At Robust Analytics & Systems Simulation (RASS) lab, we bring together advanced artificial intelligence (AI) models and operations management decisions. Our interdisciplinary team focus on applying machine learning algorithms, quantitative mathematical modeling, and system simulation techniques to improve business decisions in various industries including supply chain management, logistics, and healthcare. 

 Research Streams:

 Publications & Working Papers:

Data Analytics & Revenue Optimization

1. Sison, N., Li, L., Han, M. (2021) Survey of Machine Learning and Deep Learning Techniques for Travel Demand Forecast. (Accepted) Proceeding of the 5th IEEE International Conference on Smart City Innovations.

2. Li, L., & Zhou, Y. (2019). Mitigating Customers’ Downsell Risk for Single-leg Revenue Management with Demand Dependencies. 2019 Winter Simulation Conference (WSC), IEEE

3. Gallego, G., Li, L., & Ratliff, R. (2009). Choice-Based EMSR Methods for Single-leg Revenue Management with Demand Dependencies, Journal of Revenue and Pricing Management, 8(2), 207-240

Healthcare System Modeling and Simulation

1. Zhou, Y., Nikolaev, A., Bian, L., Lin, L., & Li, L. (2021) Investigating Transmission Dynamics of Influenza in a Public Indoor Venue: An agent-based modeling approach. Computers & Industrial Engineering, 157, 107327

2. Zhou, Y., Li, L. & Ghasemi, Y.  (2021) An Agent-Based Model for Simulating COVID-19 Transmissions on University Campus and Its Implications on Mitigation Interventions: A Case Study. Information Discovery and Delivery, special issue on Using Data Science to Understand Coronavirus Pandemic. 

3. Vyas, J. D., Han, M., Li, L., Pouriyeh, S., & He, J. S. (2020). Integrating Blockchain Technology into Healthcare. Proceedings of the 2020 ACM Southeast Conference.

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Smart Supply Chain Management

1. Li, L., Katircioglu, K., & Sourijan, K. (2010). Empirical methods for two-echelon inventory management with service level constraints based on simulation-regression, Winter Simulation Conference 2010 

Engineering Education

Others

1. Wan, M., Han, M., Li, L., Li, Z., & He, S. (2020). Effects of and Defenses Against Adversarial Attacks on a Traffic Light Classification CNN. Proceedings of the 2020 ACM Southeast Conference.

2. Rudd, J. M., Henshaw, A. M., Staples, L., Akkineni, S., Li, L., & DeMaio, J. (2020). Genetic Algorithm Guidance of a Constraint Programming Solver for the Multiple Traveling Salesman Problem. KSU digital commons