Ali Eshragh, PhD

Ali Eshragh is an Associate Professor of Operations Management and Business Analytics at the Johns Hopkins Carey Business School. His main expertise is in modeling and optimizing real-world complex systems in the presence of uncertainty to provide optimal decisions and significant inferences for managers and policy makers.

Ali publishes regularly in leading Operations Research and Machine Learning journals including Mathematics of Operations Research, Annals of Operations Research, and Journal of Machine Learning Research, and actively collaborate with several outstanding national and international researchers. He has been involved as a Principal Investigator (PI or Co-PI) in 11 funded research projects totaling USD 1,987,407, and won several awards for his excellence in teaching, research, and service. He has consulted for several service institutes and manufacturing companies in the areas of demand forecasting, logistic optimization, and inventory management.

Ali has developed, coordinated and taught several undergraduate as well as postgraduate courses in the areas of statistics, optimization, and supply chains such as Data Analytics for Business Intelligence, Forecasting with Linear Time Series Models, and Supply Chain Optimization. Across the last three years he received student feedback on teaching and courses average score of 4.8 (out of 5).

Prior to joining Carey, Ali was a Senior Lecturer in Data Science (equivalent to tenured Associate Professor in the US system) at the University of Newcastle. From 2019 to 2021, he was the Deputy Head of School in Industry and Engagement, and in 2021, he was program director of the two online programs titled Graduate Certificate in Data Analytics/Science at the University of Newcastle.

Education

• PhD, Stochastic Operations Research, University of South Australia
• MS, Industrial Engineering, Sharif University of Technology 
• BS, Industrial Engineering, Sharif University of Technology

Research

Selected publications

• A. Eshragh, F. Roosta, A. Nazari and M. Mahoney. LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series Data, Journal of Machine Learning Research, 23:1-36, 2022.
• A. Eshragh, J. Filar, T. Kalinowski and S. Mohammadian. Hamiltonian Cycles and Subsets of Discounted Occupational Measures, Mathematics of Operations Research, 45(2):403-795, 2020.
• A. Eshragh, S. Alizamir, P. Howley and E. Stojanovski. Modeling the Dynamics of the COVID-19 Population in Australia: A Probabilistic Analysis, PLOS-One, 15(10):e0240153, 2020.
• A. Eshragh, R. Esmaeilbeigi and R. Middleton. An Analytical Bound on the Fleet Size in Vehicle Routing Problems: A Dynamic Programming Approach, Operations Research Letters, 48(3):350-355, 2020.
• M. Abolghasemi, J. Hurley, A. Eshragh and B. Fahimnia. Demand Forecasting in the Presence of Systematic Events: Cases in Capturing Sales Promotions, International Journal of Production Economics, 230:107892, 2020.
• N.G. Bean, R. Elliott, A. Eshragh and J.V. Ross. On Binomial Observation of Continuous-time Markovian Population Models, Journal of Applied Probability, 52:457-472, 2015.
• B. Fahimnia, J. Sarkis and A. Eshragh. A Trade-off Model for Green Supply Chain Planning: A Leanness-Versus-Greenness Analysis, OMEGA, 54:173-190, 2015.
• A. Eshragh and J. Filar. Hamiltonian Cycles, Random Walks and the Geometry of the Space of Discounted Occupational Measures, Mathematics of Operations Research, 36(2):258-270, 2011.

Working papers

• SALSA: Sequential Approximate Leverage Score Algorithm with Application in Fitting ARMA Models to Big Time Series Data, Joint work with G. Livingston, M. Mahoney, F. Roosta, and L. Yerbury.
• Large-scale Group Decision-making and Rank Clustering, Joint work with B. Aslani, A. Fattahi, and M. Rabiee.
• Average-reward Model-free Reinforcement Learning: A Systematic Review and Literature Mapping, Joint work with V. Dewanto, G. Dunn, M. Gallagher and F. Roosta.

Teaching

Current

• Forecasting Models for Business Intelligence
• Statistical Analysis
• Business Analytics
• Simulation for Business Applications

Honors and distinctions

• Associate Editor and Member of Editorial Board, Environmental Modeling & Assessment, Springer Journal, 2020-Present. 
• Staff Excellence Award in the Category of Values Award, University of Newcastle, 2020.
• Australian Society for Operations Research Rising Star Award, 2017.
• Teaching Excellence and Contribution to Student Learning Team Award - Honorable Mention, University of Newcastle, 2016.
• South Australia Science Excellence Award in the Category of PhD Research Excellence in Physical Sciences, Mathematics and Engineering- Honorable Mention, Government of South Australia, 2011.
• B.H. Neumann Prize for the Best Student Talk - Honorable Mention, The 54th Annual Australian Mathematical Society Conference, 2010.
• Endeavor International Postgraduate Research Scholarship Award, The Australian Government, 2008-2011.