PhD (Lon), BSc (Lon), SFHEA
Dr Usman Naeem is a Senior Lecturer (Associate Professor) within the School of Electronic Engineering and Computer Science at Queen Mary University of London. He received his PhD from Queen Mary University of London in 2009.
His research focus is on assistive technologies, which includes 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 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.
Queen Mary University of London
Fundamentals of Web Technology (current)
Business Technology Strategy
Professional Applications (Teaching Assistant)
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
Introduction to Computer Systems
Introduction to Computer Systems and Networks
Introduction to Computer Networks and Security
Computer Architecture and Network Infrastructure
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.
Usman's current research interests are within the areas of Pervasive/Ubiquitous Computing. His research is focused on the development of assistive technologies to support independent living.
Research interests also include:
Ambient Intelligent Environments
Machine Learning Techniques
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