Shamaila Iram

Dr. Shamaila Iram is a Senior Lecturer in Data Science at the Department of Computer Science, School of Computing and Engineering, University of Huddersfield. She serves as the programme leader for the MSc Data Analytics and is an active member of the Centre for Industrial Analytics and the Centre for Autonomous and Intelligent Systems. Dr. Iram is currently accepting PhD students and is involved in cutting-edge research in data science, machine learning, and smart systems.

Research Interests: Her work spans Big Data Analysis, Data Mining, Machine Learning, Data Visualization, Internet of Things (IoT), Smart Cities, Smart Homes, and Smart Manufacturing. She applies these technologies to domains such as energy efficiency in buildings and early detection of neurodegenerative diseases using gait and EEG signals. Her research contributes to UN Sustainable Development Goals, particularly in sustainable cities and industries.

Publication Trends: Her recent and upcoming publications (2022–2025) focus on machine learning applications in energy efficiency, explainable AI for building analytics, digital twins in industrial systems, and stakeholder engagement in energy assessment. These works reflect a strong interdisciplinary approach combining computer science with real-world engineering and environmental challenges.

Scientific Service and Leadership: Dr. Iram has organized research conferences such as the 1st International Workshop on Big Data Analytics for Sustainable Environments (BDASE2018). She is a reviewer for high-impact journals and actively contributes to academic discourse in smart systems and data analytics.

Supervision and Collaboration: She supervises PhD students and has led collaborative research projects, including the EU Framework Programme ProSEco. Her work involves multi-institutional and interdisciplinary teams, particularly in energy and healthcare applications.

Laboratories and Research Groups: Dr. Iram is affiliated with the Centre for Industrial Analytics and the Centre for Autonomous and Intelligent Systems at the University of Huddersfield, where she contributes to research on intelligent systems, digital twins, and industrial data science.