1. 1
Md. Khaled Abu Mahmoud
PhD. Engjneering J.P.
+61 412 977 019
mdkhaledabu@gmail.com
Career Objective
To be assigned as an engineer / researcher with a company / university involved in Electrical, Electronic Control
Systems, Biomedical Engineering, Intelligent Information and Image Processing System, where my skills in strategic
thinking, high-level negotiation, solving complex problems, appraising both new project feasibility and design, and
training and technical knowledge/ experience, can be applied and add value to the company so I can contribute
towards its business growth.
Skills Summary
· Research
· Engineering
· Electronics
· Image Processing
· Simulations
· Machine Learning
· Team Leadership
· Management
· Project Management
· Testing
· Customer Service
· Public Speaking
· Machine Vision
· Artificial Intelligence
· AutoCAD
· MATLAB
· Microsoft Office
· PowerPoint
Subject to Teach
· Electrical Engineering - Principals and Applications
· Electronics and Circuits
· Introduction to Telecommunications
· Image Processing

2. 2
Professional Memberships
Date Description
2013 IEEE Membership number (92147881)
1991 Electrical Contractor (Licence No. 11061C)
1987 The Institution of Engineers Australia / Electrical College
(MIE Aust. 66428)
Education
Date Description Organisation
2010 2015 PhD in Electrical and Computer Engineering / Health
Technology
New Methods in Improving Skin Cancer (Melanoma)
Detection
University of Technology Sydney
1997 1998 Master Information Technology Charles Stuart University
1997 1998 Graduate Diploma in Vocational Education and Training Charles Stuart University
1964 1969 B.Sc. Engineering, Electrical (Telecommunication and
Electronics)
Minoufiya University, Egypt
Professional Training
Date Description Organisation
2011 MATLAB Introductory and Programming Techniques University of Technology Sydney
2004 Certificate III English for Employment Learning Lab - Sydney
2004 Certificate IV in Assessment and Workplace Training Learning Lab - Sydney
1994 Small Business Management Course Lithgow TAFE
1993 Computer Money Management
AutoCAD
Programmable controller (PLC)
Building Business Management
Contracting management
Miller TAFE
1991 Electrical Wiring Refresher Course: Design and
Installation
North Sydney TAFE
1991 Computer Software Programming Design Campbelltown TAFE
1990 Caltex Petroleum Products franchise Small Business CALTEX, Australia
1990 Digital Cellular / RF Communication Tester (HP8920A) Hewlett Pckard
1984 Process Control Instrumentation YEW, JAPAN
1982 Serck SCADA Systems H/W & Conversational S/W Serck Controls, UK
1982 Engineers Introduction to PDP11-34A Minicomputer
Utilities & Commands (RSX11M)
PDP-11 Systems Diagnostic Software
Disk and Printer Maintenance
DEC, UK
1982 Effective Supervision Program MERC, SA GREECE
1979 Telecommunications & Transmission Telemetry
Systems
NEC, JAPAN
1979 Material Standardization & Coding (MESC) SHELL, HOLLAND

3. 3
Research Expertise
PhD thesis: I am an electrical electronic engineer doing research in image processing. My thesis covers a complete
theoretical model for simulating the processes that takes place when a human interprets an image generated by the
eye, through designing a reliable system that can provide a screening method that filters lesions and melanoma in
a general practice. The proposed system is to be used with a standard PC with input from a high quality digital
camera, dermoscopy / microscopy slides of pathology images or any other suitable hardware sources.
This system analyses the structure of a mole / skin defects, detects cancer, identifies features, makes a decision and
provides the result. The result of the proposed system shows that the Skin Cancer (Melanoma) Detection strategy
which uses the Swarm-based SVM (SSVM) performs better than the SVM and the SVM based wavelet Gabor (SVM-
WLG) with average for accuracy, sensitivity, and specificity of 87.13%, 94.1% and 80.22%, respectively.
Further future methods and applications relating to melanoma detection will present a wider view of future goals
which will assist in designing a reliable screening system that can determine a lesion area and increase both object-
and image-level classification performances. This will make the diagnosis process faster and easier; early detection
and further assistance improves survival rate and will improve reporting quality for physicians, general practitioners,
pathologists and specialists.
Research Interests
My research interests include (but are not limited to: Image Processing, Automata Theory, Analysis of Design and
algorithm, Multiscale Transforms (Wavelet, Ridgelet, Curvelet), Support Vector Machines (SVM) network, Neural
Networks, and fuzzy inference system (FIS), particle Swarm Optimization (SSVM), Ant Colony Optimization (ACO),
called PSO-ACO, Ontology, Contourlet Transform, Mathematical tools of Soft Computing and others in multifunction
pattern recognition systems.
Industry Expertise
I am a highly experienced Professional telecommunications and electronics engineer. I have been working in the
engineering industry for over 30 years. During these years, I worked on several different engineering applications
and managerial levels, including Consultant Engineer, Telemetry instrument Engineer, lecturing and tutoring, Design
Electronic Engineer, Instrument Systems Engineer, Senior Data / SCADA and Telemetry Engineer, Recording Section
Head on Seismic Exploration Party, Maintenance and Planning Engineer, engineering manager of broadcasting and
television transmission stations and Senior Business Manager.

