Abbod
education dr maysam f. abbod (fiet, ceng, smieee, sfhea) he received bsc degree in electrical engineering fromuniversity of technology in 1987. phd in control engineering fromuniversity ofsheffield in 1992. from 1993 to 2006 he was with the department of automatic control and systems engineering at theuniversity of sheffield as a research associate and senior research fellow his main research interests are in intelligent systems for modelling, control and optimisation. developed systems were applied to industrials and biomedical modelling, and computer control of manufacturing systems. the main research areas are: · intelligent systems biomedical applications. · modelling and control of electrical power quality. · stock exchange market modelling · intelligent systems for credit scoring · intelligent hybrid modelling and control of distillation column systems. · time series modelling. · hybrid modelling techniques (multivariate/time series). · developments of advanced process modelling, optimisation and control strategies · data mining and data driven modelling techniques. intelligent systems techniques includes fuzzy logic (fl), neural networks (nn), neuro-fuzzy systems (nfs), hybrid systems, genetic algorithms (gas), genetic programming (gp), particle swarm optimisation (pso), cellular automata (ca), non-linear principal component analysis (pca), support vector machine (svm), empirical model decomposition (emd). artificial intelligence, modelling and optimisation
Professor Maysam Abbod
Education Dr Maysam F. Abbod (FIET, CEng, SMIEEE, SFHEA) He received BSc degree in Electrical Engineering fromUniversity of Technology in 1987. PhD in Control Engineering fromUniversity ofSheffield in 1992. From 1993 to 2006 he was with the Department of Automatic Control and Systems Engineering at theUniversity of Sheffield as a research associate and senior research fellow His main research interests are in intelligent systems for modelling, control and optimisation. Developed systems were applied to industrials and biomedical modelling, and computer control of manufacturing systems. The main research areas are: · Intelligent systems biomedical applications. · Modelling and control of electrical power quality. · Stock exchange market modelling · Intelligent systems for credit scoring · Intelligent hybrid modelling and control of distillation column systems. · Time series modelling. · Hybrid modelling techniques (multivariate/time series). · Developments of advanced process modelling, optimisation and control strategies · Data mining and data driven modelling techniques. Intelligent systems techniques includes fuzzy logic (FL), neural networks (NN), neuro-fuzzy systems (NFS), hybrid systems, genetic algorithms (GAs), genetic programming (GP), particle swarm optimisation (PSO), cellular automata (CA), non-linear Principal component analysis (PCA), support vector machine (SVM), empirical model decomposition (EMD). Artificial Intelligence, Modelling and Optimisation
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)
Huda
dr m nazmul huda received his bsc (hons) degree in electrical and electronic engineering from bangladesh university of engineering and technology, bangladesh in 2008, his msc by research degree in computing science from staffordshire university, uk in 2011 and his ph.d. degree in robotics and control from bournemouth university, uk in 2016. at present, he is a senior lecturer in electronic and electrical engineering at brunel university london and supervising several phd students in robotics, artificial intelligence and renewable energy. before joining at brunel university london, he has held several academic/research positions at coventry university, cranfield university, bournemouth university, staffordshire university and bangladesh. he has more than ten years of experience in performing research and leading research projects in robotics, control and machine learning funded by various funding bodies including epsrc and innovate uk. he has filed a patent and published papers on flagship journals and conferences. he is a member of iet, ieee, ieee ras and epsrc associate peer review college. he has been nominated as a regular reviewer for epsrc grants applications. he has been collaborating with internal and external academic and industrial partners and actively developing research proposals as a pi and co-pi for internal and external funding calls including horizon 2020, wellcome trust and high-volume transport. he also serves as a reviewer for many flagship journals and conferences in robotics, control and artificial intelligence including ieee icra, ieee iros, ieee ssrr, ieee/asme transactions on mechatronics, ieee robotics and automation letters (ra-l) etc. robotics, control systems, mobile robot, capsule robot, capsule endoscopy, artificial intelligence, deep learning, sensor fusion, robotic (self-driving) cars, search and rescue robot, pipe inspection robot. dr m nazmul huda has more than five years of teaching experience in the uk (brunel university london, coventry university, bournemouth university and staffordshire university) and in bangladesh.
