Session 4: AI for Forest Science: From Data to Governance

Brief Introduction

Meeting Agenda：

Speaker Biography：

Dr. Liyong Fu is a full professor at the Chinese Academy of Forestry (CAF). Prof. Fu was selected as a Young Leading Talent (2019) and subsequently as a Leading Talent (2025) under China’s National High-Level Talent Special Support Program (10,000 Talents Program). He received the China Youth Science and Technology Award and the State Council Special Government Allowance, one of China’s highest honors for distinguished experts. He has been ranked among the world’s top 2% of scientists in the field of artificial intelligence for forestry for three consecutive years (2023-2025). Prof. Fu currently serves as Director of the Department of Science and Technology at CAF, Chief Scientist of the Forestry Statistics and Biomathematics Research Group at CAF, and Chair of the High-Tech Committee on UAV Remote Sensing and Satellite Applications of the China Forestry Engineering Construction Association. His research focuses on advanced forest measurement theory, UAV remote sensing, and AI-based image recognition. He has made significant contributions to major national initiatives and forestry priorities, including science and technology support for the Beijing Winter Olympics, the Three-North Shelterbelt Program, and integrated monitoring of forests, grasslands, wetlands, and deserts. He has published over 230 papers, holds 27 authorized patents and 26 software copyrights, has led the development of one national standard, and has authored two books. He serves on the IUFRO Executive Board, coordinates the IUFRO Task Force “AI for Forest Science” and serves as Deputy Coordinator of the Continuous Forest Inventory Working Party under IUFRO Division 4.2.0. He is also an editorial board member of 12 leading journals in China and abroad, including Forestry and Scientia Silvae Sinicae.

Dr. Cao Lin is a Professor at Nanjing Forestry University and the academic lead for Smart Forestry, specializing in forestry remote sensing, tree phenomics, and biodiversity monitoring. He has been selected for a national high-level talent program and recognized as a National Leading Talent in Forestry and Grassland Science and Technology Innovation and a Young and Middle-aged Academic Leader under the Jiangsu University “Qinglan Project”. He serves as Chair of the Forest Phenotyping Working Group of the International Plant Phenotyping Network (IPPN), Director of the preparatory development site for the National Key Laboratory of Smart Forestry, and an editorial board member of ISPRS Journal of Photogrammetry and Remote Sensing, among other academic appointments. He has led four projects funded by the National Natural Science Foundation of China and two projects under the National Key R&D Program of China, published more than 130 peer-reviewed journal articles, and holds over 20 authorized Chinese invention patents. His major honors include the Second Prize of the National Science and Technology Progress Award, the First Prize of the Ministry of Education Science and Technology Progress Award, the First Prize of the Liang Xi Forestry Science and Technology Award for Natural Sciences, and the Jiangsu Youth Science and Technology Award.

Dr. Xiaodi Zhao is a full Professor at the Research Institute of Forestry Policy and Information, Chinese Academy of Forestry (CAF), a member of the China Democratic League (CDL), and a member of the Youth Federation of Central and State Organs. She is a recipient of the “China Forestry and Grassland Youth Award” and has been selected seven times for international talent development programs, including the IUFRO Special Programme for Development of Capacity in Young Scientists (IUFRO-SPDC) and the German Federal “Global Forest Expert” (BMEL-DF.V.) Programme. Her research focuses on innovations in quantitative modeling methods for natural resource assessment. She has published more than 60 papers as first or corresponding author and has been consecutively listed among the “Top 5% Highly Cited Researchers” by CNKI (2024–2025). She has authored two monographs, holds two authorized international invention patents, four software copyrights, and has contributed to the development of one national standard. Her research achievements have received 23 awards at provincial, ministerial, and national levels, including the First Prize of the National Geographic Information Science and Technology Progress Award. Dr. Zhao serves as Deputy Coordinator of the IUFRO Task Force “AI for Forest Science,” Deputy Coordinator of the IUFRO Working Party on Precision Forest Measurement Methods (S4.01.03), and Deputy Coordinator of the IUFRO Working Party on Ecological Economics (S9.04.03). She is also Associate Editor of Trees, Forests and People (Q1 in Forestry) and serves as an editorial board member or guest editor for 11 SCI journals.

Prof. Thomas A. M. Pugh is Senior Lecturer in Global Carbon Cycle Modelling at Lund University, Sweden, and Reader in Biosphere–Atmosphere Exchange at the University of Birmingham, UK. His research focuses on global change ecology, forest carbon cycling, terrestrial biosphere modelling, and interactions between forests and the atmosphere. He is internationally recognized for his contributions to understanding forest carbon sinks, forest disturbances, tree mortality, and the development of dynamic global vegetation models, particularly LPJ-GUESS. Prof. Pugh has been named a Clarivate Highly Cited Researcher for three consecutive years (2023–2025). He has received both a prestigious European Research Council (ERC) Starting Grant and an ERC Advanced Grant, reflecting sustained international leadership in forest and Earth system science. He currently co-leads the International Tree Mortality Network, serves on the international steering committee of LPJ-GUESS, and is Co-lead of the IUFRO Task Force on AI in Forest Science. He has authored more than 120 peer-reviewed publications, with over 20,000 citations on Google Scholar and an H-index of 59.

