Yang
dr qingping yang is currently the group leader for brunel quality engineering and smart technology (quest) research group and robotics and automation research group. dr yang joined the brunel centre for manufacturing metrology (bcmm) in 1988 with a visiting scholarship awarded by the avic, after his graduation in instrumentation and measurement technology from chengdu aeronautical polytechnic in 1983 and subsequent 4 years’ research experiences at an aircraft structure research institute (avic, xi’an) and admission to an msc programme in robot control and intelligent control at northwestern polytechnical university. in 1989, he was awarded an ors award and a phd studentship from british technology group to develop a patented smart 3d high precision probe system for cmms, and he received his phd degree in october 1992. since then he has been working as a research fellow, lecturer/senior lecturer/reader (associate professor) at brunel university london. he has actively participated in 15 (11 as principal investigator) research projects funded by the uk government, eu and industrial companies, with a total funding of about £2.5 million as principal investigator and £888k as co-investigator. through more than 30 years dedicated research, he has developed a unique and coherent research field broadly integrating three research areas of sensor/measurement systems, quality engineering and smart technologies (including ai and robotics) with rigorous theoretical foundation, addressing the core science and technology underpinning these areas. he has published more than 110 journal/conference papers, 5 book chapters and 3 patents (one patent successfully assigned for commercial exploitation in 2004) in these areas. he has supervised (as the 1st supervisor) 20 phd and 3 mphil students with successful completion as well as 9 visiting academic staff / phd students, and he is currently supervising one postdoctoral research fellow and 8 phd students. dr yang has received numerous prizes and awards for outstanding academic and work performance in the past (including three performance bonuses in brunel university). he has been a member of ieee and iet. he was profiled in the 15th edition of marquis who’s who in the world (1998) and the 5th edition of marquis who’s who in science and engineering (2000). dr yang has been developing a unique and coherent research field broadly integrating the following three research areas for more than 30 years: sensor / measurement systems: advanced sensors and robot sensing (including tactile, force, optical proximity and stereo vision); 3d dimensional metrology (including cmms, virtual cmms, afms); 3d freeform surface measurement (including fringe projection); intelligent instrumentation; advanced data analytics; measurement science. quality engineering: quality engineering (including robust design, triz and intelligent process control); lean six sigma; condition monitoring and structural integrity; safety and risk management; environment monitoring. uncertainty quantification; integrated quality tools and information systems; quality science. smart technologies and applications: robotics and autonomous systems (including cognitive robots; collaborative robots; robots for measurements, inspection and maintenance; medical robots; mobile robots); human-robot interaction; vr/ar/mr; iot; data science; machine learning and artificial intelligence; generalised information theory; knowledge based systems; ontology engineering; semantic web; cognition and neuroscience; smart technology applications (e.g. smart manufacturing; smart buildings; smart maintenance; smart healthcare; industry 4.0). dr yang has taught a number of subjects at both pg/ug levels and his teaching is closely related to his research: pg level (level 7): robotics and manufacturing automation; manufacturing measurement; optical and optoelectronic engineering; project management; computation for information processing and computer-aided data analysis. ug levels (level 4-6): computer integrated manufacturing (level 6); quality engineering and metrology (level 6); business for engineers (level 6); mechatronics (level 5); microprocessors (level 5); electrical engineering principles (level 5); instruments and applications (level 5); measurement and instrumentation (level 5); introduction to internet computing (level 4); internet scripting and computer architecture (level 4); project management (levels 4-5). he is currently teaching: ai applications in engineering (level 6) quality management and reliability (level 7) advanced measurement systems and data analysis (level 7)
Dr Qingping Yang
Dr QingPing Yang is currently the Group Leader for Brunel Quality Engineering and Smart Technology (QUEST) Research Group and Robotics and Automation Research Group. Dr Yang joined the Brunel Centre for Manufacturing Metrology (BCMM) in 1988 with a visiting scholarship awarded by the AVIC, after his graduation in Instrumentation and Measurement Technology from Chengdu Aeronautical Polytechnic in 1983 and subsequent 4 years’ research experiences at an Aircraft Structure Research Institute (AVIC, Xi’an) and admission to an MSc Programme in Robot Control and Intelligent Control at Northwestern Polytechnical University. In 1989, he was awarded an ORS Award and a PhD Studentship from British Technology Group to develop a patented smart 3D high precision probe system for CMMs, and he received his PhD degree in October 1992. Since then he has been working as a Research Fellow, Lecturer/Senior Lecturer/Reader (Associate Professor) at Brunel