Dr Md Nazmul Huda
Dr M Nazmul Huda received his BSc (Hons) degree in Electrical and Electronic Engineering from Bangladesh University of Engineering and Technology, Bangladesh in 2008, his MSc by Research degree in Computing Science from Staffordshire University, UK in 2011 and his Ph.D. degree in Robotics and Control from Bournemouth University, UK in 2016. At present, he is a Senior Lecturer in Electronic and Electrical Engineering at Brunel University London and supervising several PhD students in robotics, artificial intelligence and renewable energy. Before joining at Brunel University London, he has held several academic/research positions at Coventry University, Cranfield University, Bournemouth University, Staffordshire University and Bangladesh. He has more than ten years of experience in performing research and leading research projects in robotics, control and machine learning funded by various funding bodies including EPSRC and Innovate UK. He has filed a patent and published papers on flagship journals and conferences. He is a member of IET, IEEE, IEEE RAS and EPSRC associate peer review college. He has been nominated as a regular reviewer for EPSRC grants applications. He has been collaborating with internal and external academic and industrial partners and actively developing research proposals as a PI and Co-PI for internal and external funding calls including Horizon 2020, Wellcome Trust and High-Volume Transport. He also serves as a reviewer for many flagship journals and conferences in robotics, control and artificial intelligence including IEEE ICRA, IEEE IROS, IEEE SSRR, IEEE/ASME Transactions on Mechatronics, IEEE Robotics and Automation Letters (RA-L) etc. Robotics, Control systems, Mobile robot, Capsule robot, Capsule endoscopy, Artificial intelligence, Deep learning, Sensor fusion, Robotic (Self-driving) cars, Search and rescue robot, Pipe inspection robot. Dr M Nazmul Huda has more than five years of teaching experience in the UK (Brunel University London, Coventry University, Bournemouth University and Staffordshire University) and in Bangladesh.
Mackay
dr mackay is a mechanical engineer with a particular interest within the biomedical field. she gained her undergraduate degree from the university of dundee in 2007 in mechnical engineering. this was followed by a her phd micro-electromechanical-systems in 2011, also at the university of dundee, funded by a case grant from the epsrc with idb technologies. she moved to brunel in 2011 to work as a research fellow on a tanslational mrc grant developing point of care devices. she became a lecturer at brunel in 2015. her research focuses on organ-on-a-chip tecnologies for women's health, low cost point of care diagnostic devices and prosthetics. she teaches within the areas of finite element analysis and medical device engineering. dr mackay's primary research focus is within the field of organ-on-a-chip (ooc). within the group she researches the development of microfluidic devices, manufacturing methods, cell scaffold facbrication and electronic control of the systems. the ooc group at brunel university london (www.bruneldoclab.com) incorporates toxicologists, engineers, life scientists and bioinformaticians. the group’s research focuses on developing alternative systems to study women’s health issues, such as cancers, pregnancy outcomes and sexually transmitted infections. we are currently working on systems that replicate female organs (vagina, ovaries, placenta and breast) to better understand initiation, progression diagnosis and treatment of women’s diseases and disorders. her other research interests include low cost, point of care diagnostics, prosthetics and soft robotics organ on a chip low cost diagnostics microfluidics prosthetics soft robotics me3622 mechanical engineering structures me3626 vehicle structures and fea me5678 medical device engineering me5692 group project (meng)
Dr Ruth Mackay
Dr Mackay is a Mechanical Engineer with a particular interest within the biomedical field. She gained her undergraduate degree from the University of Dundee in 2007 in Mechnical Engineering. This was followed by a her PhD Micro-electromechanical-systems in 2011, also at the University of Dundee, funded by a CASE grant from the EPSRC with IDB Technologies. She moved to Brunel in 2011 to work as a Research Fellow on a tanslational MRC grant developing point of care devices. She became a lecturer at Brunel in 2015. Her research focuses on organ-on-a-chip tecnologies for women's health, low cost point of care diagnostic devices and prosthetics. She teaches within the areas of Finite Element Analysis and Medical Device Engineering. Dr Mackay's primary research focus is within the field of Organ-on-a-Chip (OOC). Within the group she researches the development of microfluidic devices, manufacturing methods, cell scaffold facbrication and electronic control of the systems. The OOC group at Brunel University London (www.bruneldoclab.com) incorporates toxicologists, engineers, life scientists and bioinformaticians. The group’s research focuses on developing alternative systems to study women’s health issues, such as cancers, pregnancy outcomes and sexually transmitted infections. We are currently working on systems that replicate female organs (vagina, ovaries, placenta and breast) to better understand initiation, progression diagnosis and treatment of women’s diseases and disorders. Her other research interests include low cost, point of care diagnostics, prosthetics and soft robotics Organ on a Chip Low cost diagnostics Microfluidics Prosthetics Soft Robotics ME3622 Mechanical Engineering Structures ME3626 Vehicle Structures and FEA ME5678 Medical Device Engineering ME5692 Group Project (MEng)