4. 4
Journal Paper Publications
Abu Mahmoud, M.K., Al-Jumaily, A. & Takruri, M. 2013 Wavelet and Curvelet Analysis for Automatic Identification
of Melanoma Based on Neural Network Classification , (2013) in the International Journal of Computer Information
Systems and Industrial Management (IJCISIM), Volume 5 2013 pp. 606-614
Conference Paper Publications
1. Abu Mahmoud, M.K. & Al-Jumaily, A. 2014, A Hybrid System for Skin Lesion Detection: Based on Gabor Wavelet
and Support Vector Machine The model is submitted to (CISP_BMEI 2014): 7th International Congress on Image
and Signal Processing, 7th International Conference on Biomedical Engineering and Informatics, Dalian, China 14-
16 October 2014.
2. Takruri, M. Al-Jumaily, A., Abu Mahmoud, M.K.2014, Automatic Recognition of Melanoma Using Support Vector
Machines: A Study Based on Wavelet, Curvelet and Colour Features . The model is presented in (IAICT 2014):
International Conference on Industrial Automation, Information and Communications Technology, Bali,
Indonesia, Aug 28-30, 2014.
3. Abu Mahmoud, M.K. & Al-Jumaily, A. 2014, Novel feature extraction methodology based on histopathalogical
images and subsequent classification by Support Vector Machine . The model is presented by Md Khaled et al.
(2014), in (ICCVIA2014) International Conference on Computer Vision & Image Analysis, Ras Al Khaimah, UAE 25-
27 March 2014.
4. Abu Mahmoud, M.K. & Al-Jumaily, A. & Maali, Y. & Anam, K. 2013, Classification of Malignant Melanoma and
Benign Nevi from Skin Lesions Based on Support Vector Machine The model is presented by Md Khaled et al.
(2013), in Fifth International Conference on Computational Intelligence, Modelling and Simulation, Seoul, South
Korea, 24-26 September.
5. Abu Mahmoud, M.K. & Al-Jumaily, A. 2011, The Automatic Identification of Melanoma by Wavelet and Curvelet
Analysis: Study Based on Neural Network Classification . This model is presented by Md Khaled et al. (2011), in
11th International Conference on Hybrid Intelligent Systems (HIS), December 5-8, Malacca, Malaysia.
6. Abu Mahmoud, M.K. & Al-Jumaily, A. 2011, Segmentation of skin cancer images based on gradient vector flow
(GVF) Snake . The model is presented by Md Khaled et al. (2011), International Conference on Mechatronics and
Automation, August 7 - 10, Beijing, China.
Hobbies and Interests:
Reading particularly in advanced technology, Arabic literature, walking, sports, handyman, enjoys painting and arts.
References
1. Dr. Adel Al-Jumaily, Associate Professor UTS
P: +61-2 9514 7939
E: adel.al-jumaily@uts.edu.au
2. Dr. Ahmed Al-Ani, Senior Lecturer UTS
P: +61-2 9514 2420
E: Ahmed.Al-Ani@uts.edu.au
3. Dr. Maen Takruri, Associate Professor AURAK UAE
P: +971-7-2210 900 / 1252
E: maen.takruri@aurak.ac.ae
4. Dr. Mohammed Assem, Medical Specialist
P: +61 2 9707 2724
E: dassem1@gmail.com