Ecology

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Augmenting citizen science with computer vision for fish monitoring

Abdul Latif Jameel Water and Food Systems Lab (J-WAFS), ai, AI (Artificial Intelligence), 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

Each spring, river herring populations migrate from Massachusetts coastal waters to begin their annual journey up rivers and streams to freshwater spawning habitat. River herring have faced severe population declines over the past several decades, and their migration is extensively monitored across the region, primarily through traditional visual counting and volunteer-based programs. Monitoring fish movement and understanding […]

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

ai, AI (Artificial Intelligence), 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

Joseph Paradiso thinks that the most engaging research questions usually span disciplines. Paradiso was trained as a physicist and completed his PhD in experimental high-energy physics at MIT in 1981. His father was a photographer and filmmaker working at MIT, MIT Lincoln Laboratory, and the MITRE Corporation, so he grew up in a house where artists, scientists,

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

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

A recent study from Oregon State University estimated that more than 3,500 animal species are at risk of extinction because of factors including habitat alterations, natural resources being overexploited, and climate change.To better understand these changes and protect vulnerable wildlife, conservationists like MIT PhD student and Computer Science and Artificial Intelligence Laboratory (CSAIL) researcher Justin Kay

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