust and department for transport. the results of his projects have been adapted for personalisation in mmogs (artemis) and in developing frameworks for collaborative decision-making games (lu-lu and responsive lu-lu).
Dr Damon Daylamani-Zad
Damon is a Senior Lecturer in Creative Computing (AI and Games). Applications of AI in Games and Digital Media Machine Learning & Evolutionary Algorithms (Neural Networks, Genetic Algorithm, Swarm Intelligence) Games, Serious Games and Gamification Accessibility Design in Games and Digital Media Extended Reality (xR) and Immersive Technologies: AR, VR and MR Computer Generated Music Damon's main research activities are within the Creative Computing, Games and Digital Media domain, and are specifically focused on Applications of Artificial Intelligence in Games and Digital Media including Collaborative Content Modelling, Serious Gaming, Immersive technologies in cultural heritage, Immersive technologies in training and education, Gamification for accessibility design and User Modelling and Personalisation. He has worked on using Machine Learning for automated music generation, strategy planning, user modelling and game personalisation, use of Artificial Intelligence (swarm intelligence) in strategic and serious games, use of gamification for accessibility design and serious games for reading interventions in Dyslexia. He has been involved in various projects funded by the EPSRC, AHRC, NIH, the Bikeability Trust and Department for Transport. The results of his projects have been adapted for personalisation in MMOGs (Artemis) and in developing frameworks for collaborative decision-making games (Lu-Lu and responsive Lu-Lu).
Gan
dr. lu gan received her b. eng and m. eng. degrees from south east university, china and the ph.d degree from nanyang technological university, singapore in 1998, 2000 and 2004 respectively. she is currently a senior lecturer (equivalent to associate professor) in brunel university, london. before she joined brunel university in 2008, she has been on the faculties with the university of newcastle (2004-2006), australia and university of liverpool, uk (2006-2007). from 2003 to 2004, she was a research associate in centre for signal processing, nanyang technological university. dr. gan’s research interests include fundamental signal processing theories and their applications in image/video coding and processing, non-destructive terahertz and ultrasound imaging, machine learning and wireless communications etc. her research work has been funded by australian research council, the engineering and physical sciences research council (epsrc) uk and twi uk. she is a member of ieee and a regular reviewer for many top journals including ieee transactions on information theory, ieee transactions on signal processing, ieee transactions on communications and ieee transactions on image processing etc. she has also been reviewing research grants in uk epsrc and uk stfc and fwo in belgium (equivalent to epsrc in uk). she has been on the technical committee member for conferences including globecom and icc. so far, she has more than 30 publications on journals with high impact factor and more than 60 conference publications. she has been working as ph. d thesis/viva examiner for more than 20 candidates in uk and australia. her google scholar file can be found here. her current research focus include: 1) fast compressive imaging for infared and terahertz imaging; 2) super-resolution in non-destructive imaging; 3) deep learning for terahertz imaging; 4) sparse antenna array; 5) sparse signal processing for 5g wireless communication systems dr. l. gan’s main research interests are in fundamental signal processing theory and their application in multimedia signal processing, machine learning, wireless communications and radar. ee 2600 communications (50%) ee 3040 digital communications (67%) ee 5511 advanced digital communications (100%) ee5612//5653: communication network security (50%)
Dr Lu Gan
Dr. Lu Gan received her B. Eng and M. Eng. degrees from South East University, China and the Ph.D degree from Nanyang Technological University, Singapore in 1998, 2000 and 2004 respectively. She is currently a senior lecturer (equivalent to associate professor) in Brunel University, London. Before she joined Brunel University in 2008, she has been on the faculties with The University of Newcastle (2004-2006), Australia and University of Liverpool, UK (2006-2007). From 2003 to 2004, she was a research associate in Centre for Signal Processing, Nanyang Technological University. Dr. Gan’s research interests include fundamental signal processing theories and their applications in image/video coding and processing, non-destructive terahertz and ultrasound imaging, machine learning and wireless