Sheema Noorain

Dr. Sheema Noorain serves as a Lecturer and Course Leader for the MSc in Big Data Technologies program at the University of Westminster, where she designs curriculum and delivers specialized instruction in Business Analytics, Business Optimization, Data Warehousing, and Business Intelligence. Her role directly shapes data science professionals equipped with cutting-edge analytical skills for industry applications.

Her academic foundation includes a B.E. in Information Science and Engineering (2013), professional experience as a Business Intelligence Analyst, an MSc in Business Analytics, and a PhD in Operational Research from the University of Kent. This trajectory bridges industry practice with advanced methodological expertise.

Dr. Noorain's research centers on Operational Research applications in healthcare systems, particularly mental health services. She develops innovative frameworks integrating optimization, simulation, and machine learning to solve complex service delivery challenges. Her work emphasizes practical translation of analytical insights into actionable healthcare improvements through stakeholder collaboration.

Her publication record demonstrates consistent focus on mental healthcare optimization, with 2022-2019 works establishing her expertise in systematic reviews of optimization methodologies and discrete-event simulation applications. These contributions highlight growing influence in health systems research.

As an active academic citizen, she serves The Operational Research Society and provides peer review for European Journal of Operational Research and BMC Health Services Research. Her editorial work supports rigorous scholarship in operational research applications.

Dr. Noorain leads significant grant-funded research as Principal Investigator for NHS collaborations, including a major West Kent Primary Care Mental Health Service improvement initiative. These projects exemplify her ability to secure and manage impactful interdisciplinary research.

Her Health and Social Care Modelling research group affiliation provides institutional context for her work, facilitating collaboration on healthcare analytics projects that address real-world service delivery challenges through advanced methodological approaches.