Sara is an assistant professor at MIT EECS’ Faculty of AI and Decision Making and CSAIL, and was previously a visiting researcher at Google working on Auto Arborist. She has always loved the natural world, and has seen a growing need for technology-based approaches to conservation and sustainability challenges. Her research focuses on building computer vision methods that enable global-scale environmental and biodiversity monitoring across data modalities, tackling real-world challenges including strong spatiotemporal correlations that lead to domain shift, imperfect data quality, fine-grained categories, and long-tailed distributions.
Lauren is an MIT METEOR postdoctoral associate advised by Profs. Sara Beery and Sherrie Wang (LIDS + MechE). She will be joining the University of Michigan’s School for Environment and Sustainability in Fall of 2026. Her research focuses on developing AI-integrated approaches for monitoring ecosystems at scale.
Lukas is a Fulbright Visiting Scholar at MIT CSAIL. He builds computer vision and machine learning systems for biodiversity monitoring, individual identification of animals, species recognition, species distribution modeling and other real-world problems where reliable AI has to work alongside domain experts.
Jonathan is a postdoctoral fellow supported by the Swiss National Science Foundation. His work focuses on scaling up ecological monitoring in challenging environments such as underwater ecosystems. He is also interested in uses of real-time 3D computer vision for rapid habitat mapping and studying animal behavior from video.
Burak is a postdoctoral associate specializing in the design and deployment of trustworthy, robust machine learning methods for climate, sustainability, and ecology. His work focuses on building diagnostic tools for domain shifts in large-scale deployments and driving scientific discovery to uncover novel ecological insights.
Justin is a PhD student at MIT, advised by Sara Beery and supported by fellowships from MIT EECS and NSF. His research focuses on making computer vision and machine learning systems more deployable and informative for science and decision-making, particularly for environmental and climate applications.
Rupa is a PhD student at MIT CSAIL, advised by Prof. Sara Beery and supported by the MIT Tina Chan Fellowship. Primarily, her research focuses on robust computer vision with remote sensing data and aerial imagery in order to address climate issues such as conservation and biodiversity monitoring.
Elena is an EECS PhD student at MIT advised by Sara Beery & Sherrie Wang and supported by the GEM Fellowship. Her research focuses on designing machine learning systems that make imperfect ecological data actionable, drawing on domain-specific knowledge to turn flawed data into reliable insight.
Antoine is an EECS PhD student at MIT CSAIL advised by Sara Beery and generously supported by the MIT Siddartha Banerjee Fellowship. His current project focuses on integrating ecological expertise in re-identification models for elephants through interpretable and editable architectures.