communications etc. Her research work has been funded by Australian research council, The Engineering and Physical Sciences Research Council (EPSRC) UK and TWI UK. She is a member of IEEE and a regular reviewer for many top journals including IEEE Transactions on Information theory, IEEE Transactions on Signal Processing, IEEE transactions on Communications and IEEE transactions on image processing etc. She has also been reviewing research grants in UK EPSRC and UK STFC and FWO in Belgium (equivalent to EPSRC in UK). She has been on the technical committee member for conferences including Globecom and ICC. So far, she has more than 30 publications on journals with high impact factor and more than 60 conference publications. She has been working as Ph. D thesis/viva examiner for more than 20 candidates in UK and Australia. Her google scholar file can be found here. Her current research focus include: 1) Fast compressive imaging for Infared and Terahertz imaging; 2) Super-resolution in non-destructive imaging; 3) Deep learning for Terahertz imaging; 4) Sparse antenna array; 5) Sparse signal processing for 5G wireless communication systems Dr. L. Gan’s main research interests are in fundamental signal processing theory and their application in multimedia signal processing, machine learning, wireless communications and radar. EE 2600 Communications (50%) EE 3040 Digital Communications (67%) EE 5511 Advanced Digital Communications (100%) EE5612//5653: Communication Network Security (50%)
Li
education phd in software engineering, institute of software, chinese academy of sciences, 1997. msc in image processing, department of computer science, north university of china, 1994. bsc in computer science, department of computer science, north university of china, 1991. employment oct 2013 - present, professor, dept. of electronic and computer engineering, brunel university london oct 2009 - sept 2013, senior lecturer, dept. of electronic and computer engineering, brunel university london feb 2002 - sept 2009, lecturer, dept. of electronic and computer engineering, brunel university london jan 1999 - jan 2002, post-doctoral research associate, school of computer science, cardiff university high performance computing mpi, grid computing, cloud computing big data analytics data intensive applications with mapreduce/hadoop smart grids, spam filtering, image annotation, information retrieval, financial risk management knowledge and data engineering context aware mobile computing, knowledge discovery with rough sets, semantic web, ontology alignment data mining and machine learning deep learning for human re-dientification based on walking patterns mobile sensing for large scale urban air quality estimation, which explores real-time and fine-grained air quality information (pm2.5, pm10, so2) throughout a city, based on the (historical and real-time) air quality data reported by constructing large-scale mobile sensing nodes (e.g. low-cost sensors) and a variety of data sources observed in the city, such as meteorology, traffic flow, structure of road networks, and point of interests (pois). computer networks network computing high performance computing
Professor Maozhen Li
Education PhD in Software Engineering, Institute of Software, Chinese Academy of Sciences, 1997. MSc in Image Processing, Department of Computer Science, North University of China, 1994. BSc in Computer Science, Department of Computer Science, North University of China, 1991. Employment Oct 2013 - present, Professor, Dept. of Electronic and Computer Engineering, Brunel University London Oct 2009 - Sept 2013, Senior Lecturer, Dept. of Electronic and Computer Engineering, Brunel University London Feb 2002 - Sept 2009, Lecturer, Dept. of Electronic and Computer Engineering, Brunel University London Jan 1999 - Jan 2002, Post-Doctoral Research Associate, School of Computer Science, Cardiff University High Performance Computing MPI, Grid computing, Cloud computing Big Data Analytics Data intensive applications with MapReduce/Hadoop smart grids, spam filtering, image annotation, information retrieval, financial risk management Knowledge and Data Engineering Context aware mobile computing, knowledge discovery with rough sets, Semantic Web, ontology alignment Data Mining and Machine Learning Deep learning for human re-dientification based on walking patterns Mobile sensing for large scale urban air quality estimation, which explores real-time and fine-grained air quality information (PM2.5, PM10, SO2) throughout a city, based on the (historical and real-time) air quality data reported by constructing large-scale mobile sensing nodes (e.g. low-cost sensors) and a variety of data sources observed in the city, such as meteorology, traffic flow, structure of road networks, and point of interests (POIs). Computer Networks Network Computing High Performance Computing
