Imperial College London


Faculty of EngineeringDepartment of Computing

Research Postgraduate



e.maali19 Website




ACE ExtensionSouth Kensington Campus





I am a third-year Ph.D. candidate at the Adaptive Emergent Systems Engineering Laboratory (AESE) at the Department of Computing. I am working under the supervision of Professor Julie McCann. My Ph.D. is funded by Schlumberger Foundation, Faculty for the Future Ph.D. Fellowship.. My Ph.D. focus is IoT Security, in which I am developing  an anomaly detector for IoT networks.

In 2017, I completed my MSc in Electromagnetic Sensor Networks at the University of Birmingham.  My Master degree was funded by Hani Qaddumi Foundation. The focus of the master was on electromagnetic, antennas, propagation, computer communications networks, and RF and microwave engineering. Moreover, I completed my BA in Computer Systems Engineering from Birzeit University in Palestine.



Eman Maali, David Boyle, and Hamed Haddadi. 2020. "Towards identifying IoT traffic anomalies on the home gateway: poster abstract". In Proceedings of the 18th Conference on Embedded Networked Sensor Systems (SenSys '20). Association for Computing Machinery, New York, NY, USA, 735–736. (PDF)


Mr. Aziz Qaroush, Dr. Mahdi Washaha, Miss Eman Maali, Mr. Ibrahim Abu Farah. “An Efficient Extractive Single document Arabic Text Summarization using a Combination of Statistical and Semantic Features with Novel Representation”. Submitted to Journal of King Saud University(Published)


Mr. Aziz Qaroush, Mr. Bassam Jaber, Dr. Khader Awwad, Dr. Mahdi Washah, Miss Eman Maali, Dr.Nibal Nayef. “An Efficient, Font Independent Word and Character Segmentation Algorithm for Printed Arabic Text”, submitted to Arabian Journal for Science and Engineering (Under Review).