13 citations · 26 across the 10 of their papers we have counts for
10 papers
Machine Learning-Based Battery State-of-health Prediction for Unmanned Aerial Vehicles Predictive Maintenance
Jiarui Xie, Lingchen Kong, Mohamed Rami Latreche +3
Battery state-of-health (SoH) prediction aims to estimate the remaining capacity by modeling battery degradation through its life cycle. Machine learning (ML)-based SoH models can…
The Economic Dispatch of Power-to-Gas Systems with Deep Reinforcement Learning:Tackling the Challenge of Delayed Rewards with Long-Term Energy Storage
Manuel Sage, Khalil Al Handawi, Yaoyao Fiona Zhao
Power-to-Gas (P2G) technologies gain recognition for enabling the integration of intermittent renewables, such as wind and solar, into electricity grids. However, determining the m…
Redundancy Analysis and Mitigation for Machine Learning-Based Process Monitoring of Additive Manufacturing
Jiarui Xie, Yaoyao Fiona Zhao
The deployment of machine learning (ML)-based process monitoring systems has significantly advanced additive manufacturing (AM) by enabling real-time defect detection, quality asse…
Economic Battery Storage Dispatch with Deep Reinforcement Learning from Rule-Based Demonstrations
Manuel Sage, Martin Staniszewski, Yaoyao Fiona Zhao
The application of deep reinforcement learning algorithms to economic battery dispatch problems has significantly increased recently. However, optimizing battery dispatch over long…
Enhancing Battery Storage Energy Arbitrage with Deep Reinforcement Learning and Time-Series Forecasting
Manuel Sage, Joshua Campbell, Yaoyao Fiona Zhao
Energy arbitrage is one of the most profitable sources of income for battery operators, generating revenues by buying and selling electricity at different prices. Forecasting these…
Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing
Jiarui Xie, Mutahar Safdar, Lequn Chen +2
Various machine learning (ML)-based in-situ monitoring systems have been developed to detect anomalies and defects in laser additive manufacturing (LAM) processes. While multimodal…
Human-artificial intelligence teaming for scientific information extraction from data-driven additive manufacturing research using large language models
Mutahar Safdar, Jiarui Xie, Andrei Mircea +1
Data-driven research in Additive Manufacturing (AM) has gained significant success in recent years. This has led to a plethora of scientific literature to emerge. The knowledge in…
Towards reproducible machine learning-based process monitoring and quality prediction research for additive manufacturing
Jiarui Xie, Mutahar Safdar, Andrei Mircea +5
Machine learning (ML)-based cyber-physical systems (CPSs) have been extensively developed to improve the print quality of additive manufacturing (AM). However, the reproducibility…
Transferability analysis of data-driven additive manufacturing knowledge: a case study between powder bed fusion and directed energy deposition
Mutahar Safdar, Jiarui Xie, Hyunwoong Ko +3
Data-driven research in Additive Manufacturing (AM) has gained significant success in recent years. This has led to a plethora of scientific literature to emerge. The knowledge in…
Fairness- and uncertainty-aware data generation for data-driven design
Jiarui Xie, Chonghui Zhang, Lijun Sun +1
The design dataset is the backbone of data-driven design. Ideally, the dataset should be fairly distributed in both shape and property spaces to efficiently explore the underlying…