{"id":1443,"date":"2025-04-23T16:58:09","date_gmt":"2025-04-23T06:58:09","guid":{"rendered":"https:\/\/wp.csiro.au\/ai4c\/?p=1443"},"modified":"2025-04-23T17:02:40","modified_gmt":"2025-04-23T07:02:40","slug":"kelly-trinh","status":"publish","type":"post","link":"https:\/\/wp.csiro.au\/ai4c\/kelly-trinh\/","title":{"rendered":"Kelly Trinh"},"content":{"rendered":"\r\n

\"\"Dr Kelly Trinh is a Research Scientist at Data61, specialising in machine-learning methodologies for forecasting, spatiotemporal analysis, and uncertainty quantification. During her time at CSIRO, she has contributed to the modelling aspects of internal and external projects across various application domains, including the digital economy, transport, infrastructure, labour markets, agriculture and natural hazards.<\/p>\r\n\r\n\r\n\r\n

Kelly’s work focuses on leveraging data-driven approaches to provide insights into critical decisions in response to environmental and socio-economic challenges. Her current research focuses on developing\/utilising statistical and machine-learning approaches for climate-related prediction and risk assessment, with a particular emphasis on understanding the interactions between natural hazards, environmental systems, and agriculture.<\/p>\r\n","protected":false},"excerpt":{"rendered":"

Dr Kelly Trinh is a Research Scientist at Data61, specialising in machine-learning methodologies for forecasting, spatiotemporal analysis, and uncertainty quantification. 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