University London. He has actively participated in 15 (11 as Principal Investigator) research projects funded by the UK government, EU and industrial companies, with a total funding of about £2.5 million as Principal Investigator and £888K as Co-Investigator. Through more than 30 years dedicated research, he has developed a unique and coherent research field broadly integrating three research areas of sensor/measurement systems, quality engineering and smart technologies (including AI and robotics) with rigorous theoretical foundation, addressing the core science and technology underpinning these areas. He has published more than 110 journal/conference papers, 5 book chapters and 3 patents (one patent successfully assigned for commercial exploitation in 2004) in these areas. He has supervised (as the 1st supervisor) 20 PhD and 3 MPhil students with successful completion as well as 9 visiting academic staff / PhD students, and he is currently supervising one postdoctoral Research Fellow and 8 PhD students. Dr Yang has received numerous prizes and awards for outstanding academic and work performance in the past (including three performance bonuses in Brunel University). He has been a member of IEEE and IET. He was profiled in the 15th edition of Marquis Who’s Who in the World (1998) and the 5th edition of Marquis Who’s Who in Science and Engineering (2000). Dr Yang has been developing a unique and coherent research field broadly integrating the following three research areas for more than 30 years: Sensor / measurement systems: Advanced sensors and robot sensing (including tactile, force, optical proximity and stereo vision); 3D dimensional metrology (including CMMs, virtual CMMs, AFMs); 3D freeform surface measurement (including fringe projection); Intelligent instrumentation; Advanced data analytics; Measurement science. Quality engineering: Quality engineering (including robust design, TRIZ and intelligent process control); Lean six sigma; Condition monitoring and structural integrity; Safety and risk management; Environment monitoring. Uncertainty quantification; Integrated quality tools and information systems; Quality science. Smart technologies and applications: Robotics and autonomous systems (including Cognitive robots; Collaborative robots; Robots for measurements, inspection and maintenance; Medical robots; Mobile robots); Human-Robot Interaction; VR/AR/MR; IoT; Data science; Machine learning and artificial intelligence; Generalised information theory; Knowledge based systems; Ontology engineering; Semantic web; Cognition and neuroscience; Smart technology applications (e.g. Smart manufacturing; Smart buildings; Smart maintenance; Smart healthcare; Industry 4.0). Dr Yang has taught a number of subjects at both PG/UG levels and his teaching is closely related to his research: PG level (Level 7): Robotics and Manufacturing Automation; Manufacturing Measurement; Optical and Optoelectronic Engineering; Project Management; Computation for Information Processing and Computer-Aided Data Analysis. UG levels (Level 4-6): Computer Integrated Manufacturing (level 6); Quality Engineering and Metrology (level 6); Business for Engineers (level 6); Mechatronics (level 5); Microprocessors (level 5); Electrical Engineering Principles (level 5); Instruments and Applications (level 5); Measurement and Instrumentation (level 5); Introduction to Internet Computing (level 4); Internet Scripting and Computer Architecture (level 4); Project Management (levels 4-5). He is currently teaching: AI Applications in Engineering (Level 6) Quality Management and Reliability (Level 7) Advanced Measurement Systems and Data Analysis (Level 7)
Wang
dr fang wang is a senior lecturer in the department of computer science at brunel university london. she received a phd in artificial intelligence from the university of edinburgh and worked as a senior researcher in the research centre of british telecom (bt) group, before she joined brunel university london in 2010. dr. wang has published a number of papers in books, journals and conferences and filed a series of patents. dr. wang is an established teacher and researcher in computer science and artificial intelligence. her research interests include nature-inspired computing, agents, intelligent information processing, intelligent distributed computing, cognitive radio networks, e-learning and cloud education, cognitive science and computer vision. she actively participated in a number of eu, epsrc, bt long term research projects and received several technical awards, including the gordon radley technical premium highly commended award of bt and acm best student paper award at the third international conference on autonomous agents. she is on the editorial boards of several international journals and serves on many program committees. dr. wang’s main research interest is in artificial intelligence and its applications. this includes using nature-inspired techniques such as intelligent agents, swarm intelligence, evolutionary computing and neural networks to solve real world applications such as network optimisation, radio spectrum management, decentralised computing, user analysis, self-organising communities, and so on. lectured, administered, tutored and examined courses at undergraduate and msc levels on topics including introduction to programming, algorithms and their applications, systems in context, digital innovation, level 1 and level 2 group projects and final year projects. class sizes varied from 8 to 350. supervised a number of undergraduate and msc projects.
