Rongyun Tang Source Confirmed

OverviewAI-generated summary

Rongyun Tang's research interests lie in the intersection of environmental science, machine learning, and supply chain management. Tang has investigated the interannual variability and climatic sensitivity of global wildfire activity, utilizing ensemble machine learning and satellite observations to model and attribute fire occurrences. Further work has focused on quantifying wildfire drivers and predictability in boreal peatlands using machine learning frameworks, specifically within the TeFire v1.0 model. Additionally, Tang has explored the effects of heatwave events on hydrological processes in the contiguous United States. In the realm of supply chain and economics, Tang has developed manufacturer decision-making models that incorporate carbon emission permits, repurchase strategies, and capital constraints, as well as examining carbon trading mechanisms and low-carbon e-commerce supply chains for sustainable development. Research has also addressed decision-making and coordination in e-commerce supply chains under conditions of logistics outsourcing and altruistic preferences.

Metrics

• h-index: 10
• Publications: 18
• Citations: 387