Group Members

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. in 2024 the computer journal commemorated the 70th anniversary of the passing of alan mathison turing with the launch of the alan turing collection to celebrate both his long-lasting legacy and how his work still inspires research today. marios’ contribution to the collection reflects on how turing’s test which was the focus of his classic paper in mind from 1950, computing machinery and intelligence, still applies today. creative computing (machine learning, serious gaming, and cognitive modelling) for developing smart iot apps

Professor Marios Angelides

Divisional Lead / Professor - Computing

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. In 2024 The Computer Journal commemorated the 70th anniversary of the passing of Alan Mathison Turing with the launch of The Alan Turing Collection to celebrate both his long-lasting legacy and how his work still inspires research today. Marios’ contribution to the collection reflects on how Turing’s test which was the focus of his classic paper in Mind from 1950, computing machinery and intelligence, still applies today. Creative Computing (machine learning, serious gaming, and cognitive modelling) for developing smart IoT apps

Professor Maozhen Li

Vice-Dean of the NCUT TNE programme/Professor

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

Dr Take Itagaki

Senior Lecturer

Dr Takebumi ITAGAKI obtained a BEng from Waseda University (Japan) and a PhD in Engineering/Music from University of Durham (UK) in 1998. In 2000, he moved to Brunel University London as a Lecturer in Engineering. He contributed towards the several EU-IST FP5/FP6 research projects, including the SAVANT Project as the prime contractor and administrative coordinator, and the INSTINCT Project as the project manager. He was coordinating the EU CIP PSP Project DTV4All. His expertise include: Digital TV system (DVB, ISDB), Digital Signal Processing, Parallel Processing, Computer Music and Computer Architecture. Currently, he is one of the coordinators of ITU-T Focus Group Audio Visual Accessibility – Working Group D. Multimedia systems, digital signal processing, audio signal processing, Digital TV with Multimedia, IoT with Communciation applications EE2601 (Brunel) EE2623 (CQUPT) Computer Architecture and Interfacing EE3099/EE3600 Final Year Project (Brunel, CQUPT) EE5612 Communication Network Security (Brunel, to be delivered at Ahlia, Bharain) EE5500 Dissertation (Brunel, to be delivered at Ahlia, Bharain)

Dr Harry Agius

Senior Lecturer in Computing

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.

professor hongying meng is with department of electronic and electrical engineering at brunel university of london. before joining brunel, 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 bsc, msc and ph.d. degree in communication and electronic systems all from xi’an jiaotong university, xi'an, china. he then worked as a postdoc researcher and then a lecturer in electronic engineering department of tsinghua university, beijing, china before he moved to uk. his research area includes biomedical engineering, computer vision, affective computing, artificial intelligence, neuromorphic computing and internet of things. his research is funded by epsrc, eu horizon 2020, royal academy of engineering, royal society, etc. he has published more than 200 academic papers with more than 7000 citations (google scholar h-index 39). he has developed 2 different emotion recognition systems that won avec2011 and avec2013 international challenge competitions respectively. he is an ieee senior member since 2017 and an associate editor for ieee transactions on circuits and systems for video technology (tcsvt) and ieee transactions on cognitive and developmental systems (tcds). he is also an associate editors-in-chief for digital twins and applications (iet). he was recognized as one of the ai 2000 most influential scholars by aminer in 2022 and was listed as a top 2% scientist of the world (stanford/elsevier, single-year data sets) in 2023 and 2024. 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). microcontroller principles (fheq level 5) computer architecture and interfacing (fheq level 5) engineering group design project (fheq level 5) advanced embedded systems design (fheq level 7, meng & msc)

Professor Hongying Meng

Professor

Professor Hongying Meng is with Department of Electronic and Electrical Engineering at Brunel University of London. Before joining Brunel, 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 BSc, MSc and Ph.D. degree in Communication and Electronic Systems all from Xi’an Jiaotong University, Xi'an, China. He then worked as a postdoc researcher and then a lecturer in Electronic Engineering Department of Tsinghua University, Beijing, China before he moved to UK. His research area includes biomedical engineering, computer vision, affective computing, artificial intelligence, neuromorphic computing and Internet of Things. His research is funded by EPSRC, EU Horizon 2020, Royal Academy of Engineering, Royal Society, etc. He has published more than 200 academic papers with more than 7000 citations (Google Scholar h-index 39). He has developed 2 different emotion recognition systems that won AVEC2011 and AVEC2013 international challenge competitions respectively. He is an IEEE Senior Member since 2017 and an associate editor for IEEE Transactions on Circuits and Systems for Video Technology (TCSVT) and IEEE Transactions on Cognitive and Developmental Systems (TCDS). He is also an associate Editors-in-Chief for Digital Twins and Applications (IET). He was recognized as one of the AI 2000 Most Influential Scholars by Aminer in 2022 and was listed as a Top 2% Scientist of the World (Stanford/Elsevier, single-year data sets) in 2023 and 2024. 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). Microcontroller Principles (FHEQ Level 5) Computer Architecture and Interfacing (FHEQ Level 5) Engineering Group Design Project (FHEQ Level 5) Advanced Embedded Systems Design (FHEQ Level 7, MEng & MSc)