Overview

***I am accepting self-funded/sponsored PhD students. If you are interested to work with me, please email me your CV.

I'm a senior lecturer in computer science (machine learning and computer vision) and a fellow of the British Higher Education Academy (HEA).

Before joining Exeter University, I was a senior lecturer in data and information science at Birmingham City University, where I was the leading member of the computer vision research team. I also worked for the School of Computer Science at Nottingham University, Mechanochemical Cell Biology at Warwick University, Nottingham Molecular Pathology Node (NMPN), and Division of Cancer and Stem Cells both at Nottingham Medical School, as a Research Fellow.

I was awarded a PhD in Computer Science and Engineering (with a Doctor’s Europaeus degree) from Scuola IMT Alti Studi Lucca, in Italy.

Throughout my career, I've had the privilege of collaborating with diverse teams of experts in fields ranging from biology and geology to entomology, pathology, engineering, and computer science. These enriching experiences have taken me to various corners of the world, including Egypt, Singapore, Italy, and the United Kingdom.

My current research interests are concerned with the development of novel artificial intelligence (statistical machine learning and deep learning) solutions, with the overall ambition to assist human investigation in healthcare and data science applications. More precisely, I’m most interested in carrying out research on different theoretical foundations in computer vision and machine learning such as:

• Deep learning and statistical machine learning.
• Explainable AI for healthcare.
• Energy functional optimisation for computer vision tasks.
• Machine teaching and active learning.
• Uncertainty quantification.
• Self-supervision and transfer learning.
• Static and dynamic deep ensemble.
• Multimodal learning.

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Publications

_{Copyright Notice: Any articles made available for download are for personal use only. Any other use requires prior permission of the author and the copyright holder.}

| 2023 | 2022 | 2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2008 |

2023

• Almehdhar M, Abdelsamea MM, Ruan N. (2023) Deep multi-locality convolutional neural network for DDoS detection in smart home IoT, International Journal of Information and Computer Security, volume 22, no. 3-4, pages 453-474, DOI:10.1504/IJICS.2023.135902.
• Kearney P, Abdelsamea M, Schmoor X, Shah F, Vickers I. (2023) Combating Alert Fatigue in the Security Operations Centre, DOI:10.2139/ssrn.4633965.
• Ayantayo A, Kaur A, Kour A, Schmoor X, Shah F, Vickers I, Kearney P, Abdelsamea MM. (2023) Network intrusion detection using feature fusion with deep learning, Journal of Big Data, volume 10, no. 1, article no. 167, DOI:10.1186/s40537-023-00834-0. [PDF]
• Almehdhar M, Na R, Abdelsamea MM. (2023) Deep multi-locality convolutional neural network for DDoS detection in smart home IoT, International Journal of Information and Computer Security, volume 1, no. 1, pages 1-1, DOI:10.1504/ijics.2023.10052345. [PDF]
• Zidan U, Desouky HAE, Gaber MM, Abdelsamea MM. (2023) From Pixels to Deposits: Porphyry Mineralization With Multispectral Convolutional Neural Networks, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, volume 16, pages 9259-9271, DOI:10.1109/jstars.2023.3321714. [PDF]
• Buczek P, Zidan U, Gaber MM, Abdelsamea MM. (2023) Idecomp: imbalance-aware decomposition for class-decomposed classification using conditional GANs, Discover Artificial Intelligence, volume 3, no. 1, article no. 31, DOI:10.1007/s44163-023-00078-0. [PDF]
• Al-Turki D, Kyriakou M, Basurra S, Gaber MM, Abdelsamea MM. (2023) The power of progressive active learning in floorplan images for energy assessment, Sci Rep, volume 13, no. 1, DOI:10.1038/s41598-023-42276-x. [PDF]
• Senousy Z, Gaber MM, Abdelsamea MM. (2023) AUQantO: Actionable Uncertainty Quantification Optimization in deep learning architectures for medical image classification, APPLIED SOFT COMPUTING, volume 146, article no. ARTN 110666, DOI:10.1016/j.asoc.2023.110666. [PDF]
• Abdelsamea MM, Gaber MM, Ali A, Kyriakou M, Fawki S. (2023) A logarithmically amortising temperature effect for supervised learning of wheat solar disinfestation of rice weevil Sitophilus oryzae (Coleoptera: Curculionidae) using plastic bags, Sci Rep, volume 13, no. 1, DOI:10.1038/s41598-023-29594-w. [PDF]
• Zidan U, Gaber MM, Abdelsamea MM. (2023) SwinCup: Cascaded swin transformer for histopathological structures segmentation in colorectal cancer, EXPERT SYSTEMS WITH APPLICATIONS, volume 216, article no. ARTN 119452, DOI:10.1016/j.eswa.2022.119452. [PDF]

