Dr. Md Asaduzzaman

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I am currently an Associate Professor of Operational Research at the University of Staffordshire in Stoke-on-Trent, UK. I joined the university as a Lecturer in 2014 and was promoted to Senior Lecturer in 2017. Previously, I served as faculty at the Institute of Statistical Research & Training (ISRT), University of Dhaka, Bangladesh, from 2001 to 2013.

Education

I have a background in Statistics and Operational Research (OR). I earned my B.Sc. (Hons) and M.Sc. degrees in Applied Statistics (major) and Mathematics and Economics (minor) from the University of Dhaka, Bangladesh, in 1999 and 2001, respectively. Additionally, I obtained an M.Sc. in Bioinformatics from the Chalmers University of Technology in Gothenburg, Sweden, in 2007, and a Ph.D. in Operational Research from the University of Westminster in London, UK, in 2010.

Research Interests

My research sits at the intersection of operational research, applied statistics, and machine learning, with a strong focus on bridging rigorous methodology and real-world application. I develop probabilistic and optimisation-based models to solve complex, data-driven problems in systems operating under uncertainty.

By leveraging continuous-time stochastic processes, Markov models, optimisation, and spatial-temporal inference, my work delivers actionable insights and decision-support tools across three primary domains:

  • Healthcare Systems & Epidemiology: Improving clinical and operational decision-making by designing capacity planning and resource allocation frameworks, predicting patient length of stay (LOS), identifying high-risk patient cohorts, and modelling infectious disease dynamics.
  • Communication Networks: Enhancing network efficiency through performance measurement, queueing dynamics, and resource optimisation.
  • Environmental Sciences & Hazards: Conducting risk assessments and predictive modelling for precipitation, temperature trends, and extreme natural events like floods and cyclones.
  • I also contribute to clinical trials by developing and reviewing statistical analysis plans, overseeing statistical issues, and participating in trial management and data monitoring committees. This work supports the robust design, conduct, monitoring, analysis, and interpretation of clinical studies.

Whether refining algorithmic approaches or collaborating on fieldwork, my ultimate goal is to translate complex mathematical frameworks into practical solutions for healthcare, infrastructure, and environmental resilience.

Major Publications

My methodological research includes the development of continuous-time Markov chain loss-network models and overflow systems for capacity planning in healthcare networks, published in leading journals such as the Journal of the Royal Statistical Society: Series A, European Journal of Operational Research, and Annals of Operations Research. These studies introduced stochastic modelling frameworks for analysing capacity-constrained systems and networked service structures under uncertainty.

I have also developed Markov renewal process models for environmental prediction, including a parametric stochastic framework for tropical cyclone forecasting, and optimisation methodologies for dynamic spectrum sharing and resource allocation in wireless communication systems, published in IEEE Transactions on Wireless Communications, IEEE Transactions on Vehicular Technology, and IEEE Transactions on Mobile Computing.

More recently, my research has focused on methodological challenges arising from partially observed stochastic systems, dynamic networks, and infectious disease transmission processes. My work integrates ideas from continuous-time Markov processes, likelihood-based inference, network modelling, and data augmentation methods to develop statistically rigorous frameworks for analysing complex dynamic systems.

Awards and Honours

My contributions have been recognised through several distinctions, including the UK Operational Research Society’s ‘The Doctoral Award’ Runner-Up and a Dean’s Honour Award for research published in the Journal of the Royal Statistical Society.

Professional Activities