Conference and Workshop Papers
K. Okoye, U. Naeem, S. Islam, M.A. Azam, A. Karami and M.S. Sharif, “The Application of a Semantic-Based Process Mining Framework on a Learning Process Domain,” in SAI Intelligent Systems (IntelliSys) Conference, London, 2018 (Accepted)
M.S. Sharif, U. Naeem, S. Islam and A. Karami, “Functional Connectivity Evaluation for Infant EEG Signals Based on Artificial Neural Network,” in SAI Intelligent Systems (IntelliSys) Conference, London, 2018 (Accepted)
R. G. Hussain, M. A. Azam, M. A. Ghazanfar, U. Naeem and C. Meurisch, “Smartphone based Robust Hierarchical Framework for Activity Recognition based on Machine Learning,” in Future Technologies Conference, Vancouver, 2017.
S. Islam, U. Naeem, M.S. Sharif and A. Dovnarovic, “CrimeSafe - Helping you stay safe,” in ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2017), 2nd workshop on intelligent personal support of human behaviour - SmartGuidance'17, Maui, 2017, pp.642-645.
I.K. Ihianle, U. Naeem and S. Islam, “Ontology-Driven Activity Recognition from Patterns of Object Use,” in ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2017), 2nd workshop on intelligent personal support of human behaviour - SmartGuidance'17, Maui, 2017, pp.654-657.
S. Islam, M.S. Sharif, U. Naeem and J. Geehan, “SignalSense: towards quality service,” in ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2017), 2nd workshop on intelligent personal support of human behaviour - SmartGuidance'17, Maui, 2017, pp.627-630.
U. Naeem, S. Islam, M.S. Sharif, S. Sudakov and M.A. Azam, “Taskification: gamification of tasks,” in ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2017), 2nd workshop on intelligent personal support of human behaviour - SmartGuidance'17, Maui, 2017, pp.631-634.
M.S.L. Khan, S.U. Réhman, Y. Mi, U. Naeem, J. Beskow and H. Li, “Moveable Facial Features in a Social Mediator,” in International Conference on Intelligent Virtual Agents, Stockholm, 2017, pp.205-208.
S. Pizzamiglio, U. Naeem, S.U. Réhman, M.S. Sharif, H. Abdalla and D.L. Turner, “A Multimodal Approach to Measure the Distraction Levels of Pedestrians using Mobile Sensing,” in 8th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, Lund, 2017, pp. 89-96.
M. Ehatisham-ul-Haq, M.A. Azam, U. Naeem, S.U. Rѐhman and A. Khalid, “Identifying Smartphone Users based on their Activity Patterns via Mobile Sensing,” in 8th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, Lund, 2017, pp.202-209.
K. Okoye, A.H. Tawil, U. Naeem, S. Islam and E.Lamine, “Semantic-based Model Analysis towards Enhancing Information Values of Process Mining: Case Study of Learning Process Domain,” in International Conference on Soft Computing and Pattern Recognition, India, 2016, pp.622-633.
K. Okoye, A.H. Tawil, U. Naeem, S. Islam and E.Lamine, “Using semantic-based approach to manage perspectives of process mining: Application on improving learning process domain data,” in IEEE International Conference on Big Data, Washington, 2016, pp.3529-3538.
U. Naeem, A.R. Tawil, I. Semelis, M.A. Azam and M.A Ghazanfar, “Inference Engine based on a Hierarchical Structure for Detecting Everyday Activities within the Home,” in SAI Intelligent Systems (IntelliSys) Conference, London, 2016, pp.969-986.
I.K. Ihianle, U. Naeem and A.R. Tawil, “Recognition of Activities of Daily Living from Topic Model,” in 7th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, London, 2016.pp.24-31.
I.K. Ihianle, U. Naeem, A.R. Tawil and M.A. Azam, “Recognizing activities of daily living from patterns and extraction of web knowledge,” in ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016), 1st International Workshop on Smarticipation: intelligent personal guidance of human behavior utilizing anticipatory models, Heidelberg, 2016, pp.1255-1262.
I.K. Ihianle, U. Naeem, and A.H. Tawil. "A dynamic segmentation based activity discovery through topic modelling," in IET International Conference on Technologies for Active and Assisted Living (TechAAL), London, 2015, pp.1-6.
S. Nasreen, M.A. Azam, U. Naeem and M.A Ghazanfar, “Inference of activities with unexpected actions using pattern mining,” in ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2015), 3rd International Workshop on Human Activity Sensing Corpus and its Application, Japan, 2015, pp.1479-1488.
K. Okoye, A.H. Tawil, U. Naeem and E.Lamine, "Semantic Process Mining Towards Discovery and Enhancement of Learning Model Analysis," in 17th IEEE International Conference on High Performance Computing and Communications, New York, 2015, pp.363-370.
U. Naeem, A.H. Tawil, I. Semelis, G. Judah and R. Aunger, “Inference of Hygiene Behaviours While Recognising Activities of Daily Living,” in 3rd International Conference on Context-Aware Systems and Applications, 4th International Workshop on Pervasive and Context-Aware Middleware, Dubai, 2014, pp.154-161.
K. Okoye, A.H. Tawil, U. Naeem, R. Bashroush and E.Lamine, “A Semantic Rule-Based Approach Towards Process Mining for Personalised Adaptive Learning,” in 16th IEEE International Conference on High Performance Computing and Communications, 1st International Workshop on Algorithmic and Modeling, Paris, 2014, pp.929-936.
