Andrew Farnsworth is a Senior Research Associate in the Center for Avian Population Studies at the Cornell Lab of Ornithology. Andrew began birding at age 5 and quickly developed his long-standing fascinations with bird migration. His current research efforts advance the use and application of rapidly expanding technologies to study bird movements across scales including weather surveillance radar, audio and video recording and monitoring tools, citizen science datasets, and machine learning techniques. Andrew received his BS in Natural Resources from Cornell, MS in Zoology from Clemson University, and PhD in Ecology and Evolutionary Biology from Cornell University.
Adriaan Dokter is a Research Associate at the Cornell lab of Ornithology. With a background in physics, his research bridges the disciplines of ecology, computer science, physics, and meteorology, addressing questions about the effects of global change on the distribution and seasonal migration of birds from continental-scale movements of species to fine-scale behavior of individuals flying through the atmosphere. Adriaan uses weather radar networks as well as individual tags to address questions in migration ecology, including when and where birds migrate, when and where birds die within the annual cycle, and how shifting patterns in mortality and recruitment of young birds cause bird abundances to change. He also develops software tools for biologists using weather radar as a tool in their research, including the R-package bioRad for biological analysis of weather radar data. After receiving a Ph.D. at the Institute of Atomic and Molecular Physics in Amsterdam, he studied animal movement during postdoctoral appointments at the Cornell Lab of Ornithology, the Netherlands Institute of Ecology, the University of Amsterdam, and the Netherlands Meteorological Institute.
Kyle is an Assistant Professor at Colorado State University in the Department of Fish, Wildlife, and Conservation Biology. He was a Rose Postdoctoral fellow at the Cornell Lab of Ornithology from 2017-2019. His research, and that of his lab, focuses on the study of bird, bat, and insect migration using a range of tools and approaches, including the use of radar, acoustics, and citizen science data. His work addresses a handful of fundamental questions of migration and its biology, including understanding avian flight strategies, long-term phenological change, population estimates, impacts of artificial light, and migration forecasting. He completed his M.S. with Jeffrey Buler at the University of Delaware and his Ph.D with Jeffrey Kelly at the University of Oklahoma.
Dan Sheldon’s primary research develops algorithms to understand and support decisions about the environment using large data sets. He and his colleagues and students are the primary machine learning research leads for BirdCast. He seeks to answer foundational questions and also to build applications that transform large-scale data resources into scientific knowledge and policy. Some examples of his work include spatial optimization to conserve endangered species, continent-scale modeling of bird migration, and biological interpretation of weather radar data across the US. Methodologically, Dan’s primary interests are machine learning, probabilistic inference, and network modeling. His work has contributed broadly applicable new approaches for reasoning about aggregate data in probabilistic graphical models, and for optimization of diffusion processes in networks.
Julia Wang is a project leader whose primary focus is on developing and coordinating Lights Out campaigns with conservation partners and local stakeholders to facilitate widespread public and governmental adoption of conservation practices. These campaigns integrate BirdCast research to better target which nights migratory birds are most at risk from the harmful effects of artificial night lighting, as well as to quantify intervention effect. Julia completed her B.A. in Government at Cornell University, and is particularly interested in the application of research to solving real world problems, and in behavioral change on both the individual and systemic level.
Benjamin is a Cornell Presidential Postdoctoral Fellow. He completed his graduate research at the University of Oxford studying the evolution and flexibility of avian migration. He enjoys using a range of tools and approaches—from light-level geolocators, to radar, to genomics—to better understand the determinants of migration. Benjamin studied biology and statistics as an undergraduate at Cornell University and has been BirdCasting since 2012.
Heather Wolf is a Web Developer at the Cornell Lab of Ornithology. In addition to BirdCast, she works on other Lab sites including eBird and Birds of the World. Heather holds a MS in Information Science from the University of North Carolina at Chapel Hill and a MS in Computer Science (Software Engineering) from the University of Northwest Florida.
Taylor is a User Interface Designer for the Center for Avian Population Studies at the Cornell Lab. As a UI designer, he shapes the development of new features in their earliest design phases, working with developers and project leaders to decide how features should look and behave. He endeavors to make each facet of these interfaces understandable, easy to use, and enjoyable for birders everywhere. Prior to joining this team, he worked as a Web Cartographer for the National Park Service in Denver, Colorado. When not designing for eBird, Taylor likes to spend his time adding to his modest yet ever-growing life list, sharing his love of map-making with others, and enjoying the great outdoors with his wonderful wife and two children.
Will Morris is design lead for the Center for Avian Population Studies at the Cornell Lab of Ornithology. His primary focus is designing the eBird and Merlin mobile applications and coordinating visual and user interface design across eBird, Merlin, Birds of the World, BirdCast, and other Lab projects. Will has a background in studio art, data visualization, and web development. A late-comer to birding, Will is slowly working on his ID skills and building a life list.
Frank La Sorte is a research ecologist in the Center for Avian Population Studies at the Cornell Lab of Ornithology. His work explores the macroecology, biogeography, and conservation of plants and birds with a special focus on migratory birds and global change.