Manivannan
dr. manivannan serves as a senior lecturer at brunel school of design, specializing in electronics, computer languages, and embedded systems. he earned his doctorate degree (dphil) from the university of oxford in optical pattern recognition in 1997 and a first-class bachelor's degree (beng hons) in electrical and electronic engineering from city university london in 1994. his professional journey includes roles at esteemed organizations such as motorola, symbian ltd, and open trade technologies ltd, primarily focusing on computer modelling and software development for scientific applications. transitioning to academia in 2009, he joined the university as a researcher. throughout his tenure, dr. manivannan has displayed exceptional leadership as a module leader and tutor for various electronics, mathematics, and computing modules, guiding undergraduate students in their academic endeavors. he has effectively supervised numerous phd and msc student dissertations, fostering their scholarly growth. his research interests encompass diverse areas within electronics, with notable expertise in sensors for wearable applications, non-thermal plasma applications, and electronic systems applications like blind reading and biometrics. he has been a prolific contributor to academic discourse, authoring over eighty papers in reputable journals and conferences, including invited articles and book chapters. dr. manivannan's contributions extend beyond scholarly pursuits. he has secured substantial funding for research projects, including a pioneering role in an innovate uk r&d project valued at £1.2 million. he has also facilitated collaborative initiatives such as the spark program, fostering international knowledge exchange and organizing joint conferences and workshops. as a respected member of the academic community, dr. manivannan has chaired sessions in international conferences, delivered keynote addresses, and received numerous accolades, including multiple best paper awards. he actively engages in professional associations, holding senior memberships in ieee and fellowship status in the higher education academy (hea). he is also affiliated with esteemed organizations such as the institute of physics (iop), electrostatics society of america (esa), and oxford engineering society. his commitment to advancing the field is evident through his roles in professional organizations, including serving as the treasurer and chair of the iop dielectrics and electrostatics (d&e) group and the program chair the international conferences "electrostatics 2019" and the chair of the "electrostatics 2023." dr. manivannan's expertise is further recognized through his role as a reviewer for prestigious journals and as a panel member for the ieee senior member admission and advancement committee, evaluating research proposals for epsrc. dr. manivannan's profound impact on academia and research underscores his dedication to pushing the boundaries of knowledge in the field of electronics and beyond. major research plasma and microwave technologies in emission control: have been working on two funded projects (deecon, fp7 eu and mags, innovateuk) those involve emission control of marine diesel engine. the technologies used are non-thermal plasma using microwave irradiation and electron beam, microwave dielectric heating, activated carbon based adsorption and microwave regeneration. optical pattern recognition: the work on optical pattern recognition explores 4f optical correlator for challenging optical information processing tasks. this work is in collaboration with the photonics group at imperial college, london. fingerprint biometrics: a range of fingerprint biometrics areas of research are explored; liveness detection of fingerprint, cancelable fingerprint template generation, multi-model biometric fusion techniques, fingerprint in m-health successful research/travel grant income pi of an eu innovation voucher - touch devices for blind reading (may 2018 to may 2019) pi of epsrc research base exhaust funding (£10k){(jan 2017 – march 2017} a two year ( feb 2014 – jan 2015) research funding from innovateuk as a co-investigator researcher; title: marine flue gas plasma treatment system (mags) project funding: £1.2 million (total), £0.36 million (brunel) travel grants to attend and present at national and international conferences. royal academy of engineering for attending 8th ieee international symposium intelligent systems and informatics in serbia in sept 2010 registration waiver for spie, orlando 2011 conference brunel research school for attending vitae conference in edinburgh in nov 2012 eu project deecon project funded to four international conferences 2011-2014 innovateuk funding (mags) to attend one international conference 2016 brunal visa awad to attend dust conference in italy in 2016 emission control using non-thermal plasmabiometrics - fingerprint recognitionsensors for wearabel applications such as sports and healthcareelectronic system engineering such blind reading and optical system for pattern recognition smart cities - human cnetered approachsocial media and ai applications present at design department, brunel dm1601 electronics and mathematics – module leader, tutor and examiner dm1601 creative engineering practice – tutor and examiner dm2305 electronics, interface and programming – module leader,tutor and examiner past analogue and digital electronics (university of oxford and demontfort university) opto-electronics (university of oxford) communications principles (demontfort university) engineering mathematics (demontfort university)
