headshot of Abdulrahman Ahmed

Abdulrahman Ahmed

Researcher Graduate Student
ABA173@pitt.edu
Industrial Engineering

overview

Abdulrahman is a PhD student in the industrial engineering department at the University of Pittsburgh. His current research focuses on devising efficient techniques for estimating treatment effects from large-scale simulations (i.e., simulation metamodel), particularly in scenarios where sampling from these simulations proves to be resource-intensive. Previously, he worked on developing reinforcement learning methods for a financial problem called optimal execution problem, where the decision maker needs to devise a cost-saving strategy to maximize the gain from the execution. He got his MSc and BSc in operations research and computer science from Cairo University.

about

MSc, Operations Research and Computer Science, Cairo University, 2022

BSc, Operations Research and Computer Science, Cairo University, 2011 - 2015

Ahmed, A.A., Rahimian, M.A., & Roberts, M.S. (2024). Optimized Model Selection for Estimating Treatment Effects from Costly Simulations of the US Opioid Epidemic.

Ahmed, A.A., Rahimian, M.A., & Roberts, M.S. (2023). Inferring Epidemic Dynamics Using Gaussian Process Emulation of Agent-Based Simulations. In 2023 Winter Simulation Conference (WSC), 00, (pp. 770-780).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/wsc60868.2023.10408157.

Ahmed, A.A., Rahimian, M.A., & Roberts, M.S. (2023). Estimating Treatment Effects Using Costly Simulation Samples from a Population-Scale Model of Opioid Use Disorder. In 2023 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI), 00, (pp. 1-4).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/bhi58575.2023.10313496.

Ahmed, A.A., Ghoneim, A., & Saleh, M. (2020). Optimizing stock market execution costs using reinforcement learning. In 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 00, (pp. 1083-1090).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/ssci47803.2020.9308153.