2022

• Senousy Z, Abdelsamea MM, Gaber MM, Abdar M, Acharya UR, Khosravi A, Nahavandi S. (2022) MCUa: Multi-Level Context and Uncertainty Aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification, IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, volume 69, no. 2, pages 818-829, DOI:10.1109/TBME.2021.3107446. [PDF]
• Abdelsamea MM, Zidan U, Senousy Z, Gaber MM, Rakha E, Ilyas M. (2022) A survey on artificial intelligence in histopathology image analysis, WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, volume 12, no. 6, article no. ARTN e1474, DOI:10.1002/widm.1474. [PDF]
• Abbas A, Gaber MM, Abdelsamea MM. (2022) XDecompo: Explainable Decomposition Approach in Convolutional Neural Networks for Tumour Image Classification, SENSORS, volume 22, no. 24, article no. ARTN 9875, DOI:10.3390/s22249875. [PDF]

2021

• Mugova NP, Abdelsamea MM, Gaber MM. (2021) On the effect of decomposition granularity on DeTraC for COVID-19 detection using chest X-ray images, Proceedings - European Council for Modelling and Simulation, ECMS, volume 35, no. 1, pages 29-34.
• Rakha A, Hettiarachchi H, Rady D, Gaber MM, Rakha E, Abdelsamea MM. (2021) Predicting the economic impact of the COVID-19 pandemic in the United Kingdom using time-series mining, Economies, volume 9, no. 4, DOI:10.3390/economies9040137.
• Abbas A, Abdelsamea MM, Gaber MM. (2021) Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network, APPLIED INTELLIGENCE, volume 51, no. 2, pages 854-864, DOI:10.1007/s10489-020-01829-7. [PDF]
• Senousy Z, Abdelsamea MM, Mohamed MM, Gaber MM. (2021) 3E-Net: Entropy-Based Elastic Ensemble of Deep Convolutional Neural Networks for Grading of Invasive Breast Carcinoma Histopathological Microscopic Images, ENTROPY, volume 23, no. 5, article no. ARTN 620, DOI:10.3390/e23050620. [PDF]
• Abbas A, Abdelsamea MM, Gaber MM. (2021) 4S-DT: Self-Supervised Super Sample Decomposition for Transfer Learning With Application to COVID-19 Detection, IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, volume 32, no. 7, pages 2798-2808, DOI:10.1109/TNNLS.2021.3082015. [PDF]
• Senousy Z, Abdelsamea MM, Gaber MM, Abdar M, Acharya UR, Khosravi A, Nahavandi S. (2021) MCUa: Multi-level Context and Uncertainty aware Dynamic Deep Ensemble for Breast Cancer Histology Image Classification, IEEE Transactions on Biomedical Engineering 2021. [PDF]

2020

• Ibrahim A, Gamble P, Jaroensri R, Abdelsamea MM, Mermel CH, Chen P-HC, Rakha EA. (2020) Artificial intelligence in digital breast pathology: Techniques and applications, BREAST, volume 49, pages 267-273, DOI:10.1016/j.breast.2019.12.007. [PDF]
• Abbas A, Abdelsamea MOHAMMEDM, Gaber MM. (2020) DeTrac: Transfer Learning of Class Decomposed Medical Images in Convolutional Neural Networks, IEEE ACCESS, volume 8, pages 74901-74913, DOI:10.1109/ACCESS.2020.2989273. [PDF]
• Abbas A, Abdelsamea MM, Gaber MM. (2020) Classification of COVID-19 in chest X-ray images using DeTraC deep convolutional neural network. [PDF]
• Abbas A, Abdelsamea MM, Gaber M. (2020) 4S-DT: Self Supervised Super Sample Decomposition for Transfer learning with application to COVID-19 detection. [PDF]

2019

• Abdelsamea MM, Mohamed MH, Bamatraf M. (2019) Automated Classification of Malignant and Benign Breast Cancer Lesions Using Neural Networks on Digitized Mammograms, Cancer Informatics, volume 18, DOI:10.1177/1176935119857570.
• Abdelsamea MM, Pitiot A, Grineviciute RB, Besusparis J, Laurinavicius A, Ilyas M. (2019) A cascade-learning approach for automated segmentation of tumour epithelium in colorectal cancer, EXPERT SYSTEMS WITH APPLICATIONS, volume 118, pages 539-552, DOI:10.1016/j.eswa.2018.10.030. [PDF]
• Abdelsamea MM, Grineviciute RB, Besusparis J, Cham S, Pitiot A, Laurinavicius A, Ilyas M. (2019) Tumour parcellation and quantification (TuPaQ): a tool for refining biomarker analysis through rapid and automated segmentation of tumour epithelium, HISTOPATHOLOGY, volume 74, no. 7, pages 1045-1054, DOI:10.1111/his.13838. [PDF]
• Sagheer A, Zidan M, Abdelsamea MM. (2019) A Novel Autonomous Perceptron Model for Pattern Classification Applications, ENTROPY, volume 21, no. 8, article no. ARTN 763, DOI:10.3390/e21080763. [PDF]

