4 citations · 4 across the 8 of their papers we have counts for
10 papers
PhyMamba: Physics-Modulated Mamba for Robust Battery Health Prognostics
Sara Sameer, Yunyi Zhao, Wei Zhang +4
Battery health prognostics is a core function in battery management systems (BMSs), yet long-horizon health forecasting from BMS signals remains challenging due to operating-condit…
Label-Free Finite-Volume-Residual Training of Attention Graph Neural Networks for Coupled Thermo-Fluid Fields
Tianyu Li, Zhiwei Cao, Qingang Zhang +3
Neural surrogates are widely used in scientific machine learning for fast prediction of three-dimensional (3D) thermo-fluid fields. However, generating training data using conventi…
BatteryLake: Agentic, Physics-Grounded Curation of Heterogeneous Battery Aging Data and Benchmarking
Tianwen Zhu, Hao Wang, Yonggang Wen
Public battery aging datasets are a critical asset for advanced health management, but their practical use is often limited by inconsistent formats, unclear schemas, and metadata s…
Dual-Loop Control in DCVerse: Advancing Reliable Deployment of AI in Data Centers via Digital Twins
Qingang Zhang, Yuejun Yan, Guangyu Wu +4
The growing scale and complexity of modern data centers present major challenges in balancing energy efficiency with outage risk. Although Deep Reinforcement Learning (DRL) shows s…
DCoPilot: Generative AI-Empowered Policy Adaptation for Dynamic Data Center Operations
Minghao Li, Ruihang Wang, Rui Tan +1
Modern data centers (DCs) hosting artificial intelligence (AI)-dedicated devices operate at high power densities with rapidly varying workloads, making minute-level adaptation esse…
Phythesis: Physics-Guided Evolutionary Scene Synthesis for Energy-Efficient Data Center Design via LLMs
Minghao LI, Ruihang Wang, Rui Tan +1
Data center (DC) infrastructure serves as the backbone to support the escalating demand for computing capacity. Traditional design methodologies that blend human expertise with spe…