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.
Machine learning and AI
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.
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.
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.
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.
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.
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:
- Artificial intelligence and machine learning - project course
- Machine learning and aritificial intelligence for engineers
- Bayesian machine learning for scientists and engineers
- Deep learning for engineers
- Linear control systems
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.
A call to integrate AI and STEM education Opens in new window
Artificial intelligence (AI) has penetrated the job landscape and is of great interest to educators. As we develop methods for integrating AI and STEM education to transform the U.S. workforce, we also need to broaden the public’s awareness of what AI can do now.
Using deep learning to research material transport in the brain
Understanding the causes of degenerative diseases like Alzheimer's, Huntington's, and Parkinson's will require the meticulous investigation into the complex, branch-like neurite networks of the brain. Machine learning can be an efficient, highly accurate part of this process.