Artan Sheshmani is a Professor at the Beijing Institute of Mathematical Sciences and Applications (BIMSA), specializing in algebraic geometry, enumerative geometry and derived geometry. His research focuses on Gromov–Witten theory, Donaldson–Thomas theory, Calabi–Yau geometry and derived algebraic geometry, with particular emphasis on the geometry of moduli spaces of sheaves and curves on Calabi–Yau spaces and their connections to the mathematics of string theory. His work explores dualities and structural properties of moduli spaces over complex varieties of dimensions two, three and four, drawing on methods from derived geometry and geometric representation theory. His recent research interests also include super algebraic geometry and birational geometry, as well as their connections with enumerative algebraic geometry and moduli theory. Prior to joining BIMSA, he spent seven years as senior personnel in the Simons Collaboration on Homological Mirror Symmetry at the Harvard University Center of Mathematical Sciences and Applications (CMSA) and served as an Associate Professor of Mathematics at Aarhus University in Denmark.

Prof Michael Watt is a Principal Scientist and Portfolio Leader for Digital Forests at Scion, part of New Zealand’s Bioeconomy Science Institute. He is internationally recognised for applying artificial intelligence, machine learning and remote sensing to improve forest measurement, management and resilience. His research spans national-scale mapping of forest extent, age, volume, biomass, carbon and future wood flows; individual-tree detection and characterisation using LiDAR data; and the early prediction of forest disease and wind risk. He has authored more than 230 peer-reviewed publications and leads major multidisciplinary programmes that translate advances in sensing and AI into operational tools for industry and government. Michael is Editor-in-Chief of Current Forestry Reports, co-leads New Zealand’s forest-industry Remote Sensing Cluster, and is a Fellow of the New Zealand Institute of Forestry. His contributions have been recognised through several national awards, including the 2022 Science New Zealand Lifetime Achievement Award.

Dr. Francisco Rivas Fuenzalida is a Research Associate at the Forest Advanced Computing and Artificial Intelligence (FACAI) Lab in the United States, and the Founder and Director of Museo Bioacústico, Chile. He is an emerging researcher in forest artificial intelligence and ecoacoustics, integrating AI, bioacoustics, remote sensing, and ecological informatics to advance forest health assessment and biodiversity monitoring. His research involves global forest data analysis, ecological soundscape monitoring, and intelligent biodiversity assessment, including contributions to the Science-i network and the Global Forest Biodiversity Initiative. His development of bioacoustic tools such as Rthoptera has advanced acoustic approaches for insect monitoring and ecosystem assessment.

Prof. Wensheng Huang is Associate Dean of the Faculty of Construction and Environment at The Hong Kong Polytechnic University. His research focuses on urban environmental remote sensing. He has published more than 300 journal papers, received over 11,000 citations, authored seven books, and achieved an H-index of 61. Prof. Huang has led and participated in numerous major research projects, including Hong Kong Research Grants Council Collaborative Research Fund (RGC CRF) projects, General Research Fund (RGC GRF) projects, Environment and Conservation Fund (ECF) projects, the Jockey Club Smart City Tree Management Programme, and projects supported by the State Key Laboratory of Coastal Urban Climate Resilience at The Hong Kong Polytechnic University, with total research funding approaching HKD 100 million. His research achievements have been recognized by international awards, including the Gold Medal (2021) and Silver Medal (2022) at the Geneva International Exhibition of Inventions and the 2021 Smart 50 Awards. He also serves as Founding Council Member and Vice President of the Atmospheric Environment Remote Sensing Society (AERSS), reviewer for the Hong Kong Research Grants Council General Research Fund, assessment panel member for the Enterprise Support Scheme under the Innovation and Technology Fund of the Innovation and Technology Commission of the Hong Kong SAR Government, and unofficial member of the Urban Forestry Advisory Panel of the Development Bureau of the Hong Kong SAR Government.

Dr Cong Xu is a Senior Lecturer in Geospatial Technologies at the School of Forestry, University of Canterbury, New Zealand, and Co-Director of the Forest Observation with Remote Sensing Technologies (FOReST) research group. Her research combines LiDAR, UAV and satellite remote sensing with machine learning and AI for forest mapping and monitoring, including species classification, forest health and disturbance detection, and the estimation of forest structure, biomass and carbon. She is particularly interested in translating advances in AI and geospatial technologies into practical tools for more efficient, accurate and scalable forest monitoring and management. Vega also serves as Secretary of the New Zealand–China Society of Science, Technology and Education, where she helps strengthen connections between researchers in New Zealand and China and supports research collaboration across a range of disciplines.