Dr. Mohamed Hisham Jaward

School of Engineering

+603 5514 6204
Room 2-4-14

Personal statement

Mohamed Jaward received the PhD degree in Automatic Control and Systems Engineering from the University of Sheffield, UK in 2002. He was a Research Assistant at the Departments of Electrical and Electronic Engineering, University of Bristol and Imperial College London, UK, before he joined Monash University. His research interests include computer vision including deep learning approaches, sequential Monte Carlo methods, target tracking in video sequences, fault detection and data detection in communication systems. At Monash, he has completed completed the supervision of two HDR students and also attracted two external grants from MOHE, Malaysia.

Academic degrees

  • Doctor of Philosophy in Automatic Control and Systems Engineering, The University of Sheffield UK, 2003
  • Degree in Electronic and Telecommunications Engineering, University of Moratuwa, Sri Lanka, 1995

Research Interests

  • Computer vision problems related to Medical Informatics. Especially, health care monitoring problems such as facial expression tecognition, activity recognition, object detection, tracking and object classification and other related signal processing problems.
  • Deep networks for facial recognition, bio-medical image segmentation and eye tracking
  • Sequential Monte Carlo methods (Particle filters) and other Bayesian methods.
  • Equalization (worked on DFE, Maximum likelihood sequence estimator, MAP and other equalisers), error correction coding and MIMO communication problems.
  • System Identification, Estimation Theory and Digital Signal Processing.
  • Fault detection.

Research Projects

Title: Deep learning based post-invariant facial expression recognition system

With the continuous improvement in living environment and healthcare, the population, in general, has a longer life-span compared to a few decades ago. As a result of this, nursing homes around the world start to face a growing labour shortage. One of the solutions to this problem is the video based technology for ambient assisted living. Similar techniques are also could be useful for monitoring a condition of a bed-ridden patient. This work proposes computer vision techniques (known as facial expression recognition) to assess the facial expression of a person which could indicate whether the person is in pain or the condition of the person’s mood. Developed techniques could also be used to infer the intention of a person and to estimate the intensity of any expression.

Facial expression recognition is a task of classifying facial feature deformation and facial motion into discrete classes based on visual information. This has been an active research for more than a decade but most of the work assumed just one frontal camera is available and the person is very cooperative and facing the camera. In real-life situations, spontaneous facial behaviour often involves head-pose variations. Hence, head-pose variations has become one of the main challenges in facial expression recognition. Since only a few work have analysed multi-view and view-invariant facial expression recognition, these problems have gained our attention. Therefore, our study attempts to develop novel algorithms for multi-view and view-invariant recognition of facial expressions from multiple views. It is hoped that developed algorithms could lead to a system which could automatically infer the expression of a non-cooperative person.

Title: Deep learning based demodulation of LMR signals

The 2-Way Land Mobile Radios (LMR) are still the preferred choice for public safety communications due to its robustness, ease of use and cost of deployment. However, the ubiquity of wireless products has resulted in RF interference becoming a real challenge to maintain signal integrity over long distances. To increase sensitivity, the amplification gain has to be increased. However, increasing gain causes blocking issues.

Nevertheless, the rapid rise of machine learning technologies has evolved, exceeding human abilities in being able to identify patterns in the midst of seemingly chaotic data. In recent years, researchers have begun looking at using machine learning to increase the sensitivity of RF communications. Preliminary findings suggest as much as 10 dB improvements in required SNR using convolutional neural networks.

To achieve these objectives, this project would first validate the reported performance of recent work applied to demodulation based on deep learning. Then, a novel deep learning architecture, which would take into consideration correlation between adjacent samples, would be developed. The outcome of this project is expected to significantly reshape the LMR ecosystem in developing and deploying efficient 2-way next gen radio products.


