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]()
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
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 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. 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 a 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 Hongying Meng
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 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. 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 a 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)
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 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, a mechanical engineer, has a keen interest in the biomedical field. she earned her undergraduate degree in mechanical engineering from the university of dundee in 2007. following that, she pursued her phd in micro-electromechanical systems in 2011, also at the university of dundee, with funding from a case grant provided by the epsrc in collaboration with idb technologies. in 2011, she joined brunel as a research fellow, contributing to a translational mrc grant focused on developing point-of-care devices. subsequently, in 2015, she assumed the role of a lecturer at brunel. her research centers around organ-on-a-chip technologies, low-cost point-of-care diagnostic devices, and prosthetics. she currently leads the organ on a chip group at brunel. additionally, she lectures in the fields of finite element analysis and medical device engineering. dr. mackay directs her research efforts towards organ-on-a-chip (ooc) technology. within her research group, she delves into the intricate development of microfluidic devices, explores innovative manufacturing methods, cell scaffold facbrication and electronic control of the systems. at brunel university london, the ooc group thrives as a multidisciplinary team, uniting toxicologists, engineers, life scientists, and bioinformaticians. their collective mission revolves around pioneering alternative systems for investigating critical women’s health issues, including cancers, pregnancy outcomes, and sexually transmitted infections. currently, their focus lies in creating systems that faithfully replicate female organs—vagina, ovaries, placenta, and breast—to unravel the complexities of initiation, progression, diagnosis, and treatment of women’s diseases and disorders. beyond her ooc pursuits, dr. mackay’s research interests extend to low-cost, point-of-care diagnostics, prosthetics, and the fascinating world of 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 Ruth Mackay
Dr. Mackay, a Mechanical Engineer, has a keen interest in the biomedical field. She earned her undergraduate degree in Mechanical Engineering from the University of Dundee in 2007. Following that, she pursued her PhD in Micro-electromechanical Systems in 2011, also at the University of Dundee, with funding from a CASE grant provided by the EPSRC in collaboration with IDB Technologies. In 2011, she joined Brunel as a Research Fellow, contributing to a translational MRC grant focused on developing point-of-care devices. Subsequently, in 2015, she assumed the role of a Lecturer at Brunel. Her research centers around organ-on-a-chip technologies, low-cost point-of-care diagnostic devices, and prosthetics. She currently leads the Organ on a Chip Group at Brunel. Additionally, she lectures in the fields of Finite Element Analysis and Medical Device Engineering. Dr. Mackay directs her research efforts towards Organ-on-a-Chip (OOC) technology. Within her research group, she delves into the intricate development of microfluidic devices, explores innovative manufacturing methods, cell scaffold facbrication and electronic control of the systems. At Brunel University London, the OOC group thrives as a multidisciplinary team, uniting toxicologists, engineers, life scientists, and bioinformaticians. Their collective mission revolves around pioneering alternative systems for investigating critical women’s health issues, including cancers, pregnancy outcomes, and sexually transmitted infections. Currently, their focus lies in creating systems that faithfully replicate female organs—vagina, ovaries, placenta, and breast—to unravel the complexities of initiation, progression, diagnosis, and treatment of women’s diseases and disorders. Beyond her OOC pursuits, Dr. Mackay’s research interests extend to low-cost, point-of-care diagnostics, prosthetics, and the fascinating world of 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 ci of an innovation volucher with carbon capture ( april 2024 to dec 2024) ci of an industrial project with pyrocore (£0.27 m), emission control project (september 2019 to august 2021) pi of an eu innovation voucher - touch devices for blind reading (may 2018 to may 2019) pi of teachbrunel project, learning electronics with the use of matlab (may 2017 to may 2018) pi of epsrc research base exhaust funding (jan 2017 – march 2017) ci(r) of a two year ( feb 2014 – jan 2015) research funding from innovateuk (£1.2m), marine flue gas plasma treatment system (mags) 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]()
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 CI of an Innovation volucher with Carbon Capture ( April 2024 to Dec 2024) CI of an Industrial Project with Pyrocore (£0.27 m), Emission Control project (September 2019 to August 2021) PI of an EU Innovation voucher - Touch devices for Blind reading (May 2018 to May 2019) PI of TeachBrunel Project, Learning Electronics with the use of MATLAB (May 2017 to May 2018) PI of EPSRC research base exhaust funding (Jan 2017 – March 2017) CI(R) of a two year ( Feb 2014 – Jan 2015) research funding from InnovateUK (£1.2m), Marine Flue Gas Plasma Treatment System (MAGS) 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)