How machine learning helps MEMS actuators move in perfect lines

Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and ...
mccormick.northwestern.edu

New Machine Learning Framework Enables Data-Efficient Design of Advanced Metamaterials

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...
mccormick.northwestern.edu

MECH_ENG 395: Machine Learning for Mechanical Sciences

Mechanical engineering has traditionally relied on physics, mathematics, and empirical knowledge to design and optimize systems. Machine learning (ML) introduces powerful tools that can complement ...

Automating microfluidic chip design: Hybrid approach combines machine learning with fluid mechanics

Researchers led by Assoc. Prof. Dr. Savaş Taşoğlu from the Department of Mechanical Engineering at Koç University have ...
Michigan Technological University

Researchers Apply Machine Learning and AI in Search of Less Costly Electronic Structure Method

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...
Machine Design

Leo AI: How CAD-Aware AI is Changing Mechanical Design and Engineering Workflows

This startup has developed an AI copilot for mechanical engineers. At the heart of the innovation is a Large Mechanical Model (LMM), a patented AI system that understands real CAD data. Leo AI is a ...
North Penn Now

Machine Learning Using Python: A Complete Learning Path With Practical Projects

Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...