3 citations · 17 across the 14 of their papers we have counts for
14 papers
Variance Reduction Based Experience Replay for Policy Optimization
Hua Zheng, Wei Xie, M. Ben Feng +1
Effective reinforcement learning (RL) for complex stochastic systems requires leveraging historical data to improve sample efficiency and accelerate policy optimization. However, c…
Digital Twin Calibration for Biological System-of-Systems: Cell Culture Manufacturing Process
Fuqiang Cheng, Wei Xie, Hua Zheng
Biomanufacturing innovation relies on an efficient Design of Experiments (DoEs) to optimize processes and product quality. Traditional DoE methods, ignoring the underlying bioproce…
Stochastic Molecular Reaction Queueing Network Modeling for In Vitro Transcription Process
Keqi Wang, Wei Xie, Hua Zheng
To facilitate a rapid response to pandemic threats, this paper focuses on developing a mechanistic simulation model for in vitro transcription (IVT) process, a crucial step in mRNA…
Structure-Function Dynamics Hybrid Modeling: RNA Degradation
Hua Zheng, Wei Xie, Paul Whitford +3
RNA structure and functional dynamics play fundamental roles in controlling biological systems. Molecular dynamics simulation, which can characterize interactions at an atomistic l…
Stochastic Biological System-of-Systems Modelling for iPSC Culture
Hua Zheng, Sarah W. Harcum, Jinxiang Pei +1
Large-scale manufacturing of induced pluripotent stem cells (iPSCs) is essential for cell therapies and regenerative medicines. Yet, iPSCs form large cell aggregates in suspension…
Variance Reduction based Experience Replay for Policy Optimization
Hua Zheng, Wei Xie, M. Ben Feng
For reinforcement learning on complex stochastic systems where many factors dynamically impact the output trajectories, it is desirable to effectively leverage the information from…
Variance Reduction based Partial Trajectory Reuse to Accelerate Policy Gradient Optimization
Hua Zheng, Wei Xie
Built on our previous study on green simulation assisted policy gradient (GS-PG) focusing on trajectory-based reuse, in this paper, we consider infinite-horizon Markov Decision Pro…
Sequential Importance Sampling for Hybrid Model Bayesian Inference to Support Bioprocess Mechanism Learning and Robust Control
Wei Xie, Keqi Wang, Hua Zheng +1
Driven by the critical needs of biomanufacturing 4.0, we introduce a probabilistic knowledge graph hybrid model characterizing the risk- and science-based understanding of bioproce…
Opportunities of Hybrid Model-based Reinforcement Learning for Cell Therapy Manufacturing Process Control
Hua Zheng, Wei Xie, Keqi Wang +1
Driven by the key challenges of cell therapy manufacturing, including high complexity, high uncertainty, and very limited process observations, we propose a hybrid model-based rein…
On the Convergence of Experience Replay in Policy Optimization: Characterizing Bias, Variance, and Finite-Time Convergence
Hua Zheng, Wei Xie, M. Ben Feng
Experience replay is a core ingredient of modern deep reinforcement learning, yet its benefits in policy optimization are poorly understood beyond empirical heuristics. This paper…
Reinforcement Learning Assisted Oxygen Therapy for COVID-19 Patients Under Intensive Care
Hua Zheng, Jiahao Zhu, Wei Xie +1
Patients with severe Coronavirus disease 19 (COVID-19) typically require supplemental oxygen as an essential treatment. We developed a machine learning algorithm, based on a deep R…
Policy Optimization in Dynamic Bayesian Network Hybrid Models of Biomanufacturing Processes
Hua Zheng, Wei Xie, Ilya O. Ryzhov +1
Biopharmaceutical manufacturing is a rapidly growing industry with impact in virtually all branches of medicines. Biomanufacturing processes require close monitoring and control, i…
Personalized Multimorbidity Management for Patients with Type 2 Diabetes Using Reinforcement Learning of Electronic Health Records
Hua Zheng, Ilya O. Ryzhov, Wei Xie +1
Comorbid chronic conditions are common among people with type 2 diabetes. We developed an Artificial Intelligence algorithm, based on Reinforcement Learning (RL), for personalized…
Green Simulation Assisted Reinforcement Learning with Model Risk for Biomanufacturing Learning and Control
Hua Zheng, Wei Xie, Mingbin Ben Feng
Biopharmaceutical manufacturing faces critical challenges, including complexity, high variability, lengthy lead time, and limited historical data and knowledge of the underlying sy…