| 2026 | ACL | Dynamics of Cognitive Heterogeneity: Investigating Behavioral Biases in Multi-Stage Supply Chains with LLM-Based Simulation. | Jiuyun Jiang, Yuecheng Hong, Bo Yang, Jin Yang, Guangxin Jiang, Xiaomeng Guo, Guang Xiao |
| 2025 | WSC | Neural Network-Based Methods for Continuous Simulation Optimization Problems with Covariates. | Yize Hao, Guangxin Jiang |
| 2025 | WSC | Enhanced Upper Confidence Bound Procedure for Large-Scale Ranking and Selection. | Song Huang, Guangxin Jiang, Chenxi Li, Ying Zhong |
| 2025 | WSC | An Efficient Bipartite Graph Sampling Algorithm with Prescribed Degree Sequences. | Tong Sun, Jianshu Hao, Zhiyang Zhang, Guangxin Jiang |
| 2024 | DASFAA | PT-Tuning: Bridging the Gap between Time Series Masked Reconstruction and Forecasting via Prompt Token Tuning. | Hao Liu, Jinrui Gan, Xiaoxuan Fan, Yi Zhang, Chuanxian Luo, Jing Zhang, Guangxin Jiang, Yucheng Qian, Changwei Zhao, Huan Ma, Zhenyu Guo |
| 2022 | WSC | Importance Sampling for Rare-Event Gradient Estimation. | Yuanlu Bai, Shengyi He, Henry Lam, Guangxin Jiang, Michael C. Fu |
| 2022 | WSC | Importance Sampling for CoVaR Estimation. | Guangxin Jiang, Xin Yun |
| 2020 | WSC | Online Risk Measure Estimation VIA Natural Gradient Boosting. | Xiaoting Cai, Yang Yang, Guangxin Jiang |
| 2020 | WSC | Reusing Simulation Outputs of Repeated Experiments Via Likelihood Ratio Regression. | Ben Feng, Guangxin Jiang |
| 2018 | WSC | On efficiencies of stochastic Optimization Procedures under Importance Sampling. | Henry Lam, Guangxin Jiang, Michael C. Fu |
| 2016 | WSC | A simulation analytics approach to dynamic risk monitoring. | Guangxin Jiang, L. Jeff Hong, Barry L. Nelson |
| 2015 | WSC | Optimal importance sampling for simulation of lvy processes. | Guangxin Jiang, Michael C. Fu, Chenglong Xu |