Liu
xiaohui liu is professor of computing at brunel university london where he conducts research in artificial intelligence, data science and optimization, with applications in diverse areas including biomedicine and engineering. xiaohui has held senior visiting positions in leiden, harvard and chinese academy of sciences, advised uk research councils on data analytics, genomics and security as well as the royal statistical society/the institute and faculty of actuaries on statistical education at uk schools in light of big data. professor liu founded the international symposium series on intelligent data analysis (1995 & 1997), served on the international panel to assess the quality of computer science research in the netherlands (2015-16), and since 2014, he has been named as a highly cited researcher for 10 consecutive years in computer science, engineering, or cross-field (clarivate/web of science). professor liu has been an investigator on a number of grants (see below) in research areas including ai, bioinformatics, complex networks, data science, deep learning, engineering and manufacturing, healthcare, optimisation, sentiment analysis, and statistical pattern recognition. modules led at brunel include: algorithms and their applications artificial intelligence research methods software development and management modules supported include: advanced topics in computer science data management & business intelligence distributed/predictive data analysis final year projects machine learning modern data msc projects year 2 group projects
Professor Xiaohui Liu
Xiaohui Liu is Professor of Computing at Brunel University London where he conducts research in artificial intelligence, data science and optimization, with applications in diverse areas including biomedicine and engineering. Xiaohui has held senior visiting positions in Leiden, Harvard and Chinese Academy of Sciences, advised UK Research Councils on data analytics, genomics and security as well as the Royal Statistical Society/the Institute and Faculty of Actuaries on statistical education at UK schools in light of big data. Professor Liu founded the international symposium series on Intelligent Data Analysis (1995 & 1997), served on the international panel to assess the quality of computer science research in the Netherlands (2015-16), and since 2014, he has been named as a Highly Cited Researcher for 10 consecutive years in Computer Science, Engineering, or Cross-Field (Clarivate/Web of Science). Professor Liu has been an investigator on a number of grants (see below) in research areas including AI, bioinformatics, complex networks, data science, deep learning, engineering and manufacturing, healthcare, optimisation, sentiment analysis, and statistical pattern recognition. Modules led at Brunel include: Algorithms and Their Applications Artificial Intelligence Research Methods Software Development and Management Modules supported include: Advanced Topics in Computer Science Data Management & Business Intelligence Distributed/Predictive Data Analysis Final Year Projects Machine Learning Modern Data MSc Projects Year 2 Group Projects
Meng
dr hongying meng is a reader with department of electronic and electrical engineering, college of engineering, design and physical sciences, brunel university london. before that, he held research positions in several uk universities including university college london (ucl), university of york, university of southampton, university of lincoln, and university of dundee. he received his ph.d. degree in communication and electronic systems from xi’an jiaotong university and was a lecturer in electronic engineering department of tsinghua university, beijing in china. he is a member of engineering professors’ council, and a fellow of the higher education academy (hea) in uk. he is a senior member of ieee and an associate editor for ieee transactions on circuits and systems for video technology (tcsvt) and ieee transactions on cognitive and developmental systems (tcds). digital signal processing: wavelet transform; digital filtering; statistical signal processing; audio signal processing; mechanical signal processing (fault detection), biomedical signal processing (e.g. ecg, eeg, emg, gsr); real-time signal processing. machine learning: support vector machine (svm); kernel methods; artificial neural networks; genetic algorithm; genetic programming, feature selection and fusion; bayesian methods; hidden markov model (hmm); deep learning; long short term memory (lstm), convolutional neural network (cnn), generative adversarial network (gan), multi-label classification; statistical learning theory; multi-score learning, multiple classifier system, decision