Wei Xie

Orcid: 0000-0001-9563-4927

Affiliations:
  • Northeastern University, Department of Mechanical and Industrial Engineering, Boston, MA, USA
  • Rensselaer Polytechnic Institute, Department of Industrial and System Engineering, Troy, NY, USA (former)
  • Northwestern University, Evanston IL, USA (PhD 2014)


According to our database1, Wei Xie authored at least 57 papers between 2010 and 2026.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Variance Reduction Based Experience Replay for Policy Optimization.
CoRR, February, 2026

2025
Efficient Sensitivity Analysis in Biomanufacturing with Sequential Shapley Value Estimation.
Asia Pac. J. Oper. Res., December, 2025

A Symbolic and Statistical Learning Framework to Discover Bioprocessing Regulatory Mechanism: Cell Culture Example.
CoRR, May, 2025

Digital Twin Calibration with Model-Based Reinforcement Learning.
CoRR, January, 2025

2024
Reinforcement Learning-Based MIMO Radar Multitarget Detection Assisted by Bayesian Inference.
IEEE Trans. Aerosp. Electron. Syst., August, 2024

Sensitivity Analysis on Interaction Effects of Policy-Augmented Bayesian Networks.
Proceedings of the Winter Simulation Conference, 2024

Linear Noise Approximation Assisted Bayesian Inference on Mechanistic Model of Partially Observed Stochastic Reaction Network.
Proceedings of the Winter Simulation Conference, 2024

Adjoint Sensitivity Analysis on Multi-Scale Bioprocess Stochastic Reaction Network.
Proceedings of the Winter Simulation Conference, 2024

Digital Twin Calibration for Biological System-of-Systems: Cell Culture Manufacturing Process.
Proceedings of the Winter Simulation Conference, 2024

2023
Policy Optimization in Dynamic Bayesian Network Hybrid Models of Biomanufacturing Processes.
INFORMS J. Comput., 2023

Stochastic simulation uncertainty analysis to accelerate flexible biomanufacturing process development.
Eur. J. Oper. Res., 2023

Structure-Function Dynamics Hybrid Modeling: RNA Degradation.
Proceedings of the Winter Simulation Conference, 2023

Policy-Augmented Bayesian Network Optimization with Global Convergence.
Proceedings of the Winter Simulation Conference, 2023

Stochastic Molecular Reaction Queueing Network Modeling for in Vitro Transcription Process.
Proceedings of the Winter Simulation Conference, 2023

2022
A pooled percentile estimator for parallel simulations.
J. Simulation, 2022

Integrate Bioprocess Mechanisms into Modeling, Analytics, and Control Strategies to Advance Biopharmaceutical Manufacturing and Delivery Processes.
CoRR, 2022

Variance Reduction based Partial Trajectory Reuse to Accelerate Policy Gradient Optimization.
CoRR, 2022

Dynamic Bayesian Network Auxiliary ABC-SMC for Hybrid Model Bayesian Inference to Accelerate Biomanufacturing Process Mechanism Learning and Robust Control.
CoRR, 2022

Opportunities of Hybrid Model-based Reinforcement Learning for Cell Therapy Manufacturing Process Control.
CoRR, 2022

Green Simulation Based Policy Optimization with Partial Historical Trajectory Reuse.
Proceedings of the Winter Simulation Conference, 2022

Sequential Importance Sampling for Hybrid Model Bayesian Inference to Support Bioprocess Mechanism Learning and Robust Control.
Proceedings of the Winter Simulation Conference, 2022

From Discovery to Production: Challenges and Novel Methodologies for Next Generation Biomanufacturing.
Proceedings of the Winter Simulation Conference, 2022

2021
Global-local Metamodel-assisted Stochastic Programming via Simulation.
ACM Trans. Model. Comput. Simul., 2021

Reinforcement learning assisted oxygen therapy for COVID-19 patients under intensive care.
BMC Medical Informatics Decis. Mak., 2021

A Nonparametric Bayesian Framework for Uncertainty Quantification in Stochastic Simulation.
SIAM/ASA J. Uncertain. Quantification, 2021

Green Simulation Assisted Policy Gradient to Accelerate Stochastic Process Control.
CoRR, 2021

