Sherif Haggag

Dr Sherif Haggag

Assistant Professor / Lecturer

School of Computer Science

Faculty of Sciences, Engineering and Technology

Eligible to supervise Masters and PhD (as Co-Supervisor) - email supervisor to discuss availability.


Dr Haggag is an Assistant Professor in Information Technology. His research areas of interest include:

  • Human-centred software engineering, understanding Human-centred issues and designing apps with Adaptive User Interfaces.
  • Digital health and engineering smart software systems.
  • Domain-specific Visual Languages and Model-driven Engineering.
  • Digital Enhanced Living and Smart home technologies.
  • Agile methods (Scrum, SAFe, Kanban, Lean, large-scale agile).
  • Working with Sensor and depth cameras to improve Human ergonomics.
  • BCI applications.
  • Socio-technical aspects of Cybersecurity.

Software engineering is designed to solve human problems and support human in different aspects such as Health, Education, Transport, Manufacturing, etc. However, current Software Engineering techniques do not pay attention to different humans/end users who use the same system. Dr Sherif current Human-centred research focuses on:

  • Human aspects which is based on personality, gender, culture backgrounds, emotion reaction, age, motivation and hidden biases.
  • Social aspects which is the base for collaboration, team work, leadership and management.

Taking in consideration those aspects in all stages of the Software Development Lifecycle will help both developers and end users to have better applications. 

Dr Sherif has limited capacity for supervising PhD and master students, feel free to contact him to discuss more details. He enjoys thinking out of the box and that is based on team brainstorming. Here are few projects that he is currently working on along with his students.

  • Journals

    Year Citation
    2017 Mohamed, S., Haggag, S., Nahavandi, S., & Haggag, O. (2017). Towards automated quality assessment measure for EEG signals. Neurocomputing, 237, 281-290.
    DOI
    2015 Nguyen, T., Bhatti, A., Khosravi, A., Haggag, S., Creighton, D., & Nahavandi, S. (2015). Automatic spike sorting by unsupervised clustering with diffusion maps and silhouettes. Neurocomputing, 153, 199-210.
  • Conference Papers

    Year Citation
    2022 Haggag, S. (2022). Better Addressing Diverse Accessibility Issues in Emerging Apps: A Case Study using COVID-19 Apps. In 9th IEEE/ACM International Conference on Mobile Software Engineering and Systems 2022 (MobileSoft 2022), May 2022, Pittsburg, USA. IEEE/ACM.
    2021 Haggag, O., Haggag, S., Grundy, J., & Abdelrazek, M. (2021). COVID-19 vs social media apps: does privacy really matter?. In 2021 IEEE/ACM 43rd International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS) (pp. 48-57). online: IEEE.
    DOI
    2015 Haggag, S., Mohamed, S., Bhatti, A., Haggag, H., & Nahavandi, S. (2015). Noise level classification for EEG using Hidden Markov Models. In 2015 10th System of Systems Engineering Conference (SoSE) (pp. 439-444). IEEE.
    2015 Haggag, S., Mohamed, S., Haggag, H., & Nahavandi, S. (2015). Prosthetic motor imaginary task classification using single channel of electroencephalography. In 2015 IEEE International Conference on Systems, Man, and Cybernetics (pp. 969-973). IEEE.
    2015 Haggag, H., Hossny, M., Nahavandi, S., Haggag, S., & Creighton, D. (2015). Body parts segmentation with attached props using rgb-d imaging. In 2015 International Conference on Digital Image Computing: Techniques and Applications (DICTA) (pp. 1-8). IEEE.
    2015 Haggag, S., Mohamed, S., Haggag, O., & Nahavandi, S. (2015). Prosthetic Motor Imaginary Task Classification Based on EEG Quality Assessment Features. In International Conference on Neural Information Processing (pp. 87-94). Springer.
    2014 Haggag, H., Hossny, M., Haggag, S., Nahavandi, S., & Creighton, D. (2014). Safety applications using kinect technology. In 2014 IEEE International Conference on Systems, Man, and Cybernetics (SMC) (pp. 2164-2169). IEEE.
    2014 Haggag, S., Mohamed, S., Bhatti, A., Haggag, H., & Nahavandi, S. (2014). Neural spike representation using cepstrum. In 2014 9th International Conference on System of Systems Engineering (SOSE) (pp. 97-100). IEEE.
    2014 Haggag, H., Hossny, M., Haggag, S., Nahavandi, S., & Creighton, D. (2014). Efficacy comparison of clustering systems for limb detection. In 2014 9th International Conference on System of Systems Engineering (SOSE) (pp. 148-153). IEEE.
    2014 Haggag, H., Hossny, M., Haggag, S., Xiao, J., Nahavandi, S., & Creighton, D. (2014). LGT/VOT tracking performance evaluation of depth images. In 2014 9th International Conference on System of Systems Engineering (SOSE) (pp. 284-288). IEEE.
    2014 Haggag, S., Mohamed, S., Bhatti, A., Haggag, H., & Nahavandi, S. (2014). Neuron’s spikes noise level classification using hidden markov models. In International Conference on Neural Information Processing (pp. 501-508). Springer.
    2014 Haggag, S., Mohamed, S., Haggag, H., & Nahavandi, S. (2014). Hidden markov model neurons classification based on mel-frequency cepstral coefficients. In 2014 9th International Conference on System of Systems Engineering (SOSE) (pp. 166-170). IEEE.
    2013 Haggag, S., Mohamed, S., Bhatti, A., Gu, N., Zhou, H., & Nahavandi, S. (2013). Cepstrum based unsupervised spike classification. In 2013 IEEE International Conference on Systems, Man, and Cybernetics (pp. 3716-3720). IEEE.
    2013 Zhou, H., Mohamed, S., Bhatti, A., Lim, C. P., Gu, N., Haggag, S., & Nahavandi, S. (2013). Spike sorting using hidden markov models. In International Conference on Neural Information Processing (pp. 553-560). Springer.

Dr Haggag has extensive experience in teaching, course coordinating and creating new courses/units in Information technology and Computer Science courses such as:

  • Fundamentals of Information Technology.
  • Introduction to Programming.
  • Introduction to Web Development.
  • Fundamental Concepts of Mathematics.
  • Object Oriented Programming.
  • Algorithms and Data Structures.
  • Databases.
  • Data Statistics and Analysis.
  • Data Structures and Algorithms.
  • IT Placements and Industry Experience.
  • Cyber Security.
  • Secure Programming.
  • Research Methods. 
  • Other Supervision Activities

    Date Role Research Topic Location Program Supervision Type Student Load Student Name
    2022 - ongoing Principal Supervisor ORCiD SIGNUP APPLICATION The University of Adelaide Master Full Time Arjun Sivarajan Pushpakaran
    2019 - ongoing Co-Supervisor Secure message transmission in vehicular adhoc network The University of Adelaide Doctor of Philosophy Doctorate Full Time Orvila Sarker
  • Position: Assistant Professor / Lecturer
  • Phone: 83135505
  • Email: sherif.haggag@adelaide.edu.au
  • Campus: North Terrace
  • Building: Ingkarni Wardli, floor Level Five
  • Room: 5.34
  • Org Unit: School of Computer Science

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