fusion, data mining, regression, spiking neural networks, neuromorphic computing. human computer interaction: affective computing; emotional states recognition; facial expression analysis; multi-model interaction; movement modelling; gesture recognition, ubiquitous and pervasive computing; robot; self-driving car, ambient intelligence; multimodal emotional interaction system; interactive film; and virtual reality (vr). computer vision: biologically inspired vision systems; dynamic motion feature extraction; human action recognition; object detection; object tracking; visual surveillance; image compression; large scale image categorization; image segmentation; real-time image processing; medical image processing (ct, fmri); embedded vision systems; 3d image processing, holoscopic imaging; autonomous driving systems. embedded systems and communications: fpga; microcontroller (pic, arm); dsp (ti); smart phones; tablet; game consoles, soc (system on chip), iot (internet of things), controller area network (can), wireless networks and communication (zigbee, bluetooth, ook, visible light communication, mmwave communication). digital systems and microprocessors (fheq level 4) electronic engineering workshop (fheq level 4) computer architecture and interfacing (fheq level 5) engineering group design project (fheq level 5) advanced embedded systems design (fheq level 7, meng & msc)
Dr Hongying Meng
Dr Hongying Meng is a Reader with Department of Electronic and Electrical Engineering, College of Engineering, Design and Physical Sciences, Brunel University London. Before that, he held research positions in several UK universities including University College London (UCL), University of York, University of Southampton, University of Lincoln, and University of Dundee. He received his Ph.D. degree in Communication and Electronic Systems from Xi’an Jiaotong University and was a lecturer in Electronic Engineering Department of Tsinghua University, Beijing in China. He is a Member of Engineering Professors’ Council, and a Fellow of The Higher Education Academy (HEA) in UK. He is a Senior Member of IEEE and an associate editor for IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) and IEEE Transactions on Cognitive and Developmental Systems (TCDS). Digital Signal Processing: wavelet transform; digital filtering; statistical signal processing; audio signal processing; mechanical signal processing (fault detection), biomedical signal processing (e.g. ECG, EEG, EMG, GSR); real-time signal processing. Machine Learning: Support Vector Machine (SVM); kernel methods; artificial neural networks; genetic algorithm; genetic programming, feature selection and fusion; Bayesian methods; Hidden Markov Model (HMM); deep learning; Long Short Term Memory (LSTM), Convolutional Neural Network (CNN), Generative Adversarial Network (GAN), multi-label classification; statistical learning theory; multi-score learning, multiple classifier system, decision fusion, data mining, regression, spiking neural networks, neuromorphic computing. Human Computer Interaction: affective computing; emotional states recognition; facial expression analysis; multi-model interaction; movement modelling; gesture recognition, ubiquitous and pervasive computing; robot; self-driving car, ambient intelligence; multimodal emotional interaction system; interactive film; and virtual reality (VR). Computer Vision: biologically inspired vision systems; dynamic motion feature extraction; human action recognition; object detection; object tracking; visual surveillance; image compression; large scale image categorization; image segmentation; real-time image processing; medical image processing (CT, fMRI); embedded vision systems; 3D image processing, Holoscopic imaging; autonomous driving systems. Embedded Systems and Communications: FPGA; microcontroller (PIC, ARM); DSP (TI); smart phones; tablet; game consoles, SoC (System on Chip), IoT (Internet of Things), Controller Area Network (CAN), wireless networks and communication (ZigBee, Bluetooth, OOK, visible light communication, mmWave communication). Digital Systems and Microprocessors (FHEQ Level 4) Electronic Engineering Workshop (FHEQ Level 4) Computer Architecture and Interfacing (FHEQ Level 5) Engineering Group Design Project (FHEQ Level 5) Advanced Embedded Systems Design (FHEQ Level 7, MEng & MSc)
Nilavalan