Dr Nadarajah Manivannan
Senior Lecturer
Dr. Manivannan serves as a Senior Lecturer at Brunel School of Design, specializing in Electronics, Computer Languages, and Embedded Systems. He earned his Doctorate degree (DPhil) from the University of Oxford in Optical Pattern Recognition in 1997 and a First-Class Bachelor's degree (BEng Hons) in Electrical and Electronic Engineering from City University London in 1994. His professional journey includes roles at esteemed organizations such as Motorola, Symbian Ltd, and Open Trade Technologies Ltd, primarily focusing on Computer Modelling and Software Development for scientific applications. Transitioning to academia in 2009, he joined the university as a researcher. Throughout his tenure, Dr. Manivannan has displayed exceptional leadership as a module leader and tutor for various Electronics, Mathematics, and Computing modules, guiding undergraduate students in their academic endeavors. He has effectively supervised numerous PhD and MSc student dissertations, fostering their scholarly growth. His research interests encompass diverse areas within electronics, with notable expertise in Sensors for wearable applications, Non-thermal plasma applications, and electronic systems applications like Blind Reading and Biometrics. He has been a prolific contributor to academic discourse, authoring over eighty papers in reputable journals and conferences, including invited articles and book chapters. Dr. Manivannan's contributions extend beyond scholarly pursuits. He has secured substantial funding for research projects, including a pioneering role in an Innovate UK R&D project valued at £1.2 million. He has also facilitated collaborative initiatives such as the SPARK program, fostering international knowledge exchange and organizing joint conferences and workshops. As a respected member of the academic community, Dr. Manivannan has chaired sessions in international conferences, delivered keynote addresses, and received numerous accolades, including multiple best paper awards. He actively engages in professional associations, holding senior memberships in IEEE and fellowship status in the Higher Education Academy (HEA). He is also affiliated with esteemed organizations such as the Institute of Physics (IoP), Electrostatics Society of America (ESA), and Oxford Engineering Society. His commitment to advancing the field is evident through his roles in professional organizations, including serving as the Treasurer and Chair of the IOP Dielectrics and Electrostatics (D&E) Group and the program chair the international conferences "Electrostatics 2019" and the chair of the "Electrostatics 2023." Dr. Manivannan's expertise is further recognized through his role as a reviewer for prestigious journals and as a panel member for the IEEE Senior Member Admission and Advancement Committee, evaluating research proposals for EPSRC. Dr. Manivannan's profound impact on academia and research underscores his dedication to pushing the boundaries of knowledge in the field of electronics and beyond. Major Research Plasma and microwave technologies in emission control: Have been working on two funded projects (DEECON, FP7 EU and MAGS, InnovateUK) those involve emission control of marine diesel engine. The technologies used are non-thermal plasma using microwave irradiation and electron beam, microwave dielectric heating, activated carbon based adsorption and microwave regeneration. Optical pattern recognition: The work on optical pattern recognition explores 4f optical correlator for challenging optical information processing tasks. This work is in collaboration with the photonics group at Imperial College, London. Fingerprint biometrics: A range of fingerprint biometrics areas of research are explored; liveness detection of fingerprint, cancelable fingerprint template generation, multi-model biometric fusion techniques, fingerprint in M-health Successful Research/Travel Grant Income PI of an EU Innovation voucher - Touch devices for Blind reading (May 2018 to May 2019) PI of EPSRC research base exhaust funding (£10k){(Jan 2017 – March 2017} A two year ( Feb 2014 – Jan 2015) research funding from InnovateUK as a co-investigator researcher; Title: Marine Flue Gas Plasma Treatment System (MAGS) Project funding: £1.2 million (total), £0.36 million (Brunel) Travel grants to attend and present at national and international conferences. Royal Academy of Engineering for attending 8th IEEE international symposium intelligent systems and informatics in Serbia in Sept 2010 Registration waiver for SPIE, Orlando 2011 conference Brunel Research School for attending VITAE conference in Edinburgh in Nov 2012 EU project DEECON project funded to four international conferences 2011-2014 InnovateUK funding (MAGS) to attend one international conference 2016 Brunal VISA awad to attend DUST conference in Italy in 2016 Emission Control using Non-thermal plasmaBiometrics - Fingerprint recognitionSensors for wearabel applications such as sports and healthcareElectronic System Engineering such blind reading and optical system for pattern recognition Smart cities - Human cnetered approachSocial Media and AI applications Present at Design Department, Brunel DM1601 Electronics and Mathematics – Module leader, Tutor and Examiner DM1601 Creative Engineering Practice – Tutor and Examiner DM2305 Electronics, Interface and Programming – Module leader,Tutor and Examiner Past Analogue and Digital Electronics (University of Oxford and DeMontfort University) Opto-electronics (University of Oxford) Communications Principles (DeMontfort University) Engineering Mathematics (DeMontfort University)