Dr Rasul Esmaeilbeigi

Rasul’s area of expertise is Operations Research (OR) and more broadly data science and prescriptive analytics (data-driven decision making). He has in-depth knowledge of a wide range of mathematical, statistical and optimisation techniques and software tools that are crucial for research and practice of decision making. Defining, modelling, and solving real-world optimisation problems through state-of-the-art mathematical programming techniques constitutes a significant part of his experience. Rasul believes in research translation and has a track record of real case studies in supply chain network design and resource planning. He has a track record of publications in top-tier OR journals and considerable expertise in developing decision support software for service and manufacturing industries.

Rasul received his PhD in Mathematics from the University of Newcastle in 2020. In his PhD, he employed machine learning, dynamic programming, mixed integer linear programming and two-stage stochastic programming approaches to solve variants of a supply chain network design problem. He developed decomposition algorithms that scale well with the number of uncertain scenarios, conducted extensive benchmarking under various scenarios, and provided managerial insights for a real case study. In his post-doctoral role at Deakin University, Rasul applied his expertise to develop a decision support system (called optimiser engine) for a real-world resource planning problem. An extensive simulation study demonstrated that the proposed optimiser significantly improves the efficiency of client’s operations over time, thereby potentially saving millions of dollars for them. Due to the significance of the theoretical and practical contributions, this work was selected as a semi-finalist of INFORMS Franz Edelman Award (2021).

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