Welcome to
Prof. Xinyun CHEN WEBSITE
Xinyun Chen is currently an Associate Professor in the Schoo of Data Science at The Chinese University of Hong Kong, Shenzhen. She received her Ph.D in Operations Research from Columbia University in 2014. Her research interests include applied probability, stochastic simulation, queueing theory and reinforcement learning. She has published papers in journals and conferences including Annals of Applied Probability, Mathematics of Operations Research, Operations Research and ICLR.
Professional Services:
Council Member, INFORMS Applied Probability Society, 2019-2021
Editor, Applied Probability Trust, 2020-
Cluster Chair, INFORMS Annual Meeting, 2020
Programe Committee, Performance, 2020
* denotes industry/medical collaborator; underline denotes Ph.D student
Working Papers
Data-Pooling Reinforcement Learning for Personalized Healthcare Intervention, with Pengyi Shi and Shanwen Pu, submitted to Management Science. [arXiv]
(A short version of the paper is accepted to Reinforcement Learning for Real Life Workshop @ ICML 2021). [video].
Online Learning and Optimization for Queues with Unknown Demand Curve and Service Distribution, with Yunan Liu and Guiyu Hong, working paper. [arXiv]
Journal Papers
Two-parameter Sample Path Large Deviations for Infinite Server Queues, with Jose Blanchet and Henry Lam (2014). Stochastic Systems, 4:206-249.
Steady-state simulation of reflected Brownian motion and related stochastic networks, with Jose Blanchet (2015). Annals of Applied Probability, 25:3209-3250.
ε-Strong Simulation for Multidimensional Stochastic Differential Equations via Rough Path Analysis, with Jose Blanchet and Jing Dong (2017). Annals of Applied Probability, 27:275-336.
Does the T+1 Rule Really Reduce Speculation? Evidence from Chinese Stock Index ETF, with Yan Liu and Tao Zeng (2018), Accounting and Finance, 57:1287–1313.
Many-server Gaussian limits for overloaded non-Markovian queues with customer abandonment, with A. Korhan Aras and Yunan Liu (2018), Queueing Systems: Theory and Applications, 89(1): 81-125.
Perfect Sampling for Generalized Jackson Networks, with Jose Blanchet (2019), Mathematics of Operations Research, 44(2): 693-714.
Rates of Convergence to Stationarity for Reflected Brownian Motion, with Jose Blanchet (2020), Mathematics of Operations Research, 45(2):660-681.
Perfect Sampling of Hawkes Processes and Queues with Hawkes Arrivals (2021), Stochastic Systems, 11(3), 264-283. [pdf]
Efficient Steady-state Simulation of High-dimensional Stochastic Networks, with Jose Blanchet, Peter Glynn and Nian Si (2021), Stochastic Systems, 11(2):174-192. [pdf]
A Multifactor Regime-switching Model for Inter-trade Durations in the High-frequency Limit Order Market, with Zhicheng Li and Haipeng Xing, Economic Modelling, 118(2023):106082. [pdf]
An Online Learning Approach to Dynamic Pricing and Capacity Sizing in Service Systems, with Yunan Liu and Guiyu Hong, Operations Research, to appear. [pdf]
Conference Proceedings
Exact gradient simulation for stochastic fluid networks in steady state. Winter Simulation Conference (WSC), 2014.
Modeling inter-trade durations in the limit order market, with Jianzhao Yang, Zhicheng Li and Haipeng Xing. 2016 Symposium of the International Chinese StatisticalAssociation Series: Springer Proceedings in Mathematics & Statistics, Vol. 57. Springer-Verlag, New York.
Infinite-horizon off-policy policy evaluation with multiple behavior policies, with Lu Wang, Yizhe Hang, Heng Ge and Hongyuan Zha. ICLR 2020.
Perfect Sampling of Multi-dimensional Hawkes Process, with Xiuwen Wang, Winter Simulation Conference (WSC) , 2020. [arXiv]
A High-fidelity, Machine-learning Enhanced Queueing Network Simulation Model for Hospital Ultrasound Operations, with Yihan Pan, Zhenghang Xu, Jin Guang, Jingjing Sun, Chengwenjian Wang, Xuanming Zhang, Jim Dai, Yichuan Ding, Pengyi Shi, Hongxin Pan*, Kai Yang* and Song Wu*, Winter Simulation Conference (WSC), 2021. [pdf]
Tail Quantile Estimation for Non-preemptive Priority Queues, with Jin Guang, Guiyu Hong, Xi Peng*, Li Chen*, Bo Bai*, Gong. Zhang*. Winter Simulation Conference (WSC), 2022. [arXiv]
