Mohammad Abu Alsheikh

One PhD scholarship is available in machine learning and IoT for domestic students (Australian permanent residents or citizens). If you have strong programming skills and previous experience in machine learning or computer networks, please send me your resume at mabualsh[at]ieee[dot]org

Mohammad Abu Alsheikh 

Assistant Professor
University of Canberra, University Dr, Bruce, ACT, Australia 2617
I acknowledge the Ngunnawal people who are the traditional custodians of the land where I live and work

I'm an assistant professor at the Faculty of Science & Technology. I design and create novel IoT systems that leverage both machine learning and convex optimization with applications in people-centric sensing, human activity recognition, and smart cities.

Previously, I was a postdoctoral researcher at Massachusetts Institute of Technology, USA. My doctoral research at Nanyang Technological University, Singapore was focused on optimizing the data collection in wireless sensor networks. After graduating with a B.Eng. degree in computer systems from Birzeit University, Palestine, I worked as a software engineer at a digital advertising startup and Cisco.

Recent News

Selected Publications *

The following three papers provide a good overview of my research:

  • M. Abu Alsheikh, D. Niyato, D. Leong, P. Wang, and Z. Han, “Privacy management and optimal pricing in people-centric sensing,” in IEEE Journal on Selected Areas in Communications (impact factor 8.09), 2017 (IEEE Xplore | arXiv)

  • M. Abu Alsheikh, D. Niyato, S. Lin, H. P. Tan, and D. I. Kim, “Fast adaptation of activity sensing policies in mobile devices,” in IEEE Transactions on Vehicular Technology (impact factor 4.07), 2017 (IEEE Xplore | arXiv)

  • M. Abu Alsheikh, D. Niyato, S. Lin, H. P. Tan, and Z. Han, “Mobile big data analytics using deep learning and Apache Spark,” in IEEE Network (impact factor 7.23), 2016 (IEEE Xplore | arXiv)

The full list can be found on Google Scholar.

Teaching

Professional Activities

I regularly review (mainly machine learning-related papers) for a number of international journals including IEEE Journal on Selected Areas in Communications, IEEE Transactions on Wireless Communications, IEEE Transactions on Communications, IEEE Transactions on Vehicular Technology, IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Mobile Computing, IEEE Network Magazine, IEEE Wireless Communications Magazine, and Elsevier Computer Networks.