Civil and environmental engineering
Civil and environmental engineering

Civil and environmental engineering

Artificial Intelligence Civil and environmental engineering Cleaner industry Concrete Concrete Sustainability Hub DMSE Emissions Environment Infrastructure Materials science and engineering Research School of Engineering Sustainability Technology and society

AI stirs up the recipe for concrete in MIT study

With demand for cement alternatives rising, an MIT team uses machine learning to hunt for new ingredients across the scientific literature.

Algorithms Artificial Intelligence Autonomous vehicles Civil and environmental engineering Computer science and technology Data Emissions IDSS Laboratory for Information and Decision Systems (LIDS) Logistics machine learning MIT Schwarzman College of Computing Research School of Engineering Sustainability Traffic management Transportation

New tool evaluates progress in reinforcement learning

“IntersectionZoo,” a benchmarking tool, uses a real-world traffic problem to test progress in deep reinforcement learning algorithms.

Algorithms Artificial Intelligence Civil and environmental engineering IDSS Laboratory for Information and Decision Systems (LIDS) MIT Schwarzman College of Computing Networks Research School of Engineering Systems design

Designing a new way to optimize complex coordinated systems

Using diagrams to represent interactions in multipart systems can provide a faster way to design software improvements.

Algorithms Artificial Intelligence Civil and environmental engineering Computer science and technology IDSS Laboratory for Information and Decision Systems (LIDS) Logistics machine learning MIT Schwarzman College of Computing Research School of Engineering

A faster way to solve complex planning problems

By eliminating redundant computations, a new data-driven method can streamline processes like scheduling trains, routing delivery drivers, or assigning airline crews.

Artificial Intelligence Civil and environmental engineering Climate change Collaboration Emissions IDSS International initiatives Mechanical engineering MIT Schwarzman College of Computing MIT Sea Grant Nuclear science and engineering Oceanography and ocean engineering Research School of Engineering Supply chains Technology and policy Transportation

MIT Maritime Consortium sets sail

A new international collaboration unites MIT and maritime industry leaders to develop nuclear propulsion technologies, alternative fuels, data-powered strategies for operation, and more.

Artificial Intelligence Civil and environmental engineering Department of Defense (DoD) Graduate, postdoctoral machine learning School of Engineering Security studies and military Students

Making airfield assessments automatic, remote, and safe

U.S. Air Force engineer and PhD student Randall Pietersen is using AI and next-generation imaging technology to detect pavement damage and unexploded munitions.

Artificial Intelligence Awards, honors and fellowships Civil and environmental engineering Computer modeling Education, teaching, academics Faculty K-12 education Mechanical engineering MIT Schwarzman College of Computing School of Engineering

Markus Buehler receives 2025 Washington Award

Materials scientist is honored for his academic leadership and innovative research that bridge engineering and nature.

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Puzzling out climate change

Accenture Fellow Shreyaa Raghavan applies machine learning and optimization methods to explore ways to reduce transportation sector emissions.

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Need a research hypothesis? Ask AI.

MIT engineers developed AI frameworks to identify evidence-driven hypotheses that could advance biologically inspired materials.

Algorithms Artificial Intelligence Civil and environmental engineering Computer science and technology IDSS Laboratory for Information and Decision Systems (LIDS) machine learning MIT Schwarzman College of Computing National Science Foundation (NSF) Research School of Engineering

MIT researchers develop an efficient way to train more reliable AI agents

The technique could make AI systems better at complex tasks that involve variability.