Harnessing AI for Forest Ecology: Tracking Migration and Biodiversity with Advanced Computing
Jingjing Liang, Purdue University
https://science-i.org/jingjingliang/?...
Meet: https://meet.google.com/niy-gtpk-sro
Talk Details: https://sites.google.com/modelingtalk...
Join group to receive calendar invite: https://groups.google.com/a/modelingt...
Abstract:
Artificial Intelligence (AI) is revolutionizing the study of forest ecosystems, enabling researchers to analyze vast amounts of biodiversity and environmental data with unprecedented precision. This presentation explores how AI-driven methodologies, including machine learning and advanced computing, are transforming forest migration research. By leveraging global datasets and computational power, we uncover patterns of forest shifts, assess biodiversity changes, and predict future ecological trends. The integration of AI into forestry science not only enhances conservation efforts but also provides valuable insights for policymakers, industries, and communities reliant on forest ecosystems. This talk will highlight key findings from global research initiatives, such as the Forest Advanced Computing and Artificial Intelligence Laboratory (FACAI) and Science-i, demonstrating AI’s critical role in understanding and managing the dynamic nature of our forests in the face of environmental change.
Bio:
Dr. Jingjing Liang is a globally recognized leader in quantitative forest ecology, AI-driven environmental research, and international scientific collaboration. He is currently an Associate Professor at Purdue University and an International Consultant at FAO, with over 20 years of expertise in sustainable forest management, biodiversity conservation, and AI-enhanced ecosystem monitoring. As the Founder of Science-i and Coordinator of the Global Forest Biodiversity Initiative (GFBI), he leads a network of 500+ researchers across 55 countries, driving global collaboration in big data forestry and biodiversity science.
Dr. Liang’s research is widely published, with 93 articles in top-tier journals such as Science, Nature, and PNAS, accumulating 6,233 citations (h-index: 38, i10-index: 71). His work informs global forest policy and conservation strategies, securing over $6 million in research funding ($2.7 million as PI). At FAO, his contributions to AIM4Forests and For-Growth projects of the United Nations advance forest growth monitoring and carbon quantification, playing a key role in climate solutions.
A dedicated mentor and advocate for inclusive science, AI-driven forestry, and climate resilience, Dr. Liang has supported 2,878+ researchers worldwide. He also serves on the Forests Remaining Forests Committee, shaping the future of REDD+ crediting by developing a framework to recognize carbon removals from forests that remain forests—an area historically excluded due to monitoring challenges. His expertise directly influences the next iteration of the global carbon crediting standard, ensuring it fully accounts for the potential of forest-based carbon sequestration in climate mitigation efforts.
#modeling #simulation #climatechange #ecology #biodiversity #foodweb #ecological #habitats #forests #ai #ml #environment #publicpolicy #deforestation