Machine learning and AI

In a world of increasingly complex challenges, our experts are using machine learning and artificial intelligence technologies as integral tools in nearly every area of mechanical engineering.

People

Learn who in Mechanical Engineering is working in maching learning and artifical intelligence.

Machine learning and AI

  • People running a race around a track

    Human health

    Machine learning can help us to improve human health in many ways, like predicting and preventing musculoskeletal injuries, personalizing rehabilitation, and developing antibodies to thwart quickly-mutating pathogens.

    It can also help us to enhance the analysis of medical imaging, model the complex geometry of neurons, design synthetic biological systems, and provide a patient's vital signs to a medical team before arriving at the hospital. Our mechanical engineers bring their unique expertise to these biomedical challenges.

    Faculty involved: Jonathan Cagan, Amir Barati Farimani, Eni Halilaj, Philip LeDuc, Conrad Tucker, Jessica Zhang

  • glass flash with pipettes

    Material discovery for energy applications

    Safer, more robust batteries... new ceramic polymer hybrid materials that require less energy to produce... heat transport prediction and improved energy conversion... these are some of the areas our faculty are investigating with the assistance of machine learning tools.

    The computational power of machine learning can screen and reject millions of possible combinations that allow researchers to hone in on the best solutions. This process would otherwise take decades of trial and error in a laboratory setting.

    Faculty involved: Amir Barati Farimani, B. Reeja Jayan, Venkat Viswanathan

  • 3d printed parts

    Design and manufacturing

    With artificial intelligence and machine learning, our experts are transforming and optimizing design and manufacturing. Here are a few examples: creating new concepts for cars and aircraft with design DNA; using computer vision to detect flaws during 3D printing; turning static drawings into active simulations with smart design tools; and developing virtual reality engineering simulations to place students in an interactive, immersive manufacturing environment.

    Faculty involved: Amir Barati Farimani, Jack Beuth, Jonathan Cagan, Burak Kara, Christopher McComb, Sneha Prabha Narra, Kenji Shimada, Conrad Tucker, Jessica Zhang

  • traffic light with red lit

    Autonomous vehicles

    The concept of a self-driving car was once a dream of future technology. Today, autonomous vehicles are a reality. How do we ensure that these vehicles are safe—at intersections, on highways, and in parking lots?

    Our experts use machine learning to make self-driving cars smarter and safer through simulations, unsupervised active perception, and the design and testing of intelligent physical systems.

    Faculty involved: Amir Barati Farimani, Ding Zhao

  • aerial drone in a canal

    Infrastructure, smart cities, and society

    Inspecting canals and power plants with drones, mapping air pollution and calibrating low-cost air quality sensors, desalinating water with new, energy-efficient materials, and using social media data to predict threats... these are a few examples of how machine learning can play a role in maintaining and improving the infrastructure in our communities.

    Faculty involved: Amir Barati Farimani, Albert Presto, Allen Robinson, Kenji Shimada, Conrad Tucker

  • hand typing on a keyboard

    In the curriculum

    The Department of Mechanical Engineering recognizes that tomorrow's mechanical engineers will need a new set of tools and resources for solving the world's complex challenges. That is why we have built artificial intelligence and machine learning coursework into the curriculum for both undergraduate and graduate students. Explore a sampling of courses:

    Learn about our new M.S. in Artificial Intelligence Engineering - Mechanical Engineering degree program.  Whether pursuing academia or industry, this degree uniquely positions students for the future of research and high demand careers with a mastery of integrating engineering domain knowledge into AI solutions.

     

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