Laura Melissa Guzman
My preferred name is Melissa. I am originally from Bogotá, Colombia. I am a computational ecologist. My main motivation is to use quantitative and computational tools to learn about patterns and processes in biodiversity to inform conservation actions. I was a Liber Ero Postdoctoral Fellow focusing on estimating changes in pollinator distributions to prioritize areas for conservation. For my work I have was awarded the Early Career Award from the Canadian Society of Ecology and Evolution, and the Young Investigator Award from the American Society of Naturalists.
Jayme Lewthwaite completed a PhD with Dr. Arne Mooers at Simon Fraser University, where her research combined spatial ecology and phylogenetic information to help evaluate the biodiversity impacts of anthropogenic change on Canadian butterfly species. Her postdoc will expand on this work by constructing detailed modern and historical occupancy maps for each of these species in order to prioritize conservation actions. She is currently serving as a member of the Arthropod Species Subcommittee for COSEWIC (the Committee on the Status of Endangered Wildlife in Canada), and loves to chase insects in her spare time.
Austin is a postdoc working with the Natural History Museum of Los Angeles County and the University of Southern California to study California’s insect biodiversity. The California Insect Barcode Initiative is a collaborative effort to sequence “DNA barcodes” of all insect species in California, and Austin will be managing the new collections part of this project. He received a Ph.D. in entomology from the University of California, Riverside where he studied the systematics of ant-parasitizing wasps in the family Eucharitidae and then did a postdoc at the University of Memphis studying the phylogeny of crickets and katydids (Orthoptera: Ensifera). His interests include insect systematics, biodiversity, evolution, and natural history.
Vaughn conducted their doctoral work with Dr. Leslie Ries at Georgetown University focusing on the impacts of climate change on Arctic and boreal butterfly occupancy and morphology. Vaughn's postdoctoral work will leverage deep computer vision to rapidly digitize natural history collection data for the conservation assessment of Southwestern butterflies. They will also be working on developing new statistical tools for understanding the drivers of changes in butterfly occupancy, phenology, and morphology. Vaughn's interests include data science, applications of AI to biodiversity, and international research collaborations.
Yan Yin Jenny Cheung
My preferred name is Jenny. I am working with Dr. Melissa Guzman as a Ph.D. student at the University of Southern California. I completed my MPhil with Dr. Hongbin Liu at the Hong Kong University of Science and Technology. I studied how climate change and nutrient input (such as water pollution) affect the phytoplankton abundance in an urbanized estuarine using machine learning algorithms. From there, I discovered my passion for statistical ecology. For my Ph.D. research at USC, I focus on applying statistical and computational methods to connect ecological theories to biodiversity data. Particularly, I want to advance our knowledge of how ecosystems connect on multiple spatiotemporal scales and how biodiversity could be affected in a changing climate. My interest includes metacommunity theory, food web ecology, satellite remote sensing technology, and data science.
Teagan completed a B.Sc. in Environmental Engineering from the University of Virginia in 2022. There, he worked with Dr. Lawrence Band to improve methods for estimating land cover and land use change effects on biogeochemical cycles in multi-use landscapes. As a PhD student in the Ecological Data Science Lab, Teagan is now interested in the role human modified landscapes play in shaping our planets biodiversity. He is using a theory-based approach to estimate how patterns of habitat loss can impact an organism's ability to adapt to other pressures, such as a warming environment. He also employs a variety of modeling techniques to identify threats to insect populations and their responses across space and time.