People

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.

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. More broadly, he is interesting in building models to decode animal communication. Beyond research, Antoine strongly believes in the importance science communication, through content creation and documentary film-making.

Eddie is a PhD student at MIT EECS advised by Sara Beery and supported by the MIT Presidential Fellowship and NSF GRFP. He is interested in bringing automation to scientific discovery, including by building systems and agents that can autonomously carry out scientific data collection, data science, and analysis.

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, decision-ready insight.

Julia is an EECS PhD student at MIT CSAIL advised by Sara Beery and generously supported by the MIT Andrew and Erna Viterbi Graduate Fellowship. Her current project focuses on investigating how synthetic data can be used to enhance real-world vision models. More broadly, she is interested in developing robust computer vision algorithms for practical use across various domains, particularly in ecology and biodiversity monitoring.

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.

Neha is a PhD student at MIT CSAIL, advised by Prof. Sara Beery and supported by the MIT Jameel Clinic Fellowship and the NSF GRFP. She is interested in building reliable machine learning systems, balancing tradeoffs of performance, efficiency, privacy, and robustness.

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. She is interested in working at the intersection between research and policy, designing and deploying real-world ecological tools.

Timm is a PhD student at MIT CSAIL and advised by Sara Beery. He is interested in multi-modal environmental and biodiversity monitoring, as well as 3D reconstruction of natural scenes to enable better animal population density estimation.