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
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
Itagaki
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 Take Itagaki
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)
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.
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%)
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)