Mayar is a Research Fellow at SCL,
where he leads interdisciplinary research on
how complex systems can remain stable when resources are
scarce and risks are high.
He received an MEng degree in Civil and Environmental Engineering from
Imperial College London in 2024.
Publications
Ergodicity-Informed Adaptive Sensing for Energy-Constrained Urban IoT Networks
IEEE Internet of Things. 2025. DOI: 10.1109/JIOT.2025.3621047.Seismic assessment of unreinforced masonry façades from images using macroelement-based modeling
Communications Engineering. 2025. DOI: 10.1038/s44172-025-00487-2.Drive-by environmental sensing strategy to reach optimal and continuous spatio-temporal coverage using local transit network
Transportation Research Record. 2024. DOI: 10.1177/0361198124124705.
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Featured
Upstream of the Fire at the MIT AI Student Forum
At the inaugural 2026 MIT AI Student Forum, hosted at the Schwarzman College of Computing, Mayar Ariss presented “Upstream of the Fire” in a research talk to industry partners. The forum gives student researchers a venue to share their work with companies across generative AI and AI hardware.
MCSC Spotlights AI for Wildfire-Resilient Water Networks
The 2026 MIT Climate & Sustainability Consortium (MCSC) Member Meetings included an AI for Sustainability Session, where “AI-Driven Water Network Optimization of Water Supply Networks for Wildfire Resilience” was selected to be presented. The session was hosted at the MIT Museum.
Generative AI for Smarter Wildfire Water Response
When wildfires strike, cities must adapt in real time. With support from OpenAI, Mayar Ariss received the MIT Generative AI Impact Consortium (MGAIC) Award for leading research that helps guide the operators of water networks during fires. The learned controller is trained inside a hydraulic simulation and then connected to the real world through an unusual data source, emergency radio chatter, parsed in real time by a language model so it can flag fire emergencies before pressure drops show up on any sensor.
Earthquakes can destroy buildings. AI may help predict which ones
Street-level photos can hint at how a building might fare in an earthquake. Ariss and co-authors developed an AI method that turns those images into simplified structural models and simulates their seismic response, offering a faster and lower-cost alternative to conventional surveys.
Driving cleaner cities by using public transport to measure pollution in real-time
Could a city’s buses and trams double as environmental monitors? Mayar Ariss led a study in Amsterdam showing that transit vehicles, fitted with low-cost sensors, can track air pollution, noise, and temperature as they run their everyday routes, an idea built to work in other cities too.
Imperial student develops flat-pack homes for earthquake-stricken regions
After the 2023 earthquakes in Morocco, Syria, and Turkey, Mayar Ariss founded the GAMMA relief project at Imperial College London. Its modular timber homes ship flat and go up in a few days, like IKEA furniture, giving displaced families a durable, solar-powered alternative to the emergency tents that too often become permanent.
Clocking Emissions
A small fraction of a city’s transit fleet may be enough to monitor its environment in real time. At MIT Senseable City Lab, Ariss and colleagues show that sensor-equipped buses and trams in Amsterdam could track air pollution, noise, and temperature citywide, using vehicles that already run every day.
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