Ecology
Ecology

Ecology

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) Animals Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Ecology Electrical engineering and computer science (EECS) Environment machine learning Mechanical engineering MIT Schwarzman College of Computing MIT Sea Grant National Science Foundation (NSF) Oceanography and ocean engineering Research School of Engineering Undergraduate Research Opportunities Program (UROP) Video Volunteering, outreach, public service Water

Augmenting citizen science with computer vision for fish monitoring

MIT Sea Grant works with the Woodwell Climate Research Center and other collaborators to demonstrate a deep learning-based system for fish monitoring.

Alumni/ae Artificial Intelligence Digital technology Ecology Electronics Environment Faculty health Internet Of Things machine learning Media Lab Medicine Physics Profile School of Architecture and Planning School of Science sensors Space Wearable sensors Wireless

How Joseph Paradiso’s sensing innovations bridge the arts, medicine, and ecology

From early motion-sensing platforms to environmental monitoring, the professor and head of the Program in Media Arts and Sciences has turned decades of cross-disciplinary research into real-world impact.

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) Algorithms Animals Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Ecology Electrical engineering and computer science (EECS) Environment Graduate, postdoctoral Interview machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Pollution Research School of Engineering Students Sustainability

3 Questions: How AI is helping us monitor and support vulnerable ecosystems

MIT PhD student and CSAIL researcher Justin Kay describes his work combining AI and computer vision systems to monitor the ecosystems that support our planet.

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS) Algorithms Animals Artificial Intelligence computer-vision Data Ecology Electrical engineering and computer science (EECS) Environment Faculty Food machine learning Research School of Engineering Sustainability

Streamlining data collection for improved salmon population management

Assistant Professor Sara Beery is using automation to improve monitoring of migrating salmon in the Pacific Northwest.

Algorithms Animals Artificial Intelligence Computer Science and Artificial Intelligence Laboratory (CSAIL) Computer science and technology computer-vision Data Ecology Electrical engineering and computer science (EECS) machine learning MIT Schwarzman College of Computing Research School of Engineering

Ecologists find computer vision models’ blind spots in retrieving wildlife images

Biodiversity researchers tested vision systems on how well they could retrieve relevant nature images. More advanced models performed well on simple queries but struggled with more research-specific prompts.