dr. r. nilavalan obtained the b.sc. eng. in electrical & electronic engineering (first class) from university of peradeniya, srilanka in 1995 and his phd in near-field microwave imaging from university of bristol, uk in 2001. from 1999 to 2005 he was a researcher at centre for communications research (ccr), bristol university working in the field of radio frequency engineering. he was member of the european commission, network of excellence on antennas from 2002 - 2005. he joined brunel university london in september 2005 as a lecturer in wireless communications. professional memberships and services senior member of the ieee member of the iet fellow of the higher education academy 5g and beyond communication systems, antennas and propagation, beamforming and phased arrays, emergency communication systems microwave systems use of radio and microwave frequencies in automotive and biomedical applications for past and present projects please refer the personal web wireless communication systems, radio frequency and microwave systems, non-destructive testing and sensing radio and optical communication systems (ee5550/ee5150, msc) advanced electronics (ee3049/ee3601) communication systems (ee2640, level 5) electronic systems (ee2604, level 5)
Dr Nila Nilavalan
Dr. R. Nilavalan obtained the B.Sc. Eng. in Electrical & Electronic Engineering (First Class) from University of Peradeniya, SriLanka in 1995 and his PhD in Near-field microwave imaging from University of Bristol, UK in 2001. From 1999 to 2005 he was a researcher at Centre for Communications Research (CCR), Bristol University working in the field of Radio Frequency Engineering. He was member of the European commission, Network of Excellence on Antennas from 2002 - 2005. He joined Brunel University London in September 2005 as a lecturer in wireless communications. Professional Memberships and Services Senior member of the IEEE Member of the IET Fellow of the Higher Education Academy 5G and beyond Communication Systems, Antennas and Propagation, Beamforming and Phased Arrays, Emergency Communication Systems Microwave Systems Use of Radio and microwave frequencies in Automotive and Biomedical applications For past and present projects please refer the personal web Wireless Communication Systems, Radio Frequency and Microwave Systems, Non-destructive testing and sensing Radio and Optical Communication Systems (EE5550/EE5150, MSc) Advanced Electronics (EE3049/EE3601) Communication Systems (EE2640, Level 5) Electronic Systems (EE2604, Level 5)
Serrano-Rico
dr. alan serrano is a reader in the department of computer science at brunel university london, uk, where he also received his phd in information systems and an msc in data communication systems. he is now the chair of the industry advisory board, department industry lead & brunel talent marketplace director. previous to his appointment at brunel he has worked in industry and public sectors in mexico for a number of years, in the areas of computer networks and information systems development. his research interest lies in the area of information systems and organisational strategy. more specifically, dr serrano focuses on undertaking research that aims to solve the real-life challenges organisations face when adopting information and communication technologies (ict) in complex environments. some examples of collaboration with industry includes bmw group in uk, axa insurance uk, pepsico latin america, the national health service (nhs) in uk, centrica energy uk, jaguar & land rover uk, and standard chartered uk. dr serrano has exposed his work in more than 26 publications in recognised journals and international conferences such as the european journal of information systems, electronic markets, the international journal of information management, and the international journal of enterprise information systems. i would not like to box myself into a specific area, as i believe the information systems domain expands in many directions and i find all of these fascinating. i have done research on health care, programme management, and business process and simulation to mention a few. most of my formal research however, lies within the area of information system and business strategy. today i am very passionate about finding effective ways for dissemination of academic knowledge to wider audiences; applying academic research in real context (industry) and the social network phenomena in general. during my academic career, i have taught a number of subjects ranging from the social (is in context) to the technical (java programming, erps, and telecommunications). today my teaching responsibilities are: module leader for cs1703 data and information the aim of this module is to provide students with a comprehensive introduction to different kinds of data and the means by which it can be collected, stored, retrieved, analysed and then communicated in order to achieve the goal of satisfying user information needs. module teaching contributor for cs2006 business analysis and process modelling and cs3072 computer science fyp
Dr Alan Serrano-Rico