K. Okoye, A.H. Tawil, U. Naeem, R. Bashroush, E. Lamine, “A Semantic Rule-Based Approach Supported by Process Mining for Personalised Adaptive Learning,” in 5th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, Canada, 2014, pp.203-210.
S. Nasreen, M.A. Azam, K. Shehzad, U. Naeem and M.A. Ghazanfar, “Frequent Pattern Mining Algorithms for Finding Associated Frequent Patterns for Data Streams: A Survey,” in 5th International Conference on Emerging Ubiquitous Systems and Pervasive Networks, Canada, 2014, pp.109-116.
S.W. Lee, U. Naeem, R. Anthony, A.H. Tawil, M.A. Azam and D. Preston, “Tracking Functional Decline Using Ambient Intelligence for Alzheimer’s Patients,” in 19th International Conference on Transformative Research in Science and Engineering, Business and Social Innovation, Malaysia, 2014, pp.1-9.
N. Sarantinos, A. Al-Nemrat and U. Naeem, “Statistical Sampling Approach to Investigate Child Pornography Cases,” in 4th Cybercrime and Trustworthy Computing Workshop, Sydney, 2013, pp.22-29.
T. B. Lau, D.M.L. Wong, U. Naeem and S.W. Lee, “An Indoor Prototype Framework for Recognition of Activities of Daily Life,” in 7th Conference on Rehabilitation Engineering and Assistive Technology Society of Korea, Korea, 2013, pp.94-97.
M.A. Azam, J. Loo, U. Naeem, S. K. A. Khan, A. Lasebae and O. Gemikonakli, “A Framework to Recognise Daily Life Activities with Wireless Proximity and Object Usage Data,” in 23rd IEEE International Symposium on Personal, Indoor and Mobile Radio Communication, Sydney, 2012, pp.590-595.
U. Naeem, A.H. Tawil, R. Bashroush and A. Al-Nemrat, “Achieving Model Completeness for Hierarchally Structured Activities of Daily Life,” in 2nd International Conference on Pervasive and Embedded Computing and Communication Systems, Rome, 2012.
U. Naeem and J. Bigham, “Recognising Activities of Daily Life through the Usage of Everyday Objects around the Home,” in 3rd International Conference on Pervasive Computing Technologies for Healthcare, Technologies to Counter Cognitive Decline Workshop, London, 2009, pp.1-4.
U. Naeem and J. Bigham, “A Hierarchal Approach to Activity Recognition in the Home Environment based on Object Usage,” in Networking and Electronic Commerce Research Conference (NAEC 2008), Italy, 2008, pp.48-54.
U. Naeem and J. Bigham, “Activity Recognition using a Hierarchical Framework,” in 2nd International Conference on Pervasive Computing Technologies for Healthcare, Ambient Technologies for Diagnosing and Monitoring Chronic Patients Workshop, Finland, 2008, pp.24-27.
U. Naeem, J. Bigham and J. Wang, “Recognising Activities of Daily Life Using Hierarchical Plans,” in 2nd European Conference on Smart Sensing and Context, UK, 2007, pp.175-189.
U. Naeem and J. Bigham, "A Comparison of Two Hidden Markov Approaches to Task Identification in the Home Environment," in 2nd International Conference on Pervasive Computing and Applications, Birmingham, 2007, pp.383-388.
dr
USman
NAEEM
PhD (Lon), BSc (Lon), SFHEA, SMIEEE
Dr Usman Naeem is a Reader (Associate Professor) in Computer Science Education within the School of Electronic Engineering and Computer Science at Queen Mary University of London. Usman is also a Queen Mary Academy Fellow in Learner Engagement Analytics.
Usman received his PhD from Queen Mary University of London in 2009.
His research focus is on educational and assistive technologies, which include machine learning techniques, mobile computing, and ambient intelligent environments.
Usman has taught on a variety of programmes, ranging from traditional programmes such as BSc Computer Science to degree apprenticeships programmes such as BSc Digital & Technology Solutions Professional.
Usman is also a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).
TEACHING
Usman has over 15 years of successful teaching experience in higher education, which includes teaching on a variety of undergraduate and postgraduate modules at Queen Mary University of London and University of East London.
Usman is a Senior Fellow of the Higher Education Academy (SFHEA). He also has Postgraduate Certificate in Learning and Teaching in Higher Education.
Usman is currently the co-ordinator for undergraduate and postgraduate projects.
Modules Taught
Queen Mary University of London
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Fundamentals of Web Technology (current)
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Software Engineering
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Enterprise Management
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Product Development
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Business Technology Strategy
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Professional Applications (Teaching Assistant)
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Internet Applications (Teaching Assistant)
Usman was involved in teaching on the joint programme with Beijing University of Posts and Telecommunication (BUPT) China.
University of East London
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Introduction to Computer Systems
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Introduction to Computer Systems and Networks
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Introduction to Computer Networks and Security
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Computer Architecture and Network Infrastructure
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Database Systems
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Professional Issues
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Operating Systems
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Design and Application of Mobile Computing Systems
The modules above span programmes such as: BSc Computer Science, BSc Computing for Business, BSc Digital & Technology Solutions Professional, MSc Mobile Communications, BSc Computing, BSc Computer Networks and BSc Software Engineering,
Usman also taught on the joint programme with Hangzhou Dianzi University (HDU) in China.
CONTACT
School of Electronic Engineering and Computer Science
Queen Mary University of London
5.01 People's Palace Building
Mile End Road
London
E1 4NS
+44 20 7882 6171