2018

• Abdelsamea MM, Cham S, Pitiot A, Grineviciute RB, Besusparis J, Laurinavicius A, Ilyas M. (2018) TuPaQ: Tumour Parcellation and Quantification, JOURNAL OF PATHOLOGY, volume 246, pages S45-S45. [PDF]
• Abdelsamea MM, Pitiot A, Grineviciute RB, Besusparis J, Laurinavicius A, Ilyas M. (2018) A Novel Machine-Learning Approach for Segmentation of Tumour Epithelium in Colorectal Cancer, JOURNAL OF PATHOLOGY, volume 246, pages S45-S45. [PDF]
• Abbas A, Abdelsamea MM. (2018) Learning Transformations for Automated Classification of Manifestation of Tuberculosis using Convolutional Neural Network, PROCEEDINGS OF 2018 13TH INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND SYSTEMS (ICCES), pages 122-126. [PDF]

2017

• Abdelsamea MM, Gnecco G, Gaber MM. (2017) A SOM-based Chan-Vese model for unsupervised image segmentation, SOFT COMPUTING, volume 21, no. 8, pages 2047-2067, DOI:10.1007/s00500-015-1906-z. [PDF]

2016

• Abdelsamea MM. (2016) A semi-automated system based on level sets and invariant spatial interrelation shape features for Caenorhabditis elegans phenotypes, JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION, volume 41, pages 314-323, DOI:10.1016/j.jvcir.2016.10.011. [PDF]

2015

• Abdelsamea MM, Gnecco G, Gaher MM. (2015) An efficient Self-Organizing Active Contour model for image segmentation, NEUROCOMPUTING, volume 149, pages 820-835, DOI:10.1016/j.neucom.2014.07.052. [PDF]
• Abdelsamea MM, Gnecco G. (2015) Robust local-global SOM-based ACM, ELECTRONICS LETTERS, volume 51, no. 2, pages 142-143, DOI:10.1049/el.2014.3691. [PDF]
• Abdelsamea MM, Gnecco G, Gaber MM, Elyan E. (2015) On the Relationship between Variational Level Set-Based and SOM-Based Active Contours, COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, volume 2015, article no. ARTN 109029, DOI:10.1155/2015/109029. [PDF]
• Abdelsamea M, Mohamed MH, Bamatraf M. (2015) An Effective Image Feature Classiffication using an improved SOM. [PDF]
• Abdelsamea M. (2015) Regional Active Contours based on Variational level sets and Machine Learning for Image Segmentation. [PDF]

2014

• Minervini M, Abdelsamea MM, Tsaftaris SA. (2014) Image-based plant phenotyping with incremental learning and active contours, ECOLOGICAL INFORMATICS, volume 23, pages 35-48, DOI:10.1016/j.ecoinf.2013.07.004. [PDF]
• Abdelsamea MM, Gnecco G, Gaber MM. (2014) A Survey of SOM-Based Active Contour Models for Image Segmentation, ADVANCES IN SELF-ORGANIZING MAPS AND LEARNING VECTOR QUANTIZATION, volume 295, pages 293-302, DOI:10.1007/978-3-319-07695-9_28. [PDF]
• Abdelsamea MM, Gnecco G, Gaber MM. (2014) A Concurrent SOM-Based Chan-Vese Model for Image Segmentation, ADVANCES IN SELF-ORGANIZING MAPS AND LEARNING VECTOR QUANTIZATION, volume 295, pages 199-208, DOI:10.1007/978-3-319-07695-9_19. [PDF]
• Mohamed MH, Abdelsamea MM. (2014) Self Organization Map based Texture Feature Extraction for Efficient Medical Image Categorization. [PDF]
• Abdelsamea MM. (2014) An Automatic Seeded Region Growing for 2D Biomedical Image Segmentation. [PDF]
• Abdelsamea MM. (2014) Unsupervised Parallel Extraction based Texture for Efficient Image Representation, 2011 International Conference on Signal, Image Processing and Applications With workshop of ICEEA 2011, IPCSIT vol.21 (2011), IACSIT Press, Singapore. [PDF]
• Abdelsamea MM. (2014) An Enhancement Neighborhood connected Segmentation for 2D-Cellular Image. [PDF]

2013

• Abdelsamea MM, Tsaftaris SA. (2013) Active Contour Model driven by Globally Signed Region Pressure Force, 2013 18TH INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP). [PDF]

2008

• Mohamed MH, AbdeISamea MM. (2008) An efficient clustering based texture feature extraction for medical image, Proceedings of International Workshop on Data Mining and Artificial Intelligence (DMAI' 08), pages 88-93, DOI:10.1109/ICCITECHN.2008.4803114.

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