Dr. Alan Serrano is a Reader in the Department of Computer Science at Brunel University London, UK, where he also received his PhD in Information Systems and an MSc in Data Communication Systems. He is now the Chair of the Industry advisory board, Department Industry Lead & Brunel Talent Marketplace Director. Previous to his appointment at Brunel he has worked in industry and public sectors in Mexico for a number of years, in the areas of computer networks and information systems development. His research interest lies in the area of information systems and organisational strategy. More specifically, Dr Serrano focuses on undertaking research that aims to solve the real-life challenges organisations face when adopting information and communication technologies (ICT) in complex environments. Some examples of collaboration with industry includes BMW group in UK, AXA Insurance UK, PepsiCo Latin America, the National Health Service (NHS) in UK, Centrica Energy UK, Jaguar & Land Rover UK, and Standard Chartered UK. Dr Serrano has exposed his work in more than 26 publications in recognised journals and international conferences such as the European Journal of Information Systems, Electronic Markets, the International Journal of Information Management, and the International Journal of Enterprise Information Systems. I would not like to box myself into a specific area, as I believe the Information Systems domain expands in many directions and I find all of these fascinating. I have done research on health care, programme management, and business process and simulation to mention a few. Most of my formal research however, lies within the area of information system and business strategy. Today I am very passionate about finding effective ways for dissemination of academic knowledge to wider audiences; applying academic research in real context (industry) and the social network phenomena in general. During my academic career, I have taught a number of subjects ranging from the social (IS in context) to the technical (Java Programming, ERPs, and Telecommunications). Today my teaching responsibilities are: Module leader for CS1703 Data and Information The aim of this module is to provide students with a comprehensive introduction to different kinds of data and the means by which it can be collected, stored, retrieved, analysed and then communicated in order to achieve the goal of satisfying user information needs. Module teaching contributor for CS2006 Business Analysis and Process Modelling and CS3072 Computer Science FYP
Swash
dr rafiq swash joined the department of electronic and computer engineering, college of engineering, design and physical sciences, brunel university london, uk in 2013. before that, he held research positions in the area of multimedia search & retrieval systems, expert systems and 3d imaging & display systems at brunel university london. he received his ph.d. degree in holoscopic 3d imaging systems: camera / processing / display from brunel university london, uk. he is a member of ieee, iet, ieee broadcast technology society, the optical society america (osa), and the society for information display (sid). in the past, dr swash has worked as a senior software engineer, senior technical architect, technical director and chief technology officer in international gaming, financial and robotics industries. dr swash has a wide research interests includes 3d imaging and display systems (3d cameras / 3d display / 3d processing), 3d virtual reality / augment reality, 3d computer vision, medical image processing & visualisation, multimedia search & retrieval, human-computer interaction design, interactive game design including serious games and gamification advanced 3d imaging systems: holoscopic and multiview 3d displays, holoscopic 3d cameras, 3d image processing 3d image reformatting advanced 3d computer graphics multiscopic and stereoscopic 3d systems 3d visual engineering / 3d multimedia search and retrieval 3d virtual reality / 3d augmented reality 3d interaction and interactive serious gaming design human-computer interaction design medical image processing and visualisation 2d/3d computer vision advanced multimedia design and 3d technologies msc 3d film design and production | ee5565 multimedia and interaction design | ee5557 digital design and branding msc digital media technologies | ee5504 digital design bsc interaction design & usability | ee1706 advanced 3d imaging systems | ee3617
Dr Mohammad Swash
