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Research Work

Research Interests

  • Theory:

    • Data-Driven Distributionally Robust Optimization

    • Stochastic Programming and Chance-Constrained Programming

    • Integrated Learning-and-Optimization Frameworks

    • Integer and Mixed-Integer Programming

  • Applications:

    • Financial Risk Modeling and Portfolio Optimization

    • Humanitarian Relief Operations and Disaster Management

    • Predictive Maintenance and Machine Scheduling

    • Supply Chain Analytics and Optimization

    • Sustainable Waste Management

    • Bus Fleet Electrification and Smart Charging

Funded Projects

  • Artificial Intelligence and Advanced Analytics to Estimate Collision Risk during Departure and Arrival. Role: Co-PI; PI: Lance Sherry. Total amount: $1,446,374. FAA and University of Maryland Baltimore County. 2022–2027.

  • Explainable and Transparent Machine Learning for Autonomous Decision Making (EXTRA). Role: Co-PI; PI: K.C. Chang. Total amount: $280,000. U.S. Air Force. 2022–2023.

  • Decision Support Tools for Smart Municipal Solid Waste Collection. Role: Co-PI; PI: Kuo Tian. Total amount: $20,000. 4-VA. 2022–2023.

  • Illegal Drug Supply Network Disruption: Learning and Optimization Frameworks. Role: Co-PI; PI: Weijun Xie. Total amount: $30,000. 4-VA. 2022–2023.

  • Condition-Based Predictive Maintenance for Mission Critical Systems with Probabilistic Knowledge Graph and Deep Learning. Role: Co-PI; PI: K.C. Chang. Total amount: $480,000. U.S. Department of the Navy. 2020–2021.

Journal Publications

  • Fontem, B., and R. Ji, “Distributionally Robust Optimization with Generalized Total Variation Ambiguity Sets”, European Journal of Operational Research (2025).

  • Jiang, Z., and R. Ji, “Optimizing Hurricane Shelter Locations with Smart Predict-then-Optimize Framework”, International Journal of Production Research 63(8) (2025): 2905–2925.

  • Li, D., Z. Jiang, K. Tian, and R. Ji, “Estimation of Hydraulic Conductivity of Bentonite-Polymer GCLs with Machine Learning Techniques”, Environmental Geotechnics 12(6) (2025): 433–451.

  • Li, D., Z. Jiang, K. Tian, and R. Ji, “Prediction of Hydraulic Conductivity of Sodium Bentonite GCLs by Machine Learning Approaches”, Environmental Geotechnics 40(2) (2025): 154–173.

  • Fan, Z., R. Ji, and M. A. Lejeune, “Distributionally Robust Portfolio Optimization under Marginal and Copula Ambiguity”, Journal of Optimization Theory and Applications 203(3) (2024): 2870–2907.

  • Fan, Z., R. Ji, S.-C. Chang, and K.-C. Chang, “Novel Integer L-Shaped Method for Parallel Machine Scheduling under Uncertain Sequence-Dependent Setups”, Computers & Industrial Engineering 193 (2024): 110282.

  • Hashemi-Amiri, O., F. Ghorbani, and R. Ji, “Integrated Supplier Selection, Scheduling, and Routing Problem for Perishable Product Supply Chain: A Distributionally Robust Approach”, Computers & Industrial Engineering 175 (2023): 108845.

  • Jiang, Z., R. Ji, and Z. Dong, “A Chance-Constrained Distributionally Robust Optimization Model for Humanitarian Relief Network Design”, OR Spectrum 45(4) (2023): 1153–1195.

  • Jiang, Z., Y. Chen, T.-Y. Yang, W. Ji, and R. Ji, “Leveraging Machine Learning and Simulation to Advance Disaster Preparedness Assessments through FEMA National Household Survey Data”, Sustainability 15(10) (2023): 8035.

  • Hashemi-Amiri, O., R. Ji, and K. Tian, “Integrated Location-Scheduling-Routing Framework for Smart Municipal Solid Waste Systems”, Sustainability 15(10) (2023): 7774.

    • Featured as Cover Paper

  • Fan, Z., K. C. Chang, R. Ji, and G. Chen, “Data Fusion for Optimal Condition-Based Aircraft Fleet Maintenance with Predictive Analytics”, Journal of Advances in Information Fusion 18(2) (2023): 102–117.

  • Ji, R., M. A. Lejeune, and Z. Fan, “Distributionally Robust Portfolio Optimization with Linearized STARR Performance Measure”, Quantitative Finance 22(1) (2022): 113–127.