Units taught

ECE2191 - Probability Models in Engineering

ECE3141 - Information and Networks


Ebrahimkhani, Somayeh; Jaward, Mohamed Hisham; Cicuttini, Flavia M.; Dharmaratne, Anuja; Wang, Yuanyuan; de Herrera, Alba G.Seco; , 2020, A review on segmentation of knee articular cartilage: from conventional methods towards deep learning, Artificial Intelligence in Medicine, Volume: 106, Issue Number: 09333657, 10.1016/j.artmed.2020.101851

Khanam, Shapla; Ahmedy, Ismail Bin; Idna Idris, Mohd Yamani; Jaward, Mohamed Hisham; Bin Md Sabri, Aznul Qalid; , 2020, A Survey of Security Challenges, Attacks Taxonomy and Advanced Countermeasures in the Internet of Things, IEEE Access, (219709-219743), Volume: 8, 10.1109/ACCESS.2020.3037359

Cheok, Ming Jin; Omar, Zaid; Jaward, Mohamed Hisham; , 2019, A review of hand gesture and sign language recognition techniques, International Journal of Machine Learning and Cybernetics, (131-153), Volume: 10, Issue Number: 18688071, 10.1007/s13042-017-0705-5

Kamarol, Siti Khairuni Amalina; Jaward, Mohamed Hisham; Kälviäinen, Heikki; Parkkinen, Jussi; Parthiban, Rajendran; , 2017, Joint facial expression recognition and intensity estimation based on weighted votes of image sequences, Pattern Recognition Letters, (25-32), Volume: 92, Issue Number: 01678655, 10.1016/j.patrec.2017.04.003

Kamarol, Siti Khairuni Amalina; Jaward, Mohamed Hisham; Parkkinen, Jussi; Parthiban, Rajendran; , 2016, Spatiotemporal feature extraction for facial expression recognition, IET Image Processing, (534-541), Volume: 10, Issue Number: 17519659, 10.1049/iet-ipr.2015.0519

Petrou, Maria; Jaward, Mohamed H.; Chen, Shengyong; Briers, Mark; , 2012, Super-resolution in practice: The complete pipeline from image capture to super-resolved subimage creation using a novel frame selection method, Machine Vision and Applications, (441-459), Volume: 23, Issue Number: 09328092, 10.1007/s00138-010-0315-7

Jaward, M. H.; Bull, D.; Canagarajah, N.; , 2010, Sequential Monte Carlo methods for contour tracking of contaminant clouds, Signal Processing, (249-260), Volume: 90, Issue Number: 01651684, 10.1016/j.sigpro.2009.06.022

Kadirkamanathan, V.; Li, P.; Jaward, M. H.; Fabri, S. G.; , 2002, Particle filtering-based fault detection in non-linear stochastic systems, International Journal of Systems Science, (259-265), Volume: 33, Issue Number: 00207721, 10.1080/00207720110102566

Jaward, M. H.; Kadirkamanathan, V.; , 2001, Interacting multiple models for single-user channel estimation and equalization, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, (2101-2104), Volume: 4, Issue Number: 15206149, 10.1109/ICASSP.2001.940407

Kadirkamanathan, V.; Li, P.; Jaward, M. H.; Fabri, S. G.; , 2000, A sequential Monte Carlo filtering approach to fault detection and isolation in nonlinear systems, Proceedings of the IEEE Conference on Decision and Control, (4341-4346), Volume: 5, Issue Number: 01912216, 10.1109/CDC.2001.914586

Kadirkamanathan, V.; Jaward, M. H.; Fabri, S. G.; Kadirkamanathan, M.; , 2000, Particle filters for recursive model selection in linear and nonlinear system identification, Proceedings of the IEEE Conference on Decision and Control, (2391-2396), Volume: 3, Issue Number: 01912216, 10.1109/CDC.2000.914157


Tang, Tiong Yew; Alhashmi, Saadat M.; Hisham Jaward, Mohamed; , 2012, Hamming Selection Pruned Sets (HSPS) for efficient multi-label video classification, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), (589-600), Volume: 7458 LNAI, Issue Number: 03029743, 10.1007/978-3-642-32695-0_52


Jin, Cheok Ming; Omar, Zaid; Jaward, Mohamed Hisham; , 2016, A mobile application of American sign language translation via image processing algorithms, Proceedings - 2016 IEEE Region 10 Symposium, TENSYMP 2016, (104-109), 10.1109/TENCONSpring.2016.7519386

Lung, Fam Boon; Jaward, Mohamed Hisham; Parkkinen, Jussi; , 2015, Spatio-temporal descriptor for abnormal human activity detection, Proceedings of the 14th IAPR International Conference on Machine Vision Applications, MVA 2015, (471-474), 10.1109/MVA.2015.7153233