Dr Rafiq Swash joined the Department of Electronic and Computer Engineering, College Of Engineering, Design and Physical Sciences, Brunel University London, UK in 2013. Before that, he held research positions in the area of multimedia search & retrieval systems, expert systems and 3D imaging & display systems at Brunel University London. He received his Ph.D. degree in Holoscopic 3D Imaging Systems: Camera / Processing / Display from Brunel University London, UK. He is a member of IEEE, IET, IEEE Broadcast Technology Society, The Optical Society America (OSA), and The Society for Information Display (SID). In the past, Dr Swash has worked as a senior software engineer, senior technical architect, technical director and chief technology officer in international gaming, financial and robotics industries. Dr Swash has a wide research interests includes 3D imaging and display systems (3D cameras / 3D display / 3D processing), 3D virtual reality / augment reality, 3D computer vision, medical image processing & visualisation, multimedia search & retrieval, human-computer interaction design, interactive game design including serious games and gamification Advanced 3D imaging Systems: holoscopic and multiview 3D displays, holoscopic 3D cameras, 3D image processing 3D image reformatting Advanced 3D computer graphics Multiscopic and stereoscopic 3D systems 3D visual engineering / 3D multimedia search and retrieval 3D virtual reality / 3D augmented reality 3D Interaction and interactive serious gaming design human-computer interaction design Medical image processing and visualisation 2D/3D Computer vision Advanced Multimedia Design and 3D Technologies MSc 3D Film Design and Production | EE5565 Multimedia and Interaction Design | EE5557 Digital Design and Branding MSc Digital Media Technologies | EE5504 Digital Design BSc Interaction Design & Usability | EE1706 Advanced 3D Imaging Systems | EE3617
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
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.
Wang
zidong wang is a member of academia europaea, a member of the european academy of sciences and arts, an ieee fellow and professor of computing at brunel university london, uk. he has research interests in intelligent data analysis, statistical signal processing and dynamic systems & control. he has been named as the hottest scientific researcher in 2012 in the area of big data and listed as highly cited researchers in categories of both computer science and engineering in 2015-2020 with an h-index of 139. he is currently serving as the editor-in-chief for international journal of systems science, the editor-in-chief for neurocomputing, the editor-in-chief for systems science and control engineering, and associate editor for other 12 prestigious journals including 5 ieee transactions. his research has been funded by the eu, the royal society and the epsrc. intelligent data analysis (data modelling, data mining, data classification, data quality evaluation, neural networks, fuzzy systems, statistical identification), statistical signal processing (digital filter design, envelope-constrained filter, signal processing for uncertain systems, optimal filtering and deconvolution, multi-rate and filter banks), dynamical systems and control (stochastic control, robust control and estimation, h-infinity control, model reduction, sampled-data systems, time-delay systems, nonlinear systems, multi-dimensional systems, fuzzy control, robot control). introduction to computing, artificial intelligence, data and information, construction of programs, software engineering methods
Professor Zidong Wang
Zidong Wang is a member of Academia Europaea, a Member of the European Academy of Sciences and Arts, an IEEE Fellow and Professor of Computing at Brunel University London, UK. He has research interests in intelligent data analysis, statistical signal processing and dynamic systems & control. He has been named as the Hottest Scientific Researcher in 2012 in the area of Big Data and listed as highly cited researchers in categories of both computer science and engineering in 2015-2020 with an h-index of 139. He is currently serving as the Editor-in-Chief for International Journal of Systems Science, the Editor-in-Chief for Neurocomputing, the Editor-in-Chief for Systems Science and Control Engineering, and Associate Editor for other 12 prestigious journals including 5 IEEE Transactions. His research has been funded by the EU, the Royal Society and the EPSRC. Intelligent Data Analysis (Data modelling, Data mining, Data classification, Data quality evaluation, Neural Networks, Fuzzy systems, Statistical identification), Statistical Signal Processing (Digital filter design, Envelope-constrained filter, Signal processing for uncertain systems, Optimal filtering and deconvolution, Multi-rate and filter banks), Dynamical Systems and Control (Stochastic control, Robust control and estimation, H-infinity control, Model reduction, Sampled-data systems, Time-delay systems, Nonlinear systems, Multi-dimensional systems, Fuzzy control, Robot control). Introduction to Computing, Artificial Intelligence, Data and Information, Construction of Programs, Software Engineering Methods