  • Zhang, S., M. Li, J. Zhang, Y. Liu, W. Jiang, X. Li, H. Qi, L. Tang, R. Ji, W. Zhao, Y. Gu, and L. Qi, “Identification of Nutational Signature for Lung Adenocarcinoma Prognosis and Immunotherapy Prediction”, Journal of Molecular Medicine 100(12) (2022): 1755–1769.

  • Ji, R., and M. A. Lejeune, “Data-Driven Distributionally Robust Chance-Constrained Programming with Wasserstein Metric”, Journal of Global Optimization 79(4) (2021): 779–811.

    • Best Paper Award, Journal of Global Optimization (2021)

  • Ji, R., and M. A. Lejeune, “Data-Driven Optimization with Reward-Risk Ratio Measures”, INFORMS Journal on Computing 33(3) (2021): 1120–1137.

  • Jiang, Z., R. Ji, and K.-C. Chang, “A Machine Learning Integrated Portfolio Rebalance Framework with Risk-Aversion Adjustment”, Journal of Risk and Financial Management 13(7) (2020): 155.

  • Ji, R., and B. Kamrad, “Newsvendor Model as an Exchange Option on Demand and Supply Uncertainty”, Production and Operations Management 28(10) (2019): 2456–2470.

  • Ji, R., and M. A. Lejeune, “Risk-Budgeting Multi-Portfolio Optimization with Portfolio and Marginal Risk Constraints”, Annals of Operations Research 262(2) (2018): 547–578.

  • Ji, R., M. A. Lejeune, and S. Y. Prasad, “Properties, Formulations and Algorithms for Portfolio Optimization Using Mean-Gini Criteria”, Annals of Operations Research 248(1) (2017): 305–343.

Papers Under Review or Revision

  • Kamrad, B., and R. Ji, “Commodity and Index-Based Hedging: An Analytical Framework for Valuing Supply Options under Volatility and Commitment Risk”, Major Revision (2025).

  • Ji, R., B. Kamrad, and S. Dahiya, “From Volatility to Value: An Analytical Study of Supply Options for Risk and Commitment Management”, Under Revision (2025).

  • Aslani, B., S. Mohebbi, and R. Ji, “Multi-Stage Stochastic Network Restoration Problems: Learn-to-Construct Cuts for Nested Benders Decomposition”, Under Review (2025).

  • Hashemi-Amiri, O., and R. Ji, “Multi-Objective Optimization for Sustainable Municipal Solid Waste Management Using Genetic Algorithms”, Under Review (2025).

  • Kamrad, B., and R. Ji, “Risk Mitigation in Fixed Price Supply Contracts: Sourcing as a Portfolio of Options”, Under Revision (2025).

  • Jiang, Z., and R. Ji, “Enhancing Equity in Disaster Relief: Integrating Individual Disaster Preparedness Metrics and Multi-Objective Optimization for Relief Resource Allocation”, Under Review (2025).

Conference Proceedings

  • Jiang, Z., R. Ji, Y. Chen, and W. Ji, “Machine Learning and Simulation-Based Framework for Disaster Preparedness Prediction”, 2021 Winter Simulation Conference, IEEE (2021): 1–10.

  • Ji, R., K.C. Chang, and Z. Jiang, “Risk-Aversion Adjusted Portfolio Optimization with Predictive Modeling”, 22nd International Conference on Information Fusion (FUSION), IEEE (2019): 1–8. [Link]

  • Dong, Z., S. Hu, and R. Ji, “A CVaR-Based Facility Location Model for Uncertain Demand in Disaster Operations Management”, IISE Annual Conference Proceedings (2019): 1294–1299.

  • Ji, R., M. A. Lejeune, and S. Y. Prasad, “Dynamic Portfolio Optimization with Risk-Aversion Adjustment Utilizing Technical Indicators”, 20th International Conference on Information Fusion (2017): 1787–1794. [Link]

Book Chapters

  • Ji, R., M. A. Lejeune, and S. Y. Prasad, “Interactive Portfolio Optimization Using Mean-Gini Criteria”, Financial Decision Aid Using Multiple Criteria Models (2018): 49–91. Springer. [Link]

  • Kamrad, B., R. Ji, and G. M. Schmidt, “Managing Supply Risk in Fixed Price Contracts: A Contingent Claims Perspective”, Foundations and Trends in Technology, Information, and Operations Management 11(1-2) (2018): 65–88. [Link]