Dr Fang Wang
Dr Fang Wang is a Senior Lecturer in the Department of Computer Science at Brunel University London. She received a PhD in artificial intelligence from the University of Edinburgh and worked as a senior researcher in the research centre of British Telecom (BT) Group, before she joined Brunel University London in 2010. Dr. Wang has published a number of papers in books, journals and conferences and filed a series of patents. Dr. Wang is an established teacher and researcher in computer science and artificial intelligence. Her research interests include nature-inspired computing, agents, intelligent information processing, intelligent distributed computing, cognitive radio networks, e-learning and cloud education, cognitive science and computer vision. She actively participated in a number of EU, EPSRC, BT long term research projects and received several technical awards, including the Gordon Radley Technical Premium Highly Commended award of BT and ACM Best Student Paper Award at the Third International Conference on Autonomous Agents. She is on the editorial boards of several international journals and serves on many program committees. Dr. Wang’s main research interest is in artificial intelligence and its applications. This includes using nature-inspired techniques such as intelligent agents, swarm intelligence, evolutionary computing and neural networks to solve real world applications such as network optimisation, radio spectrum management, decentralised computing, user analysis, self-organising communities, and so on. Lectured, administered, tutored and examined courses at undergraduate and MSc levels on topics including Introduction to programming, Algorithms and their applications, Systems in Context, Digital Innovation, level 1 and level 2 group projects and final year projects. Class sizes varied from 8 to 350. Supervised a number of undergraduate and MSc 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)
Wang
bin wang graduated with beng (1985) in solid mechanics from xi’an jiaotong university, msc (1988) by research in dynamics and phd (1991) in applied mechanics, both from university of manchester (formerly umist). he had been an academic staff member of nanyany technological university (singapore), deakin (australia), brunel, manchester and aberdeen university before returning to brunel in july 2011. at brunel he has held roles as the chairperson of the board of study in mechanical, aerospace and automotive engineering, year 1 tutor, programme director of msc structural integrity, and now the vice dean internatioanl of the college. dr wang’s expertise is in applied mechanics, including stress and strain analysis, dynamics and impact mechanics. he also conducts research in reliability and safety analysis with application in energy and medical areas. his research contributed to the british energy’s r3 document on impact assessment of nuclear power plants. under the title shooting cancers, his research also presented at the royal society summer science exhibition (2004). dr. wang is also one of the inventors of a patented knee implant which is a leading product in the north american market. structural response under impact material behaviour under high strain rate loading design of energy absorption systems foams, cellulous and sandwich materials biomaterials and surgical devices nano scale materials uncertainty, reliability and parametric sensitivity multi-physics phenomenon dr. wang has delivered a wide range of subjects in the subject area of applied mechanics at both undergraduate and postgraduate levels, including strength of materials, vector calculus, vibration and machine dynamics, plasticity, mechanism and design, advanced reliability analysis, fracture and fatigue, etc. current teaching modules: me3062/me3092 fea, cfd and design of engineering systems mn5561 computer aided design 2
Dr Bin Wang
Bin Wang graduated with BEng (1985) in Solid Mechanics from Xi’an Jiaotong University, MSc (1988) by research in Dynamics and PhD (1991) in Applied Mechanics, both from University of Manchester (formerly UMIST). He had been an academic staff member of Nanyany Technological University (Singapore), Deakin (Australia), Brunel, Manchester and Aberdeen University before returning to Brunel in July 2011. At Brunel he has held roles as the Chairperson of the Board of Study in Mechanical, Aerospace and Automotive Engineering, Year 1 Tutor, Programme Director of MSc Structural Integrity, and now the Vice Dean Internatioanl of the College. Dr Wang’s expertise is in Applied Mechanics, including stress and strain analysis, dynamics and impact mechanics. He also conducts research in reliability and safety analysis with application in energy and medical areas. His research contributed to the British Energy’s R3 document on Impact Assessment of nuclear power plants. Under the