Hisham Jaward

Lecturer in Computing and AI

+44 (0)1473 338297
School of Technology, Business and Arts
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Hisham is a lecturer in Computing and AI and joined the University of Suffolk after working at University of Monash for twelve years. Before he joined Monash, he worked as a researcher at the University of Bristol and Imperial College, UK. His first work at University of Bristol involved developing algorithms for removing interference in military communication systems and was funded by QinetiQ. Subsequent projects at UOB involved developing algorithms for multiple target tracking in video sequences and tracking airborne contaminants using Sequential Monte Carlo techniques. At Imperial College London, he worked on a project on image super-resolution and was funded by BAE Systems (UK) and QinetiQ.

Hisham has extensive experience in course management, design and validation and delivery at undergraduate and postgraduate level. At Monash, he has taught 10 modules related to computer science and electronic engineering. These include modules on deep learning, probability theory, communication theory and networking etc.

Hisham is an active researcher in the area of computer vision and machine learning as evidenced by Google scholar (https://scholar.google.com/citations?hl=en&user=ZAGtTjMAAAAJ&view_op=list_works&sortby=pubdate) with a 5 year h-index of 10 and 750 citations in the past five years.

Listed below are some of his recent publications:

S. Ebrahimkhani, A. Dharmaratne , M.H. Jaward, , Yuanyuan Wang, Flavia M. Cicuttini, “Automated Segmentation of Knee Articular Cartilage: Joint Deep and Hand-Crafted Learning-Based Framework using Diffeomorphic Mapping,” Neurocomputing, Vol. 467, Pages 36-55, 2022.

Shapla Khanam, Ismail Bin Ahmedy, Mohd Yamani Idna Idris, M.H. Jaward, Aznul Qalid Bin Md Sabri,“ Towards an Effective Intrusion Detection Model using Focal Loss Variational Autoencoder for Internet of Things (IoT)”, Sensors, 2022.

Ifham Abdul Latheef Ahmed, M.H. Jaward, “Classifier aided training for semantic segmentation,” Journal of Visual Communication and Image Representation, Vol. 78, 2021.

Guo Hao Thng, Masuduzzaman Bakaul, M.H. Jaward “Differential encoding for unlock heterodyning millimeter-wave RoF link,” Optics Communications, Vol. 498, 2021.

S. Ebrahimkhani, M.H. Jaward, Yuanyuan Wang, Alba Garcia, A. Dharmaratne, Flavia M. Cicuttini, “A review on segmentation of knee articular cartilage: from conventional methods towards deep learning,” Artificial Intelligence in Medicine, Vol. 106, 2020.

Shapla Khanam, Ismail Bin Ahmedy, Mohd Yamani Idna Idris, M.H. Jaward, Aznul Qalid Bin Md Sabri,“A survey of security challenges, attacks taxonomy and advanced countermeasures in the internet of things”, IEEE Access, Vol. 8, Pages 219709-219743, 2020.

He has successfully completed the supervision of four research students. One of the recent completion is on applying deep learning techniques for downlink coordinated multipoint in mm-wave communication systems. Another was on deep learning-based cartilage segmentation and this work collaborated with Prof. Flavia Cicuttini of Alfred Hospital, Melbourne. He is currently supervising two research students. First one sponsored by Motorola Solutions explores the use of machine learning to mitigate interference and other impairments in a two-way radio system. The second one investigates the development of flow models for image and video compression.