Steve Kelling’s primary focus is to coordinate a team of ornithologists, project managers, statisticians, application developers, and data managers to develop programs, tools, and analyses to gather, understand, and disseminate information on birds and the environments they inhabit. His responsibilities revolve around four broad topics: the management of eBird, a citizen-science project that gathers millions of bird observations from around the globe; the use of novel digital library strategies to create global communities of interested users centered around primary scientific references; the organization of the rich data resources of the bird-monitoring community and integrating these resources within existing bioinformatic infrastructures; and using unique statistical and computer science strategies to analyze the distribution and abundance of wild bird populations.
Cecilia Nilsson is a postdoc at the Center for Macroecology, Evolution and Climate, Globe Institute, Københavns Universitet. She is a behavioral ecologist, primarily working with radar aeroecology to study flight behavior and animal migration. She worked with the European migration system during a postdoc at the Swiss Ornithological Institute and, most recently, with the American migration system during a postdoc at Cornell Lab of Ornithology. At CMEC she continues her research using large weather radar networks to understand factors influencing the movements of flying animals at continental scales.
Rich Caruana is Senior Principal Researcher at Microsoft Research. Most of his research is in machine learning and data mining, and in the application of these to challenging problems in medical decision making and ecology. Rich has collaborated with Cornell’s Lab of Ornithology on a number of projects, and now serves as an external advisor on BirdCast. Rich is involved in a collaboration with members of the BirdCast Team to develop methods for providing ground truth observations of birds in flight to more accurately measure bird migration and calibrate radar measurements.
Tom Dietterich led the development and application of advanced machine learning algorithms to model bird migration. These algorithms analyzed the data provided by eBird volunteers, weather radar imagery, and weather forecasts to discover migration patterns and understand the factors that affect the speed and direction of bird flight during migration. Dietterich is President-Elect of the Association for the Advancement of Artificial Intelligence.
Jed Irvine brought more than two decades of experience in software engineering to his work supporting a number of projects in the Intelligent Systems group at Oregon State University. Bird migration (especially raptors) has been a lifelong passion for him, and for Birdcast Jed built a web application to support rapid labeling of radar images by experts that was critical for the early advances in BirdCast methodologies to extract bird information from radar data. Jed’s current passion is a small coaching practice he has started, focused on helping graduate students elevate their collaboration skills and work habits. In May of 2020 he launched The Grad Student Coach Podcast.
Garrett is an AI Research Scientist at Invitae, applying machine learning to medical genetic testing. He received his PhD in Computer Science at UMass Amherst, advised by Dr. Daniel Sheldon, where he developed algorithms to help scientists in all fields do their jobs more efficiently and effectively, including helping ornithologists and conservationists to study continent-wide bird migration patterns. His thesis was on machine learning for differential privacy. Prior to UMass, he worked at MIT Lincoln Lab. He received an MEng in Computer Science in 2011 and a B.S. In Applied Physics in 2010, both from Cornell University.
Liping Liu brought expertise in machine learning and probabilistic graphical models to the project as a graduate student under Tom Dietterich at Oregon State University. In previous work with Rebecca Hutchinson, he developed an R package for fitting latent variable models with boosted regression trees. He extended this work to create the Semi-Parametric Latent Process Models required during the first BirdCast NSF award.
Tao Sun studied machine learning and probabilistic graphical models as part of his doctoral research at University of Massachusetts Amherst. He contributed to BirdCast by developing a synthetic data generator for weather-dependent bird migration, and by developing and testing different algorithms for approximate inference in Collective Graphical Models. He also explored scaling inference algorithms to continent-sized problems, as well as other applications and extensions of Collective Graphical Models.
Giles Hooker’s primary focus is on the interface of mathematical models for biological processes and data observed from them. He has particular expertise in using machine learning methods, functional data analysis and nonlinear dynamics. A particular focus of his research is in the interface of data mining with statistics, assessing the statistical evidence for patterns found in data and using machine learning models within more classical statistical modeling frameworks. His work is applied in ecology, epidemiology, evolution and in modeling large-scale bird ecology.
Wesley Hochachka is a senior research associate at Cornell University who has studied many aspects of the ecology and evolutionary biology of birds. Much of his research has revolved around identifying patterns and inferring processes over long time periods or large spatial extents. One of his current focuses is on the use of volunteer-collected (citizen science) data in order to understand the factors that determine where individual species live and why their distributions might change over time. Much of this work is as a member of the team that works on the analyses of data from eBird and the Avian Knowledge Network. The second current focus of his work is in disease ecology, as a member of a long-term collaboration that is studying the relationship between one finch species and a bacterial pathogen that jumped from poultry to these finches and subsequently caused substantial population declines in its new host.
David Nicosia has been a meteorologist with NOAA for over 20 years after receiving his B.S and M.S in Meteorology from Penn State. Dave has studied severe weather and flood events, publishing numerous papers in meteorology. An avid birder for most of his life, David is also a leader for the Lab’s Spring Field Ornithology class and the Broome Naturalist’s Club.
Carley Eschliman was an editorial assistant at the Cornell Lab for the summer of 2018. She pursued majors in Atmospheric Science and Communication in the Cornell College of Agriculture and Life Science. Carley has been interested in weather since she first caught a glimpse of a tornado in her early childhood. She hopes that her studies at Cornell will equip her with skills to better bridge the communication gap between climate scientists and the general public. Through her work at the Cornell Lab, she wishes to encourage a closer partnership between birders and meteorologists, showing each group that there is a lot still left to learn about what is going on in the troposphere.