Kamarol, Siti Khairuni Amalina; Meli, Nor Syazana; Jaward, Mohamed Hisham; Kamrani, Nader; , 2015, Spatio-temporal texture-based feature extraction for spontaneous facial expression recognition, Proceedings of the 14th IAPR International Conference on Machine Vision Applications, MVA 2015, (467-470), 10.1109/MVA.2015.7153112

Chua, Jia Luen; Chang, Yoong Choon; Jaward, Mohamed Hisham; Parkkinen, Jussi; Wong, Kok Sheik; , 2014, Vision-based hand grasping posture recognition in drinking activity, 2014 International Symposium on Intelligent Signal Processing and Communication Systems, ISPACS 2014, (185-190), 10.1109/ISPACS.2014.7024449

Yanto, Gradi; Jaward, Mohamed Hisham; Kamrani, Nader; , 2013, Bayesian Chan-Vese segmentation for iris segmentation, IEEE VCIP 2013 - 2013 IEEE International Conference on Visual Communications and Image Processing, 10.1109/VCIP.2013.6706440

Nah, J. H.Y.; Parthiban, R.; Jaward, M. H.; , 2013, Visible light communications localization using TDOA-based coherent heterodyne detection, 4th International Conference on Photonics, ICP 2013 - Conference Proceeding, (247-249), 10.1109/ICP.2013.6687128

Weerasekera, C. S.; Jaward, M. H.; Kamrani, N.; , 2013, Robust ASL fingerspelling recognition using local binary patterns and geometric features, 2013 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2013, 10.1109/DICTA.2013.6691521

Jaward, M. H.; Bull, D.; Canagarajah, N.; , 2008, Contour tracking of contaminant clouds with Sequential Monte Carlo methods, ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, (1469-1472), Issue Number: 15206149, 10.1109/ICASSP.2008.4517898

Jaward, M. H.; Mihaylova, L.; Canagarajah, N.; Bull, D.; , 2006, A data association algorithm for multiple object tracking in video sequences, IET Seminar Digest, (135-142), Volume: 2006, 10.1049/ic:20060565

Jaward, M.; Mihaylova, L.; Canagarajah, N.; Bull, D.; , 2006, Multiple object tracking using particle filters, IEEE Aerospace Conference Proceedings, Volume: 2006, Issue Number: 1095323X, https://www.scopus.com/record/display.uri?eid=2-s2.0-34047183832&origin=resultslist

Jaward, M. H.; Bull, D.; Canagarajah, N.; , 2006, Distributed tracking with sequential Monte Carlo methods for manoeuvrable sensors, NSSPW - Nonlinear Statistical Signal Processing Workshop 2006, (113-116), 10.1109/NSSPW.2006.4378832

Jaward, Mohamed H.; Kadirkamanathan, Visakan; , 2002, Interacting multiple model for adaptive narrowband interference rejection in spread spectrum systems, IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, (1227-1231), Volume: 3, 10.1109/PIMRC.2002.1045224

Jaward, M. H.; Kadirkamanathan, V.; , 2002, Adaptive multiuser detection for frequency selective channel using IMM, IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC, (1275-1279), Volume: 3, 10.1109/PIMRC.2002.1045234

Local grants

  • Facial Expression Recognition in Image Sequences, Mohamed Hisham Jaward  (CI), Jussi Parkinnen, 2013-2016, Exploratory Research Grant Scheme (ERGS) of Malaysian Ministry of Higher Education (MOHE), RM72,000
  • Human activity recognition using Multiple Models, Mohamed Hisham Jaward(CI), Maria Petrou(Imperial College London), Jussi Parkinnen, 2012-2015, Fundamental Research Grant Scheme (FRGS), Ministry of Education, Malaysia, RM52,700

Current supervision

Joshua Nah Han Yew

Optimizing Visible Light Illumination and Positioning

2013 - now

School of Engineering, Monash University Malaysia

Somayeh Ebrahimkhani

Knee cartilage segmentation based on deep learning

2016 - now

School of IT, Monash University Malaysia

Completed supervision

Siti Khairuni Amalina Binti Kamarol

Feature Extraction and Representation Techniques for Facial Expression Analysis

2013 - 2017

School of Engineering, Monash Univeristy Malaysia

Fam Boon Lung

Human activity recognition using weighted multi-camera features

2014 - 2015

School of Engineering, Monash Univeristy Malaysia

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