title Shooting Cancers, his research also presented at the Royal Society Summer Science Exhibition (2004). Dr. Wang is also one of the inventors of a patented knee implant which is a leading product in the North American market. Structural response under impact Material behaviour under high strain rate loading Design of energy absorption systems Foams, cellulous and sandwich materials Biomaterials and surgical devices Nano scale materials Uncertainty, Reliability and Parametric Sensitivity Multi-physics phenomenon Dr. Wang has delivered a wide range of subjects in the subject area of Applied Mechanics at both undergraduate and postgraduate levels, including Strength of Materials, Vector Calculus, Vibration and Machine Dynamics, Plasticity, Mechanism and Design, Advanced Reliability Analysis, Fracture and Fatigue, etc. Current teaching modules: ME3062/ME3092 FEA, CFD and Design of Engineering Systems MN5561 Computer Aided Design 2
Xu
dr xu is a tribologist and has extensive knowledge in the subjects of manufacturing engineering, engineering materials, mechanical engineering and product design & development. he is very experienced in the area of precision machining, failure analysis for the engineering products, and the area of materials application in support of the engineering products in the oil and gas field. his significant contributions in the research of materials and manufacturing have managed to attract funding from epsrc and major industrial companies such as bp and shell. he is also often approached by various companies to provide technical consultancy on materials properties and applications, product design, and failure analysis. dr xu has published 30 research and technical papers in the leading international journals. brief biography dr xu obtained his phd from the university of southampton in 2004. after completing his phd study, he worked as a postdoctoral research fellow for 5 years at university of cambridge, leeds university and brunel university london. before he joined brunel university london in july 2010, he worked as a materials and forensic engineer at john crane ltd, at where he obtained extensive industrial experience. dr xu obtained his master’s degree from korea advanced institute of science and technology (kaist) in 1998, and his bachelor’s degree from harbin university of science and technology in 1993, china. i am currently interested in the research area of printing materials and devices using the inkjet printing technology. specialities:module leader for workshops with materials, lecturer in materials and manufacturing systems, specialising in engineering materials, mechanical engineering, manufacturing engineering and product design & development. module leader for dm1602, workshops with materials module teaching contributor for dm1309, mechanics supervision msc, phd research students and final year undergraduate students
Dr Yanmeng Xu
Dr Xu is a tribologist and has extensive knowledge in the subjects of Manufacturing Engineering, Engineering Materials, Mechanical Engineering and Product Design & Development. He is very experienced in the area of precision machining, failure analysis for the engineering products, and the area of materials application in support of the engineering products in the oil and gas field. His significant contributions in the research of materials and manufacturing have managed to attract funding from EPSRC and major industrial companies such as BP and Shell. He is also often approached by various companies to provide technical consultancy on materials properties and applications, product design, and failure analysis. Dr Xu has published 30 research and technical papers in the leading international journals. Brief biography Dr Xu obtained his PhD from the University of Southampton in 2004. After completing his PhD study, he worked as a postdoctoral research fellow for 5 years at University of Cambridge, Leeds University and Brunel University London. Before he joined Brunel University London in July 2010, he worked as a Materials and Forensic Engineer at John Crane Ltd, at where he obtained extensive industrial experience. Dr Xu obtained his Master’s degree from Korea Advanced Institute of Science and Technology (KAIST) in 1998, and his Bachelor’s degree from Harbin University of Science and Technology in 1993, China. I am currently interested in the research area of printing materials and devices using the Inkjet Printing Technology. Specialities:Module Leader for Workshops with Materials, Lecturer in Materials and Manufacturing Systems, specialising in Engineering Materials, Mechanical Engineering, Manufacturing Engineering and Product Design & Development. Module leader for DM1602, Workshops with Materials Module teaching contributor for DM1309, Mechanics Supervision MSc, PhD research students and final year undergraduate students