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 and postgraduate courses in the areas of statistics, optimization, and supply chains, including Business Analytics, Forecasting Models for Business Intelligence, and Simulation for Business Applications. Over the past three years, he has received an average student feedback score of 4.7 out of 5 for his teaching and courses.

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, M. P. Skerritt, B. Salvye, and T. McCallum, Optimal Experimental Design for Partially Observable Pure Birth Processes, Forthcoming in PLOS ONE, 2025   
• S. Mahmoudinazlou, A. Sobhanan, H. Charkhgard, A. Eshragh, and Deep Reinforcement Learning for Dynamic Order Picking in Warehouse Operations, Computers and Operations Research, 182:107112, 2025
• 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.
• 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

• A. Eshragh, Y. Li, L. Yerbury, F. Roosta, and M. W. Mahoney, Efficient Leverage Score Subsampling Methods with Applications in Large-Scale Energy Market Demand Forecasting   
• A. Eshragh, A. Fattahi, Y. Li, and K. Wang, Bridging Data-Driven Learning and Optimization for Efficient Decision-Making in Large-Scale Uncertain Models  
• A. Fattahi, A. Eshragh, B. Aslani, and M. Rabiee, Ranking Vectors Clustering: Theory and Applications

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.

Impact & Engagement

• Chair and Organizer, Business Analytics, Artificial Intelligence, and Cherry Blossom Conference, Washington, D.C., March 22-23, 2025  

• Chair and Organizer, Carey AI Integration Gathering (CRAIG), Washington, D.C., 2024-2025