Shamaila Iram image

Dr Shamaila Iram

Research Fellow


Shamaila Iram works as a “Research Fellow” in the School of the Built Environment at University of Salford. She has received her PhD in “Computer Science” from Liverpool John Moores University in 2014. During her PhD, she got an opportunity to work in the SIGMA Laboratory at ESPCI ParisTech, France, for few months.

There, she worked on the early detection of Alzheimer’s using EEG signals. Previously, in 2010, she obtained her MSc degree in “Computing and Information Systems” from Liverpool John Moores University, with distinction.

Research Interests:

Dr Iram’s main area of research is Machine Learning, Artificial Intelligence, Big Data Analysis, and Data Mining. Dr Iram’s research has been published in various international journals and conferences.

Research Projects (current and previous):

  • ProSEco(A European Project for collaborative design of product-services, using Ambient Intelligence (AmI) technology, lean and eco-design principles and applying Life Cycle Assessment techniques, allowing for effective extensions of products of manufacturers in different sectors)
  • Early Detection of Neurodegenerative Diseases from Bio-Signals: A Machine Learning Approach
  • Early Detection of Term and Pre Term Births using EHG signals
  • An Integrated web-based e-Assessment system

Qualifications and Memberships:

Ph.D . (Computer Science) MSc (Computing and Information Systems) BSc (Hons) (Computer Science)


Book Chapters:

Dhiya Al-Jumeily, Shamaila Iram, Abir Jaffar Hussain, Vialatte Francois-Benois, Paul Fergus,"Early Detection Method of Alzheimer’s Disease Using EEG Signals," in Intelligent Computing in Bioinformatics. vol. 8590, D.-S. Huang, K. Han, and M. Gromiha, Eds., ed: Springer International Publishing, 2014, pp. 25-33.

Shamaila Iram, Francois Vialatte, Muhammed Irfan Qamar, "Early Detection of Neurodegenerative Diseases from Gait Discrimination to Neural Synchronization" accepted for publication in "Applied Computing in Health and Medicine", Elsevier, 2015

Journal Papers:

Shamaila Iram, Paul Fergus, Dhiya Al-Jumeily, Abir Hussain, Martin Randles, "A Classifier Fusion Strategy to Improve the Early Detection of Neurodegenerative Diseases", the International Journal of Artificial Intelligence and Soft Computing, 2013

Dhiya Al-Jumeily, Shamaila Iram, Francois-Benois Vialatte, Paul Fergus and Abir Hussain, "A Novel Method of Early Diagnosis of Alzheimer's Disease Based on EEG Signals", The Scientific World Journal, Article ID 931387

Fergus P, Cheung P, Hussain A, Al-Jumeily D, Dobbins C, Iram S. (2013) "Prediction of Preterm Deliveries from EHG Signals Using Machine Learning". PLoS ONE 8(10): e77154

Paul Fergus, Shamaila Iram, Dhiya Al-Jumeily, Martin Randles, Andrew Attwood, "Home-based Health Monitoring and Measurement for Personalised Healthcare", Journal of Medical Imaging and Health Informatics (JMIHI), vol. 2(1), pp. 35-43, March 2012.

William Hurst, Madjid Merabti, Shamaila Iram, Paul Fergus, "Protecting Critical Infrastructures Through Behavioural Observation", the International Journal of Critical Infrastructures, Vol.10(2), pp. 174-192, 2014.

Conference Papers:

Shamaila Iram, Dhiya Al-Jumeily, Abir Hussain, Paul Fergus and David Lamb, "On the Early Detection of Neurodegenerative Disease from Gait and EEG Signals: A Machine Learning Approach", BCS International IT Conference, Abu Dhabi, UAE, 2013.

Shamaila Iram, Dhiya Al-Jumeily, Paul Fergus, Martin Randles, Abir Hussain, "Computational Data Analysis for Movement Signals Based on Statistical Pattern Recognition Techniques for Neurodegenerative Diseases", The 13th Annual Postgraduate Symposium on the Convergence of Telecommunications, Networking and Broadcasting, 25th - 26th June 2012, Liverpool, UK.

Shamaila Iram, Dhiya Al-Jumeily, Paul Fergus, Martin Randles, "E-Health: The Potential of Linked Data and Stream Reasoning for Personalised Healthcare", in Developments in E-Systems Engineering (DeSE), IEEE Society Dubai, 6th - 8th December 2011.

Shamaila Iram, D. Al-Jumeily and J. Lunn, "An Integrated Web-Based e-Assessment Tool" in Developments in "-systems Engineering (DeSE), IEEE Society, 2011, pp. 271-275.

Dhiya Al-Jumeily, Shamaila Iram, Francois Valatte Paul Fergus, "A Novel Method to Analyze EEG Synchrony for the Early Diagnosis of Alzheimer's Disease in Optimized Frequency Bands", accepted for publication in CCNC 2014 - Consumer eHealth Platforms Services and Applications-America - CeHPSA 2014.

Shamaila Iram, Dhiya Al-Jumeily, Paul Fergus, Abir Hussain, "Exploring the Hidden Challenges Associated with the Evaluation of Multi-class Datasets using Multiple Classifiers", International Conference on Complex, Intelligent and Software Intensive Systems (CISIS), IEEE, 2014.