I am an ecologist interested in understanding the causes and consequences of biodiversity change at scales ranging from individual organisms to the entire biosphere. I develop data-model synthesis frameworks that integrate remote sensing (e.g., LiDAR, hyperspectral imaging), field sampling, and ecological monitoring networks with Bayesian hierarchical models and Earth System models. I predict how remotely sensed habitats and climate change interact to drive biodiversity shifts, while also quantifying the feedbacks of biodiversity changes on carbon and water exchanges between land and atmosphere. Additionally, I study global forest regeneration potential and its critical role in shaping food web dynamics.

Prior to joining Duke University, I served as a tenure-track assistant professor at the Department of Ecosystem Science and Management at the Pennsylvania State University. I conducted postdoctral research with Dr. Jim Clark and Dr. Jennifer Swenson at the Nicholas School of the Environment. For my doctoral research, I worked with Drs. Conghe Song, Jim Clark, Erika Wise, Diego Riveros-Iregui, and Allen Hurlbert to understand how vegetation phenology is influenced by climate change, extreme weather events, and urbanization.

Dr. Zhuohong Li is a postdoctoral researcher specializing in deep learning (GeoAI) and Earth observation (AI4EO). His research in computer vision has been recognized with multiple international honors, including a CVPR 2024 Highlights selection and first place in the CVPR OpenEarthMap Challenge. Zhuohong also led the development of SinoLC-1, the first 1-meter resolution national land-cover map of China. This dataset was recognized as an ESI Highly Cited Paper and named the No. 1 Most Valuable Dataset in the 2023 China Top 10 Remote Sensing Events. Dr. Li received his B.Eng. in Communication Engineering and Ph.D. in Remote Sensing from the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS) at Wuhan University, where he worked under the mentorship of Professors Hongyan Zhang, Wei He, and Liangpei Zhang. At Duke, Zhuohong is advancing the development of digital twins for urban and forest environments in the United States and is leading the lab’s efforts in applying GeoAI to ecological research.

Dr. Yu Shen is a postdoctoral researcher with expertise in quantifying ecosystem dynamics across forest and cropland systems using multi-source remote sensing, time series analysis, and deep learning. His work focuses on integrating data from a wide range of satellite and airborne sensors, including Sentinel-2, Landsat, VIIRS, MODIS, GOES, and PlanetScope, to monitor land surface processes at multiple spatial and temporal scales. He earned his Ph.D. and conducted a one-year postdoctoral research under the mentorship of Dr. Xiaoyang Zhang, a leading expert in land surface phenology and fire emissions, and Dr. Hankui Zhang, a member of the Landsat Science Team and a specialist in deep learning for remote sensing applications. At Duke, Yu will advance the understanding of interactions between vegetation and environmental stressors, such as fire and disturbance, particularly in dryland and forest ecosystems facing compounded climate extremes.

Hanshi is a Ph.D. student in the University Program in Ecology (UPE) at Duke University. Before moving to Duke, she was a Ph.D. student in the Intercollege Graduate Degree Program (IGDP) in Ecology at Penn State. Her research focuses on how climate warming and habitat change interact to shape ecosystem dynamics in both natural forests and human-managed landscapes. She also examines the ecological impacts of restoration practices in Sub-Saharan Africa, with an emphasis on how these interventions influence ecosystem dyanmics and the provision of ecosystem services. She worked with Dr. Weiqiang Chen and Dr. Hua Cai at the Institute of Urban Environment at Chinese Academy of Sciences from 2021 to 2023 before joining the lab.

Brandt Geist is a Ph.D. student in the Environment program at the Nicholas School of the Environment at Duke University. He previously earned his M.S. in Earth and Environmental Sciences at Vanderbilt University, where he worked with Dr. Lin Meng on research involving urban ecology, remote sensing, and urban planning. A recipient of the National Science Foundation Graduate Research Fellowship Program (NSF GRFP), Brandt’s work at Duke will focus on leveraging multi-sensor remote sensing and ecological big data to examine how anthropogenic activities influence ecological processes in urbanized regions. His research efforts aim to understand the spatial and temporal dynamics of vegetation, biodiversity, and ecosystem functioning to inform sustainable land management and urban design.

Rongfei is a Ph.D. student in the University Program in Ecology (UPE) at Duke University. She studies responses of biodiversity to urbanization and climate warming across scales in the Couple Human And Nature Systems (CHANS). She is interested in applying integrated tools, like LiDAR, ecoinformatics, causal inference and ecological modelling to disentangle the underlying complex mechanisms to inform conservation practices. Before joinning Duke, she worked with Dr. Ruishan Chen at Shanghai Jiao Tong University to develope both theoretical and applied models in understanding social and ecological functions in urban habitat gardens using remote sensing, camera traps, and citizen science data.

Yu Wei is an Environment Ph.D. student in the Nicholas School of the Environment at Duke university. Prior to joining Duke, she was a Ph.D. student in the Department of Ecosystem Science and Management at Penn State. She studies structural and spectral diversity in the terrestrial ecosystems using combined LiDAR and hyperspectral remote sensing across different scales. She is also interested in applying deep learning and other advanced computing models to understand species composition under global change. She has a very strong background in remote sensing and worked with Dr. Mi Wang at the State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing (LIESMARS) at Wuhan University.

Alexis Fox is an undergraduate student at Duke University, Class of 2028. Alexis worked at UVA’s Biocomplexity Institute on research intersecting information theroy and generative AI. As a high school student, Alexis completed a draft that is currently under review for AAAI. The manuscript focused on analyzing current generative model metrics for output quality and proposing a novel metric differentiating inter- and intra-class diversity. She will work on the deep learning project that focused on fusing airborne and terrestrial laser scanning to facilitate the mapping of biodiversity in the eastern forests.

Ivy Geng is an undergraduate student at Duke University, Class of 2028. Ivy plans to double major in Earth and Climate Science and Public Policy. She worked at Tsinghua University as a high school research assistant, where she contributed to projects on microplastic runoff and soil remediation following heavy metal contamination. Ivy also independently designed and conducted environmental experiments, resulting in multiple first-author publications in peer-reviewed journals. Her academic interests lie in environmental sustainability, pollution control, and climate adaptation, with a strong commitment to integrating scientific research with practical, community-based solutions.

Sophie Mao is an undergraduate student at Duke University, Class of 2028. She has conducted research at University of North Carolina Wilmington on Woody Plant Encroachment, which involved studying LiDAR data to predict how this would continue in drylands in Arizona. Furthermore, she is also part of the NASA SEES program where her team has conducted research on using the Gravity Recovery and Climate Experiment Follow-on (GRACE-FO) data to build a model to predict how sea and ice levels would progress. At Duke, Sophie is part of the climate$+$ team that aims to build forest digital twins in eastern U.S. using deep learning and remote sensing data.

Max Xiong is an undergraduate student at Duke University, Class of 2028. Max worked at Rutgers Univerisity flew a DJI phantom 4 drone over a corn farm in upstate New York. They use YOLO and Mask RCNN and identified harmful weeds within the cornfield, the health conditions of the corn, and a total count for how many corn crops. Max ranked top 3% at the united States of America Computing Olympiad (USACO) and had a first-author paper in IEEE Xplore on multi-spectral drone imagery and deep learning for corn assessment.