Policy Optimization in Bayesian Network Hybrid Models of Biomanufacturing Processes.
CoRR, 2021

Reinforcement Learning under Model Risk for Biomanufacturing Fermentation Control.
CoRR, 2021

2020
Personalized Multimorbidity Management for Patients with Type 2 Diabetes Using Reinforcement Learning of Electronic Health Records.
CoRR, 2020

Blockchain-Enabled Internet-of-Things Platform for End-to-End Industrial Hemp Supply Chain.
CoRR, 2020

Data-Driven Stochastic Optimization for Power Grids Scheduling under High Wind Penetration.
CoRR, 2020

Green Simulation Assisted Reinforcement Learning With Model Risk for Biomanufacturing Learning and Control.
Proceedings of the Winter Simulation Conference, 2020

Simulation-Based Digital Twin Development for Blockchain Enabled End-to-End Industrial Hemp Supply Chain Risk Management.
Proceedings of the Winter Simulation Conference, 2020

2019
Bayesian sequential data collection for stochastic simulation calibration.
Eur. J. Oper. Res., 2019

Global-Local Metamodel Assisted Two-Stage Optimization via Simulation.
CoRR, 2019

Bayesian Network Based Risk and Sensitivity Analysis for Production Process Stability Control.
CoRR, 2019

Metamodel-Assisted Sensitivity Analysis for Controlling the Impact of Input Uncertainty.
Proceedings of the 2019 Winter Simulation Conference, 2019

Simulation-based Blockchain Design to Secure Biopharmaceutical Supply Chain.
Proceedings of the 2019 Winter Simulation Conference, 2019

Stochastic Simulation Model Development for Biopharmaceutical Production Process Risk Analysis and Stability Control.
Proceedings of the 2019 Winter Simulation Conference, 2019

2018
Simulation-based stochastic Programming to Guide Real-Time Scheduling for Smart Power Grids under Cyber Attacks.
Proceedings of the 2018 Winter Simulation Conference, 2018

A simulation-based Prediction Framework for stochastic System Dynamic Risk Management.
Proceedings of the 2018 Winter Simulation Conference, 2018

Metamodel-Assisted Risk Analysis for stochastic simulation with input uncertainty.
Proceedings of the 2018 Winter Simulation Conference, 2018

2017
An Efficient Budget Allocation Approach for Quantifying the Impact of Input Uncertainty in Stochastic Simulation.
ACM Trans. Model. Comput. Simul., 2017

A Factor-Based Bayesian Framework for Risk Analysis in Stochastic Simulations.
ACM Trans. Model. Comput. Simul., 2017

Asymmetric kriging emulator for stochastic simulation.
Proceedings of the 2017 Winter Simulation Conference, 2017

A stochastic simulation calibration framework for real-time system control.
Proceedings of the 2017 Winter Simulation Conference, 2017

Bayesian sequential calibration using detailed sample paths.
Proceedings of the 2017 Winter Simulation Conference, 2017

2016
Multivariate Input Uncertainty in Output Analysis for Stochastic Simulation.
ACM Trans. Model. Comput. Simul., 2016

A simulation-based prediction framework for two-stage dynamic decision making.
Proceedings of the Winter Simulation Conference, 2016

2015
Simulation optimization when facing input uncertainty.
Proceedings of the 2015 Winter Simulation Conference, 2015

A sequential experiment design for input uncertainty quantification in stochastic simulation.
Proceedings of the 2015 Winter Simulation Conference, 2015

Quantifying statistical uncertainty for dependent input models with factor structure.
Proceedings of the 2015 Winter Simulation Conference, 2015

2014
A Bayesian Framework for Quantifying Uncertainty in Stochastic Simulation.
Oper. Res., 2014

Quantifying Input Uncertainty via Simulation Confidence Intervals.
INFORMS J. Comput., 2014

Statistical uncertainty analysis for stochastic simulation with dependent input models.
Proceedings of the 2014 Winter Simulation Conference, 2014

2010
The influence of correlation functions on stochastic kriging metamodels.
Proceedings of the 2010 Winter Simulation Conference, 2010

A framework for input uncertainty analysis.
Proceedings of the 2010 Winter Simulation Conference, 2010


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