Welcome to the BeeryLab at MIT!
Based in MIT’s Department of Electrical Engineering and Computer Science, the Computer Science and AI Laboratory, and the Schwarzmann College of Computing, we combine expertise in computer vision, deep learning, and ecology to develop methods that enable global-scale environmental and biodiversity monitoring across diverse ecological data modalities. To achieve this, our research tackles real-world challenges for AI including heterogeneous multimodal data, spatial intelligence, strong spatiotemporal correlations that lead to distribution shift, imperfect data quality, fine-grained categories, and long-tailed distributions. We build methods that are robust, efficient, and deployable by design, and our models are used globally by scientific collaborators, governmental agencies, and non-governmental organizations.
Recent Publications
INQUIRE-Search: A Framework for Interactive Discovery in Large-Scale Biodiversity Databasesin arXivEdward Vendrow * , Julia Chae * , Rupa Kurinchi-Vendhan * , Isaac Eckert , Jazlynn Hall , Marta Jarzyna , Reymond Miyajima , Ruth Oliver , Laura Pollock , Lauren Schrack , Scott Yanco , Oisin Mac Aodha , Sara Beery- * Equal contribution
Consensus-Driven Active Model Selection in ICCV 2025 (Highlight)
Align and Distill: Unifying and Improving Domain Adaptive Object Detectionin TMLR 2025Justin Kay , Timm Haucke , Suzanne Stathatos , Siqi Deng , Erik Young , Pietro Perona , Sara Beery † , Grant Van Horn †- † Equal advising